Introduction
Dodigovic (2007) defined AI as machines that emulate the behavior of intelligent beings—and a field that applies the principles of the human mind to the design of technologies. Although scholars have proposed a variety of alternatives, this definition characterizes the key feature of many, if not most, of these variants.
As many researchers and commentators propose, artificial intelligence or AI is likely to become increasingly important over the years to tertiary education (e.g., Educause, 2018, 2019). To illustrate the potential impact, in one course, coordinated by Professor Ashok Goel, the students wanted to nominate an online teaching assistant—Jill Watson—an award. The students, however, were unaware that Jill Watson was actually virtual: a teacherbot (Maderer 2016). Although the International Journal of AI in Education has published material on this topic for decades, many educators have only recently explored the potential of AI to tertiary education.
Application of AI to teaching: Intelligent tutoring systems
Many researchers have discussed or explored the benefits of intelligent tutoring systems. These tools enable institutions to present relevant information to students automatically. For example, students might type questions in a platform and receive automatized and relevant answers. Or students might receive learning materials that are relevant to their needs or competence. These tools are helpful whenever institutions cannot afford personal tutors. In essence, the AI utilizes various machine learning algorithms, such as neural networks, coupled with learner models to predict the needs of students.
Some tools utilize physiological data to guide this feedback. For example, Liu et al. (2018) reported a tool that measures the heart rate, blinks, facial expressions, and other physiological changes of students while they completed a test. These measures were utilized to predict the learning state of students and to influence the prompts these students received. Students who exhibited signs of stress, for example, can then receive feedback to regulate these emotions.
Mondragon et al. (2015) discussed a similar tool that is especially applicable to students who have been diagnosed with autism spectrum disorder. This tool is called the Integrated Specialized Learning Application. A virtual agent, called Jessie, delivers prompts and encouragement to regulate the emotional state of students and to help these students resolve problems.
Application of AI to teaching: Language education
Many institutions utilize natural language processing—machine language algorithms that analyze text—to facilitate language education. For example, when learners practice a language, many tools can recognize the language, identify errors, and deliver feedback to address these errors (e.g., Zhang & Zou, 2020). Chen et al. (2022) outlines many other examples, such as Genie Tutor.
Application of AI to teaching: Intelligent virtual reality
AI can be utilized to enhance virtual reality or other online environments that are immersive and gamified. That is, AI can customize the virtual reality experience to match the needs of each student. This approach is sometimes called intelligent virtual reality
Application of AI to teaching: Intelligent support of collaborative learning
Researchers have developed a range of AI tools that facilitate collaboration between students—collaboration that is essential to learning. For example, AI may disseminate prompts or questions that facilitate online conversations. To illustrate, Calvo et al. (2011) utilized AI to generate automatic questions and feedback, primarily to facilitate collaborative writing. Alternatively, AI might summarise online discussions, and human tutors can then utilize this information to deliver feedback and to guide the students.
Application of AI to assessment and evaluations
Tertiary education institutions are increasingly applying AI to assess and evaluate both students and staff. For example, institutions can utilize AI to grade essays and other assignments automatically (e.g., Perin & Lauterbach, 2018). Indeed, AI can grade student essays accurately. In one study, for example, agreement between AI and human evaluations of the same essays, submitted by postgraduate medical students, exceeded 95%. In this study, the institution applied LightSIDE, open-source Java software.
Institutions can also utilize AI to identify violations of academic integrity. To illustrate, some machine learning algorithms, utilized by Amigud et al. (2017), estimate the degree to which students had submitted work that was similar to their past assignments. The accuracy was around 93%.
Admittedly, AI may not be as useful to assessment in all fields and in all circumstances. Obviously, institutions need to collect a large database of graded assignments to calibrate the AI. Therefore, AI cannot be readily developed to grade assignments in small classes in which the tests change frequently. Furthermore, students are sometimes dissatisfied with the feedback they receive from AI (e.g., Dikli, 2010)
Some AI, however, has been specifically designed to deliver feedback. For example, some tools utilize natural language processing to identify shortcomings in the writing of students and to deliver feedback in response (e.g., Garcia-Gorrostieta et al., 2018). Other tools have been designed to deliver prompts when students are unsure how to proceed on a task (Huang et al., 2008) or to alert trainee pilots as their situational awareness subsides (Thatcher, 2014)
Institutions have also utilized AI to evaluate teaching rather than only students. For example, Duzhin and Gustafsson (2018) utilized AI to evaluate competing teaching methods. This study, for example revealed that online homework exercises, in which feedback was automated and immediate, was more likely to benefit students than clickers.
Application of AI to student services: Mental health support
Institutions may also utilize AI to enhance the mental health and wellbeing of their students and staff. As Rutkin (2015) revealed, many AI apps have already been developed to achieve this goal. For instance, Moodnotes monitors the emotions of individuals across time and circumstances—and, therefore, provides users with insights on the causes and determinants of their mood
Application of AI to administration: Decision making around admission and support
Like in many industries, tertiary education institutions often utilize AI—or, more specifically, machine learning algorithms—to predict the outcomes of students. For example, AI can be used to predict the likelihood that a student may withdraw from a course. These predictions can then inform decisions, such as whether to admit a student or how to assist a student (see Phani Krishna et al., 2018). Although institutions can utilize classical statistical techniques to generate these predictions, machine learning algorithms tend to be more accurate, especially when the dataset is extensive and the relationships are complicated.
Application of AI to administration: Evaluation of programs
Moye (2019) published a book on how AI could be used to improve the capacity of institutions to evaluate their performance. That is, machine learning can be applied to measure and to evaluate the curriculum, teaching, and support services, as well as identify opportunities to improve.
Challenges of AI in tertiary education: Ethical implications
Tertiary education institutions need to consider many of the ethical implications of AI to their sector. First, as the potential of AI escalates, many staff may be concerned that chat bots, expert systems, and many other tools could supplant their jobs. Although some jobs will inevitably become increasingly redundant over time, the stress and uncertainty of these impending changes may not only compromise the wellbeing of staff but also tends to impair commitment, engagement, innovation, and performance.
Second, to be effective, the analytics that underpin AI tend to benefit from extensive data. Consequently, institutions become increasingly motivated to collect and to store data on all facets of life. This obsession with data may culminate in a range of complications, such as breaches of privacy or inadequate data protection (Li, 2007; Zawacki-Richter et al., 2019). The Institute for Ethical AI in Education was established to address such ethical concerns about AI in education but is unlikely to be able to prevent all these complications.
Challenges of AI in tertiary education: Costs
Many authors, such as Welham (2008), acknowledge the extensive costs of AI in the realm of tertiary education. These expenses, however, are diminishing over time. In the future, the benefits of AI will become especially likely to outweigh these costs.
Challenges of AI in tertiary education: Attitudes of staff
Many teaching staff are reluctant to utilize AI. Their concerns may stem from an array of matters, ranging from a discomfort with unfamiliar technology to worries their job may become redundant (Popenici & Kerr, 2017). According to Chen, institutions should consider several avenues to address this reluctance. In particular, institutions could
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arrange more opportunities that enable teaching staff to contribute to the development of these platforms; teaching staff can then utilize the expertise of the needs and preferences of students as well as the challenges and complications of the learning material
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offer more personalized, technical support to staff who are not as familiar with these technologies
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conduct more studies to compare AI and traditional approaches on the satisfaction and outcomes of students
Challenges of AI in tertiary education: Developmental opportunities
As Pence (2019) acknowledges, AI might compromise the development of academic staff. Specifically, as AI becomes more advanced, this technology might supplant many human roles, such as tutors or teaching assistants. Therefore, many of the roles that support inexperienced researchers might dissipate. Consequently, fewer competent researchers may be attracted to these roles, compromising the development of academics.
Similarly, Pence (2019) argues that AI might diminish the time that academics interact with students. These interactions are rewarding and helpful to staff. Changes that diminish these interactions might decrease the satisfaction and development of these staff. This problem is comparable to concerns that medical practitioners have expressed after computers diminished patient contact and often impaired the satisfaction of these doctors.
References
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Amigud, A., Arnedo-Moreno, J., Daradoumis, T., & Guerrero-Roldan, A.-E. (2017). Using learning analytics for preserving academic integrity. International Review of Research in Open and Distance Learning, 18(5), 192–210.
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Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges.
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Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education? International Journal of Educational Technology in Higher Education, 17(1), 1–12
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Calvo, R. A., O’Rourke, S. T., Jones, J., Yacef, K., & Reimann, P. (2011). Collaborative writing support tools on the cloud. IEEE Transactions on Learning Technologies, 4(1), 88–97
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Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two decades of artificial intelligence in education: Contributors, collaborations, research topics, challenges, and future directions. Educational Technology & Society, 25(1), 28–47.
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Dikli, S. (2010). The nature of automated essay scoring feedback. CALICO Journal, 28(1), 99–134.
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Dodigovic, M. (2007). Artificial intelligence and second language learning: An efficient approach to error remediation. Language Awareness, 16(2), 99–113.
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Duzhin, F., & Gustafsson, A. (2018). Machine learning-based app for self-evaluation of teacher-specific instructional style and tools. Education Sciences, 8(1).
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EDUCAUSE. (2018). Horizon report: 2018 higher education edition.
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EDUCAUSE. (2019). Horizon report: 2019 higher education edition.
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Garcia-Gorrostieta, J. M., Lopez-Lopez, A., & Gonzalez-Lopez, S. (2018). Automatic argument assessment of final project reports of computer engineering students. Computer Applications in Engineering Education, 26(5), 1217–1226.
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Gierl, M., Latifi, S., Lai, H., Boulais, A., & Champlain, A. (2014). Automated essay scoring and the future of educational assessment in medical education. Medical Education, 48(10), 950–962.
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Huang, C.-J., Chen, C.-H., Luo, Y.-C., Chen, H.-X., & Chuang, Y.-T. (2008). Developing an intelligent diagnosis and assessment e-Learning tool for introductory programming. Educational Technology & Society, 11(4), 139–157
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Li, X. (2007). Intelligent agent-supported online education. Decision Sciences Journal of Innovative Education, 5(2), 311–331.
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Liu, S., Chen, Y., Huang, H., Xiao, L., & Hei, X. (2018, December). Towards smart educational recommendations with reinforcement learning in classroom. In 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) (pp. 1079-1084). IEEE.
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Mondragon, A.L., Nkambou, R., Poirier, P. (2015). Towards an integrated specialized learning application (ISLA) to support high functioning asd children in mathematics learning. In Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, E. (Eds) Design for Teaching and Learning in a Networked World. EC-TEL 2015. Lecture Notes in Computer Science, vol 9307. Springer, Cham.
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Moye, J. N. (2019). A machine learning, artificial intelligence approach to institutional effectiveness in higher education: Vol. First edition. Emerald Publishing Limited.
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Pence, H. E. (2019). Artificial intelligence in higher education: New wine in old wineskins? journal of Educational Technology Systems, 48(1), 5–13.
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Perin, D., & Lauterbach, M. (2018). Assessing text-based writing of low-skilled college students. International Journal of Artificial Intelligence in Education, 28(1), 56–78.
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Phani Krishna, K. V., Mani Kumar, M., & Aruna Sri, P. S. G. (2018). Student information system and performance retrieval through dashboard. International Journal of Engineering and Technology (UAE), 7, 682–685.
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Popenici, S., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 22.
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Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599
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Rutkin, A. (2015). Therapist in my pocket. New Scientist, 227(3038), 20
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Thatcher, S. J. (2014). The use of artificial intelligence in the learning of flight crew situation awareness in an undergraduate aviation programme. World Transactions on Engineering and Technology Education, 12(4), 764–768
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Welham, D. (2008). AI in training (1980–2000): Foundation for the future or misplaced optimism? British Journal of Educational Technology, 39(2), 287–303.
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Yu, S., & Lu, Y. (2022). An introduction to artificial intelligence in education. Springer Singapore Pte. Limited.
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Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International Journal of Educational Technology in Higher Education, 16(1), 1-27.
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Zhang, R., & Zou, D. (2020). Types, purposes, and effectiveness of state-of-the-art technologies for second and foreign language learning. Computer Assisted Language Learning, 1–47.
Student evaluations of teaching quality
Introduction
Tertiary institutions need to measure the quality of teaching at their organization. This information may guide the feedback that teachers receive to improve their classes as well as inform decisions about promotions, awards, performance management, and extensions to contracts. Positive evaluations can also be promoted in marketing campaigns.
Institutions may utilize multiple sources of information to evaluate teaching staff. Most commonly, students may complete questionnaires to evaluate teachers (Spooren 2010; Rantanen 2013). Peers might also evaluate the teaching practices of one another. Specialists can observe and appraise teachers. Or institutions can utilize objective information, such as examination performance, to assess teachers. Finally, institutions can ask teaching staff to present a portfolio, demonstrating the resources and initiatives they utilize to teach effectively.
Evaluation instruments
To ascertain the biases that could distort teacher evaluations, Spooren (2010) validated an instrument that comprises 37 items and assesses 12 facets of teaching. For example, some items, such as “The information presented by the lecturer at the start of the course clearly specified what I should learn and accomplish”, measured the degree to which the teacher communicated the course objectives clearly. Some items, including “The lecturer explained the material well”, gauged the presentation skills of teachers. Some items, including “This lecturer did not give any performance feedback throughout the course” (reverse scores), reflected the extent to which the teacher arranged formative assessments. Other items assessed whether the examinations correspond to the learning content, relevance of the materials, and assistance in response to questions or challenges. Confirmatory factor analysis indicated all the items and facets load onto a single factor, representing teacher quality.
Researchers and institutions have implemented many other instruments or questionnaires to evaluate teaching quality. These instruments include the Student Evaluation of Educational Quality (Marsh, 1982; Marsh et al. 2009) and the Student Course Experience Questionaire (Ginns, Prosser, and Barrie 2007).
Applications of evaluations
To measure how tertiary institutions utilize student evaluations of teachers, Vasey and Carroll (2016) administered a survey that over 9000 academics from American universities completed. This survey generated some interesting findings.
First, since the advent of online teaching, the proportion of students who completed these evaluations had diminished. That is, when students needed to complete these evaluations on paper, in a class, about 80% evaluated the teacher. However, when students completed these evaluations online, this percentage dropped to between 20% and 40%. This finding suggests that institutions should, whenever possible, encourage students to complete evaluations in person
Second, in general, a central department tended to develop the instrument. In over 50% of instances, academics were not granted opportunities to contribute their expertise to shape this instrument. Similarly, few academics were permitted to customize this instrument or approach to accommodate the distinct characteristics of their discipline. Yet, in many instruments, the questions that are valid in one discipline may not be valid in another discipline. Furthermore, according to Vasey and Carroll (2016), an undue emphasis on standard instruments generates unreasonable comparisons across disciplines. As many authors, such as Cashin (1990) and Feldman (1978), have discussed, students tend to rate courses that are harder, courses that are electives, and courses in the humanities more favorably than other courses.
Third, most academics recognized that students should be permitted to complete the evaluations anonymously; otherwise, they might not be willing to express their concerns about the course. Nevertheless, when students complete evaluations anonymously, their responses are sometimes discriminatory, inappropriate, or belligerent. Conceivably, students could be informed their responses will be confidential, but their identity can be determined if their responses violate the code of conduct or rules of the institution and disciplinary action can be considered.
Potential biases: Course grades
Some commentators dismiss procedures in which students evaluate teachers, maintaining that too many events could bias the responses. For example, one possibility is that students who are pleased with their grades are more likely to evaluate teachers favorably, whereas students who are displeased with their grades are more likely to evaluate teachers unfavorably.
Spooren (2010) collected data that partly, but not wholly, verifies this assumption. To evaluate teachers, around 12000 students at a Flemish university completed an instrument, comprising 37 items that measure 12 facets of teaching—such as whether the examinations correspond to the learning content, clarity of the course objectives, relevance of the materials, and assistance in response to questions or challenges. The analyses revealed that students who received higher course grades were more likely to evaluate the teacher positively. Nevertheless, the effect size was small: course grade explained only 6.3% of the variance in teacher evaluations.
This small effect implies the bias might be modest. Nevertheless, this finding could have underestimated the effect of satisfaction with grades on teacher evaluations. That is, course grade does not necessarily coincide strongly with satisfaction with grades. Students might receive high grades but feel their marks should have been higher. Conversely, students might receive low grades but feel this mark is deserved. As this argument indicates, the extent to which students are satisfied with the grades might explain more than 6.3% of the variance in teacher evaluations.
Despite this small effect, teaching staff are often concerned that grades will bias evaluations. In one survey, conducted by Vasey and Carroll (2016), the majority of participants somewhat or strongly agreed that teaching staff feel pressure to raise grades primarily to prevent harsh evaluations.
Potential biases: Student preferences
As Feistauer and Richter (2017) revealed, the preferences of students, such as whether they like to be challenged by teachers, appreciably influences and potentially biases evaluations. As this finding implies, unfavorable evaluations merely indicate the student does not prefer this particular style—and these preferences can vary considerably across students. Consequently, when other students evaluate the same teacher, the results can change substantially.
One of the implications of these results is that institutions should not encourage all teachers to adopt the same teaching style and practices. Instead, teachers may need to adapt their practices to accommodate students. Alternatively, whenever more than one person can teach a specific course or module, which students are assigned to which teacher may also need to be considered and determined carefully.
Potential biases: Teacher rank
Students might evaluate more senior professors more favourably than junior academics. For example, if students do not understand a lecturer, they might ascribe this confusion to either the pre-eminent intelligence of the senior, renowned professor or to the incompetence of a junior academic. Consistent with this possibility, Spooren (2010) revealed that students to evaluate full professors more favourably than other teaching academics. However, the effect size was very small, indicating this effect of teacher rank is not especially consequential.
Other potential biases
Many other circumstances may bias the responses to these evaluations. For example, as Vasey and Carroll (2016) indicate, students are often especially stressed as their final examination approaches. This stress might culminate in harsher ratings if evaluations are administered at this time. This consideration implies that evaluations should perhaps be administered after stress has diminished but perhaps before the final grade is released
Reliability over time
To demonstrate that student evaluations of teachers are useful, researchers first need to show that random variations do not appreciably influence the results. That is, researchers need to establish the evaluations are reliable; otherwise, these evaluations should not be trusted because the pattern of results could be very different if the instrument was administered again.
Researchers can adopt several approaches to measure reliability. One approach is to assess whether the responses of students towards the same teacher is consistent over time, often called stability That is, in some circumstances, an instructor might teach different courses or units to the same individuals. The same cohort of students, therefore, will evaluate this instructor more than once. Research in these circumstances suggest that responses of students towards the same teacher are typically consistent over time (e.g., Rantanen, 2013; Rindermann & Schofield, 2001).
To illustrate, Irby et al. (1977) prompted students to evaluate teachers after the first lecture and after the course ended, several months later. The ratings were relatively stable over time. That is, students who evaluated the teacher favorably after the first lecture tended to evaluate the teacher favorably after the final lecture. This possibility is consistent with literature on the need for closure, in which many individuals form impressions prematurely, called seizing, and are reluctant to shift these impressions, called freezing (Kruglanski & Webster, 1996).
Recommendations about sample size
When institutions need to evaluate teachers, they should perhaps consider the range of guidelines, proposed and justified by Rantanen (2013). Specifically, according to Rantanen (2013), if institutions want to evaluate whether instructors taught a specific course effectively, evaluations from 15 students is usually sufficient to generate a reliable estimate, even if the number of students in the class is particularly high. Indeed, this number can be as low as 9 if the class size is 20, 10 if the class size is 30, 11 if the class size is 40, and 12 if the class size is 50. These recommendations are predicated on the assumption that students who complete the evaluation are representative of all students in the class and are not especially lenient or harsh.
Conceivably, to assess whether these evaluations are representative, institutions could implement the evaluation over successive times. For example, the institution might first distribute the survey as usual and analyse the data. Second, the institution might then disseminate more information to encourage responses, such as the instruction “We need to collect at least 10 more responses”. This approach enables the institution to ascertain whether the mean response changes as increasingly more students complete the evaluations. If the mean response does not change, the institution can be relatively confident that students who completed the evaluation are representative of all students in the class.
In contrast, if institutions want to evaluate the quality of teacher overall, and not the quality of particular class, the minimum number of responses changes. Specifically, Rantanen (2013) developed a table that can guide these decisions. According to this table
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if institutions have evaluated 7 classes that an instructor has taught, at least 36 students need to have evaluated this instructor; otherwise, the results are unlikely to be reliable
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if institutions have evaluated 5 classes that an instructor has taught, at least 52 students need to have evaluated this instructor
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if institutions have evaluated 4 classes that an instructor has taught, at least 85 students need to have evaluated this instructor
These recommendations are predicated on the assumption that reliability of measurements should exceed .90. Levels that are lower than .90 indicate the measure should not inform significant decisions.
To generate these recommendations, Rantanen (2013) partitioned the sources of variance that influence teacher ratings. That is, many circumstances can affect teacher evaluations, such as the quality of teachers, the biases of students, the content of these courses, and the number of times the teacher has presented this course. For example, teachers might receive more favourable evaluations because they communicate effectively, because they are similar to students, because the course revolves an interesting topic, or because the teacher has taught this course before. These four determinants of teacher evaluations are sometimes called teacher, student, course, or implementation. The study that Rantanen (2013) conducted was designed to assess all these sources of variance simultaneously.
Recommendations about practices
Fewer studies have explored how tertiary institutions, managers, and teaching staff utilize the responses they receive from students. Nevertheless, a variety of practices could be considered to enhance the utility of these data. For example, according to Overall and Marsh (1979), teaching staff should be granted the opportunity to discuss the evaluations they receive from students with an external consultant. A frank discussion with this person could uncover some key insights.
Recommendations about principles
The Statement on Teaching Evaluation, released by the American Association of University Professors, enumerates several detailed principles that institutions should follow when they evaluate teachers. To illustrate, according to these standards
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institutions should clarify, as precisely as possible, the key priorities and expectations they want teaching staff to fulfill
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institutions should stipulate the weight they assign teaching in writing and the criteria they will utilised to evaluate teachers
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the institution must utilize multiple sources of data to evaluate teachers—such as the materials they have developed and methods they apply. The activities that teachers undertake, such as their workload, number of classes, difficulty of classes, and capacity to shape the course, must be considered before conclusions are generated.
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academics should meaningfully and genuinely be able to contribute to instruments and methods that are designed to seek the opinions of their students
References
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American Association of University Professors (1975). Statement on Teaching Evaluation. https://www.aaup.org/report/statement-teaching-evaluation
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Educational Psychology, 71, 6, 856–865.
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Emery, C. R., Kramer, T. R., & Tian, R. G. (2003). Return to academic standards: A critique of student evaluations of teaching effectiveness. Quality assurance in Education.
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Feistauer, D., & Richter, T. (2017). How reliable are students’ evaluations of teaching quality? A variance components approach. Assessment & Evaluation in Higher Education, 42(8), 1263-1279.
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Ginns, P., Prosser, M., & Barrie, S. (2007). Students’ perceptions of teaching quality in higher education: The perspective of currently enrolled students. Studies in Higher Education, 32(5), 603-615.
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instructional improvement and students’ cognitive and affective outcomes. Journal of
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Khamis, N. K., Sulong, A. B., & Deros, B. M. (2012). A case study on peer review and lecturer evaluations in an academic setting. Asian Social Science, 8(16).
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Kruglanski, A. W., & Webster, D. M. (1996). Motivated closing of the mind: "Seizing" and "freezing." Psychological Review, 103, 263-283.
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Makondo, L., & Ndebele, C. (2014). University lecturers’ views on student-lecturer evaluations. The Anthropologist, 17(2), 377-386.
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Marsh, H. W. (1982). The use of path analysis to estimate teacher and course effects in student ratings of instructional effectiveness. Applied psychological measurement, 6(1), 47-59.
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Marsh, H. W., & Bailey, M. (1993). Multidimensionality of students' evaluations of teaching effectiveness: A profile analysis..Journal of Higher Education, 64, 1–18.
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Marsh, H. W., & Hocevar, D. (1991). The multidimensionality of students' evaluations of teaching effectiveness: The generality of factor structures across academic discipline, instructor level, and course level. Teaching and Teacher Education, 7, 9–18.
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Marsh, H. W., & Overall, J. U. (1979). Long-term stability of students' evaluations..Research in Higher Education, 10, 139–147.
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Marsh, H. W., & Roche, L. A. (1992). The use of student evaluations of university teaching in different settings: The applicability paradigm. Australian Journal of Education, 36(3), 278-300.
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Marsh, H. W., & Roche, L. A. (2000). Effects of grading leniency and low workloads on students' evaluations of teaching: Popular myth, bias, validity or innocent bystanders? Journal of Educational Psychology, 92, 202–228.
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Marsh, H. W., Muthén, B., Asparouhov, T., Lüdtke, O., Robitzsch, A., Morin, A. J., & Trautwein, U. (2009). Exploratory structural equation modeling, integrating CFA and EFA: Application to students' evaluations of university teaching. Structural equation modeling: A multidisciplinary journal, 16(3), 439-476.
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of university instruction across courses and teachers. Research in Higher Education, 42, 377–98.
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Overall, J.U., & H.W. Marsh. (1979). Midterm feedbacks from students: It’s relationship to
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Rantanen, P. (2013). The number of feedbacks needed for reliable evaluation. A multilevel analysis of the reliability, stability and generalisability of students’ evaluation of teaching. Assessment & Evaluation in Higher Education, 38(2), 224-239.
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Rindermann, H., & N. Schofield. (2001). Generalizability of multidimensional student ratings
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Sahin, S. (2008). An application of peer assessment in higher education. Turkish Online Journal of Educational Technology-TOJET, 7(2), 5-10.
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Spooren, P. (2010). On the credibility of the judge: A cross-classified multilevel analysis on students’ evaluation of teaching. Studies in educational evaluation, 36(4), 121-131.
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Vasey, C., & Carroll, L. (2016). How do we evaluate teaching? Findings from a survey of faculty members. American Association of University Professors. https://www.aaup.org/article/how-do-we-evaluate-teaching#.Ytz1h-xBy3J
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Watkins, D., & Akande, A. (1992). Student evaluations of teaching effectiveness: A Nigerian investigation. Higher Education, 24(4), 453-463.
Benchmarking in tertiary education
Introduction to benchmarking
Tertiary education institutions often engage in benchmarking exercises, partly to improve their operations and partly to comply with the demands of regulations and accreditation bodies. Broadly, benchmarking refers to the act in which institutions continually and systematically compare themselves to competitors in their industry and strive to uncover better practices. Despite the simplicity of this definition, benchmarking comprises a diverse range of activities. For example, to benchmark effectively, institutions should
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assess the degree to which their courses, research, and other activities comply with relevant standards or regulations
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assess how their courses, research, and other activities are ranked compared to other similar institutions in their nation
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assess how they are perceived by students and other stakeholders relative to other institutions
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assess how their practices overlap and diverge from the practices of exemplary institutions
This document, therefore, introduces some of the latest advances on these activities. Other documents will receive specific analyses and approaches, such as university rankings, in more detail.
Introduction to benchmarking: History
According to Vlăsceanu et al. (2004), who briefly traces the history of benchmarking in tertiary education institutions, this exercise first surfaced in the USA during the early 1990s. For example, the National Association of Colleges and University Business Officers, conducted benchmarking research and published reports that disseminate data about member institutions. In 1997, the Dearing Committee Report was published in the UK. This report, intended to improve higher education in the nation, included several examples of benchmarking.
Introduction to benchmarking: Main phases
Many authors have developed simple models to characterize the main phases of benchmarking. For example, according to Drew (1997) and Spendolini (1992), organizations should
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determine which practices or attributes they should benchmark and improve, such as assessment practices
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establish a team to coordinate this benchmarking, comprising both specialists in benchmarking and specialists in the practices or attributes to benchmark
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the team should identify partners—such as collaborators at other institutions—with whom to compare their results.
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the team should then collect and analyze data that measures and compares these practices or attributes in the various institutions
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finally, the team should interpret the results—such as identify shortfalls relative to competitors, identify possible improvements, develop a plan to implement these improvements, and monitor progress on this plan over time
Some other models, such as the six phases that Alcoa recommend (Bemowski, 1991) and the benchmarking wheel (Bhutta & Huq, 1999), are similar and comprise overlapping activities. Other models insert some additional phases. For example,
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according to Partovi (1994), before institutions choose which activities to benchmark, they should conduct a situational analysis, in which they identify the opportunities and challenges to the business, as well as clarify the key features or benefits of their services.
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these activities will help institutions choose which activities to benchmark.
In contrast, Camp (1989), in a seminal book on this topic, differentiated 12 phases of benchmarking. This sequence imparts greater insight on how to analyze and apply the data. Specifically, institutions should
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determine which domain to benchmark, such as student assessment
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define the process to benchmark, such as the grading of assessments
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identify potential partners, such as similar institutions who might also want to collaborate on the benchmarking exercise
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identify data sources, such as databases that stores grades and feedback on past assignments or future assignments
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collect data and select all partners
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determine the gap; that is, identify measures in which the institution performs less proficiently than do other institutions
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establish process differences; that is, conduct a more comprehensive approach, such as interviews and document analysis, to determine some of the practices that rivals apply that could explain discrepancies in the measures
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target future performance; clarify the targets on these measures the institution should reach in one year, for example
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communicate the results and plans to the relevant stakeholders, such as a teaching and learning committee
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adjust goals to accommodate these stakeholders
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implement a plan to achieve these goals
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review performance and recalibrate the plan, if necessary
Key activities: Decide which activities or attributes to benchmark
Asif (2015) proposed a method that tertiary education institutions could apply to decide which activities or attribute they would like to improve and to benchmark. In essence, Asif recommended that institutions apply a practice called analytic hierarchy process—a variant of multiple criteria decision making.
To illustrate, a strategic plan might delineate 11 priorities a university wants to pursue, such as excellent research infrastructure, innovation, collaboration with industry, innovative course designs, effective teaching approaches, exemplary curriculum development, proficient student performance, and excellent academic productivity. Relevant stakeholders, such as executives and government representatives, could then be asked to indicate the degree to which they believe each priority is more important than another priority. For example, they could be asked, on a scale of 1 to 9, to what extent do you believe collaboration with industry is more important than effective teaching approaches. Institutions can then utilize various tools, such as Expert Choice, to subject these responses to analytic hierarchy process. Analytic hierarchy processes will then generate the weight or importance that should be attached to each priority. For example, this technique might reveal that
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research infrastructure should be assigned a weight of .8
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innovation should be assigned a weight of .45
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collaboration with industry should be assigned a weight of .65 and so forth
The institution might then utilize benchmarking to improve only the three or four priorities that were assigned the highest weights. This technique might seem simple, but is powerful because
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the stakeholders can more readily compare the importance of two priorities at a time but cannot as readily compare many priorities simultaneously
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the technique generates additional metrics to validate the estimates; for example, consistency indices can identify stakeholders whose responses were inconsistent and thus should be discarded
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this technique can simultaneously examine priorities at multiple levels, such as broad priorities—such as teaching versus research—and specific priorities—such as assessment versus induction
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many software and tutorials are available to help specialist learn and conduct analytic hierarchy processes
Daultani et al. (2021) utilized another variant of multiple-criteria decision-making, called data envelopment analysis, to also determine the most important priorities. However, these researchers used this technique to ascertain which attributes of courses students prioritize. For example, after they applied data envelopment analysis, the researchers concluded that, to decide which engineering course to choose, prospective students tend to prioritize the fees, location, perceived employment opportunities, and compatibility between the course and preferred stream of engineering.
Key activities: Determine which institutions to examine and which data to utilize
Regardless of how they conduct benchmarking, institutions must decide with which competitors they would like to compare themselves. As part of a broader study, Tasopoulou and Tsiotras (2017) explored how institutions reach this decision. Specifically, the researchers administered a questionnaire that was designed to characterize the benchmarking practices of universities globally. The questionnaire was distributed to executives and senior administrators—such as presidents, provosts, deans, quality managers and policy advisors—of 300 universities. Although executives from 200 universities responded, the data of only 20 universities was detailed enough to utilize in the analysis. These universities were located in America, UK, Australia, the Netherlands, Switzerland, and Scandinavia.
In one of the questions, participants were prompted to detail how the institutions identify which competitors with which they will compare themselves. The respondents suggested a range of answers. For example, institutions may compare themselves to
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competitors in the same geographical region
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competitors in their region that perform at a similar level or greater level on research, teaching, or other rankings, depending on which activity they want to explore
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competitors that seem most similar—in specialties, size, and priorities
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competitors in which staff have already developed strong contacts
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competitors who are experiencing similar challenges
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competitors in their cohort, such as the Russel group in Britain or the Group of Eight in Australia
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competitors who have introduced some change or initiative that is relevant
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local, national, or international trends in some activity, derived from official report
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their own performance and metrics over time rather than other institutions
In another question, participants were prompted to detail how the collect data about these competitors. Again, the respondents entered a range of answers. Specifically, institutions may
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contact staff at other institutions and offer to share data, collaborate on a benchmarking project, or even visit one another
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utilize data on best practices that accreditation bodies, relevant associations, peak bodies, or cohorts freely share
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utilize data that government agencies produce—such as data about research performance or student satisfaction
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administer surveys or conduct interviews to collect their own data about other institutions
To illustrate, in Australia, to compare themselves to competitors, institutions will often utilize
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the database of research income in each university, called the Higher Education Research Data Collection, available from the Department of Education website
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the database of higher degree by research completions in each university, also available from the Department of Education website
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the Quality Indicators of Learning and Teaching or QIL—a website that presents the data collected from the student experience survey, the graduate outcomes survey, including the postgraduate research experience questionnaire, and the employee satisfaction survey
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international rankings, including the Sustainable Development Goals
Alternatively, in principle, institutions could survey their existing staff who have worked at rival organizations. These staff could be asked to detail how the practices of their past employers differ from their practices of their current workplace.
Key activities: Examine measures of alignment
Many benchmarking exercises include alignment analysis. To illustrate examples of alignment, institutions may want to ascertain whether
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the assessment of a particular course or subject aligns to the learning outcomes of this course or subject
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the learning outcomes of this course align to the learning outcomes of the entire degree
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the learning outcomes of an entire degree align to the national or industry standards
Lau et al. (2018) proposed an approach, derived from an integration of the revised Bloom taxonomy and Cohen’s κ statistic, that institutions could apply to gauge various kinds of alignment. To understand this approach, institutions need to be aware of the revised Bloom taxonomy. Specifically, as this taxonomy applied, individuals can learn a concept or skill to various degrees. For example, after attending a class on statistics, students might be able to
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remember or recite various statistical tests
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understand—such as summarize or describe—these tests
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apply—such as use these tests to solve a problem
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analyze—such as appreciate the main phases of these tests, the similarities and differences between these tests, integrate these tests, and infer other information about these tests
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evaluate—such as use these tests to judge the validity or utility of other procedures
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create—such as design improvements to these tests
The revised Bloom taxonomy also distinguishes four kinds of knowledge to learn: concepts, facts, procedures, and meta-cognitive knowledge, such as knowledge about how to learn this material. This taxonomy can help institutions measure alignment. Specifically, education specialists might first apply this taxonomy to evaluate the assessment of a course. They might, for example, conclude the assessments of this units assess whether students can
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apply concepts
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analyze facts
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evaluate procedures or skills
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understand meta-cognitive knowledge
Second, to evaluate the level of knowledge that correspond to the learning outcomes of a course, specialists can apply the same procedure or taxonomy. For instance, the specialists might conclude the learning outcomes imply that students should be able to
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evaluate concepts
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analyze facts
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evaluate procedures or skills
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understand meta-cognitive knowledge
This analysis reveals a slight discrepancy: the course learning outcomes indicate that students should be able to evaluate concepts, but the assessment gauges only whether students can apply concepts. If the course learning outcomes differ from the assessments on several kinds of knowledge, specialists can utilize various statistics, such as Cohen’s κ statistic, to measure the level of discrepancy.
Finally, institutions can apply the same procedure to gauge alignment between other activities, such as whether the course learning outcomes align with the degree learning outcomes and whether the degree learning outcomes align with national standards.
Key activities: Use software tools to collect, analyze, display, and interpret data
To conduct a benchmarking exercise, institutions can invest in a range of software tools. Obviously, institutions can apply many of the techniques and tools they would typically utilize to collect, analyze, and display data—such as surveys, R, and so forth. But some tools have been specifically developed to facilitate benchmarking and include
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PowerStats.com: This tool enables a cohort of institutions, such as several universities, to compare their practices and performance. In essence, representatives of each institution regularly answer questions about their organization. The tool then generates charts to compare the performance and practices of these institutions.
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Combo Benchmark: Provides similar benefits to PowerStats.com
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Baromitr.com: Provides similar benefits to PowerStats.com
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SAP Value Lifecycle Manager: When institutions access this tool, users will receive surveys and answer questions about existing practices in the organization as well as the goals they want to achieve. The tool will then generate various displays or scorecards, indicating which practices need to be improved, as well as present specific recommendations on how to improve these practices. The tool will also display performance relative to competitors that also use this platform.
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INDEC Gobench: A platform that enables you to enter information about your institution—such as fees, technologies, patents, marketing, customers, products, and practices—and to store information about competitors and the market. The tool can then identify your strengths and weaknesses relative to competitors.
Benefits of benchmarking
When institutions conduct benchmarking effectively, they may uncover a range of insights that could inform many improvements. To clarify these benefits of benchmarking, Tasopoulou and Tsiotras (2017), in their survey of executives and senior administrators of universities across the globe, invited these participants to detail the outcomes of these benchmarking exercises. Participants revealed that benchmarking can
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uncover innovations that will improve the quality of education, research, and service
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unearth more efficient administrative arrangements and reduce unnecessary administrative costs
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help institutions choose investments that will attract a strong return
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improve the capacity of institutions to recruit, to enroll, to engage, and to retain students
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uncover opportunities to collaborate with other universities and share costs
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improve the satisfaction and sense of empowerment in staff
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facilitate accreditation
References
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Alhammadi, A & Alayed, S. (2022). The effect of benchmarking reasons on benchmarking success: An empirical study on public universities.Uncertain Supply Chain Management, 10(2), 375-382.
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Anand, G., & Kodali, R. (2008). Benchmarking the benchmarking models. Benchmarking: An International Journal.
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Asif, M. (2015). Determining improvement needs in higher education benchmarking. Benchmarking: An International Journal.
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Bemowski, K. (1991). The benchmarking bandwagon. Quality Progress, 24(1), 19-24.
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Bhutta, K. S., & Huq, F. (1999). Benchmarking–best practices: An integrated approach. Benchmarking: An International Journal.
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Camp, R. (1989). The search for industry best practices that lead to superior performance. Productivity Press.
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Dahikar, P., & Ghatole, S. (2021). Role of benchmarking in best practices for Higher Education Quality Enhancement. The Research Journal.
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Daultani, Y., Dwivedi, A., & Pratap, S. (2021). Benchmarking higher education institutes using data envelopment analysis: capturing perceptions of prospective engineering students. Opsearch, 58(4), 773-789.
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Drew, S. A. (1997). From knowledge to action: the impact of benchmarking on organizational performance. Long Range Planning, 30(3), 427-441.
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Lau, K. H., Lam, T. K., Kam, B. H., Nkhoma, M., & Richardson, J. (2018). Benchmarking higher education programs through alignment analysis based on the revised Bloom’s taxonomy. Benchmarking: An International Journal.
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Partovi, F. Y. (1994). Determining what to benchmark: an analytic hierarchy process approach. International Journal of Operations & Production Management.
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Pino-Mejías, J. L., & Luque-Calvo, P. L. (2021). Survey of methods for ranking and benchmarking higher education institutions. In Handbook of Operations Research and Management Science in Higher Education (pp. 159-211). Springer, Cham.
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Spendolini, M. J. (1992). The Benchmarking Book. New York7 American. Management Association.
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Tasopoulou, K., & Tsiotras, G. (2017). Benchmarking towards excellence in higher education. Benchmarking: An International Journal.
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Vlăsceanu, L., Grünberg, L., & Pârlea, D. (2004). Quality assurance and accreditation: A glossary of basic terms and definitions (p. 25). Bucharest: Unesco-Cepes.
Academic promotion
Introduction
In most tertiary education institutions, to be promoted, academic staff need to submit an application. The application might outline their teaching, research, and engagement as well as include evidence of their contributions. Yet, the procedures that staff and promotion committees apply vary considerably across institutions. These variations can affect
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the degree to which the institution is perceived as fair and just
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which staff will remain committed and which staff will be inclined to leave the institution, and
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the productivity and priorities of staff
Criteria to evaluate promotions: Overview
The criteria that institutions consider to reach decisions about promotions varies considerably across institutions. Rice et al. (2020), for instance, examined the criteria of 92 universities that publicized their promotion guidelines. This study was restricted to universities that conducted research, teaching, or both in biomedical sciences. The researchers determined whether the promotion guidelines considered five traditional criteria and seven other criteria. The five traditional criteria revolved around
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the number, quality, or both of publications
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whether the publications were first authored
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the journal impact factor that corresponds to each publication
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grant funding and other research income
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whether the research is recognized internationally
The seven other criteria—criteria that are not as traditional—revolved around
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the number of citations
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the level of data sharing
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the degree to which publications are open access
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whether studies have been pre-registered
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whether reporting guidelines of journals were observed
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altmetrics
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adjustments because of leave
As this study revealed, in the biomedical sciences, 95% of institutions considered the number, quality, or both of publications and 67% considered grant funding and other research income. About a third to a half considered the other traditional criteria. However, fewer than 5% of institutions considered the other criteria, except 26% considered number of citations and 37% considered adjustments because of leave.
Criteria to evaluate promotions: The H index
Promotion decisions that are informed by only a couple of measures or criteria—such as research income and teaching evaluations—may disregard the other contributions of academics. In contrast, promotion decisions that are informed by an extensive array of measures or criteria will circumvent this problem. However, when promotion boards consider many criteria, two problems unfold
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Members of the promotion board may feel inundated with information, potentially obscuring the clarity of their judgments
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Applicants cannot predict whether their application is likely to be successful
To override this problem, institutions may seek indices or measures that combine several criteria. To illustrate, institutions might consider the h-index of academics. To demonstrate this index
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academics are assigned a h-index of 2 if two of their publications are cited by at least two other publications
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academics are assigned a h-index of 3 if three of their publications are cited by at least three other publications
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more generally, academics are assigned a h-index of x if x of their publications are cited by at least x other publications
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this index thus depends on both the number of publications and number of citations these publications tend to attract.
Wang et al. (2022) suggested that promotion boards should consider the h-index. To justify this suggestion, the authors revealed that h-indices do tend to vary linearly with academic level. That is, in one department of an American university
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the h-index was higher in professors than associate professors and higher in associate professors than assistant professors
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specifically, in professors, the h-index was usually about 17 and tended to range from 9 to 23
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in associate professors, the h-index was usually about 11 and tended to range from 9 to 18
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in assistant professors, the h-index was usually about 6 and tended to range from 1.5 to 9.5
These findings may inform both promotion boards and applicants. If a h-index is above 10, for example, promotion boards should be more likely to promote assistant professors to associate professors.
Determinants of promotion: Gender and academic disciplines
Some research indicates that promotions may be biased towards men. To illustrate, Millar and Barker (2020) conducted a study to explore whether academic promotions, from associate professor to full professor in Ontaria between 2010 and 2014, depended on gender. Men were more likely to be promoted than women. This disparity subsided appreciably after the academic discipline of these applicants were controlled.
As this finding reveals, men tend to work in academic disciplines in which promotions are more likely. That is, in some academic disciplines, especially the disciplines that men dominate, promotion applications are more likely to be approved. One reason is that academics in some disciplines have published more articles than academics in other disciplines merely because more authors are included in each paper.
Yet, this variation in academic discipline cannot explain the bias towards men entirely. Even in specific disciplines, men are more likely to be promoted than women. In 2002, Nonnemaker (2000) examined the prevalence of promotions in individuals who had graduated from American medical schools between 1979 and 1997. This study revealed that men were more likely than women to be promoted to higher positions in academic medical centers.
Richter et al. (2020) then explored whether this pattern shifted over the next two decades. The sample comprised over 500 000 graduates from 134 American medical schools. Relative to men, fewer women were promoted to senior academic positions, such as full professor or department chair. This pattern was observed in both the basic sciences and clinical departments—even after controlling racial group, ethnic group, and graduation year. Furthermore, this disparity in gender was as pronounced after 1997 compared to before 1997.
Some research has attempted to explore the obstacles that impede the promotion of female academics. To illustrate, Bowering and Reed (2021) interviewed 52 academics, employed at two Canadian universities, about how conflicts between teaching, research, and service responsibilities as well as home duties affect promotions to full professor. Women tended to report more impediments than men: They feel more obliged to complete tasks that were not perceived as helpful to promotions, such as student support roles, and thus felt they were granted less time to conduct research. They were also more likely to be targets of bullying, compromising the support and confidence they need to seek promotions.
Determinants of promotion: Race or ethnicity
Besides gender, studies have also explored whether race or ethnicity affects the likelihood that academics will submit a promotion application and whether this application will be successful. Abelson et al. (2018), for example, compared the likelihood that black academic surgeons and white academic surgeons would be promoted. The results showed that black assistant professors were not as likely to be promoted as their white counterparts. This difference between black assistant professors and white assistant professors may not emanate from biases in promotion boards but might instead indicate disparities in support, training, or other provisions.
Nevertheless, as Durodoye et al. (2020) underscored, the effect of race or ethnicity on promotions varies markedly across disciplines. Under-represented minorities—such as African American, Hispanic, and American Indian academics in American universities—are not as likely to be promoted in Business, Education, Health, and Veterinary Sciences. In some other fields, the effect of race or ethnicity was only modest or negligible.
Determinants of promotion: Mobility
Academics, from their graduate studies onwards, often shift to other tertiary education institutions and sometimes to other nations. This mobility can improve the networks and knowledge of academics, but can also compromise their capacity to utilize the reputation and trust they have developed in a single institution. Therefore, in principle, mobility can either impede or expedite promotions.
Ryazanova and McNamara (2019) conducted a study to explore these dynamics in business academics. The results uncovered a complicated and nuanced pattern of observations. First, this study explored how mobility could affect the research productivity of academics. Specifically, between the second and seventh years after academics had completed their PhD, shifts to other institutions, both within and outside the nation, tend to increase the number of publications—potentially augmenting the likelihood of promotions. That is, these academics are often exposed to productive and illuminating research environments. Specifically, shifts to a strong research university can enhance the research skills and opportunities of academics. Yet shifts to a university that is not as prestigious can be beneficial too—as these academics may be perceived as especially valuable contributors and thus supported handsomely
Yet, mobility does not seem to attract more citations. Perhaps, if academics shift too often, they may not become as embedded within a research community—communities that are more likely to cite their work.
Nevertheless, this effect of mobility on research productivity does not extend to promotions. That is, promotions were often delayed in academics who shifted to other nations or who shifted more than a few times in the other country. Perhaps, academics need to remain longer at each institution to develop the reputation and opportunities that facilitate promotions. Conversely, academics who shift to another institution or nation may not appreciate the cultural nuances and expectations initially, impeding promotions.
Determinants of promotion: Academic leadership programs
Some research has shown that specific academic leadership programs may enable academics to receive promotions within a shorter period. To illustrate, Weill Cornell Medicine, a biomedical college of Cornell University, designed and implemented a program that supports the development and promotion of their academics, called the Leadership in Academic Medicine Program.
The program lasts 10 months and primarily consists of afternoon sessions on self-awareness, self-management, career planning, and leadership. Specialists on the relevant topics facilitate workshops and discussions on team building, time management, presentation skills, mentorship, negotiation, managing other people, conflict resolution, feedback delivery, and wellbeing. Furthermore, one of the topics is designed to demystify and to clarify the process to seek academic promotions. Participants also complete a capstone project that overlaps with academic goals but applies the insights these individuals gained from the program, supported by senior mentors.
As surveys revealed, participants gained many skills from this program, such as time management and comfort with negotiation. More importantly, participants were not only significantly more likely to understand the promotion process but more likely to be promoted earlier than a control group. These participants were also not as inclined as control individuals to leave the organization.
Determinants of promotion: Peer mentoring
Research has shown that peer mentoring programs also increase the likelihood that academics will receive promotions. Prendergast et al. (2019), for example, designed an initiative they called the enhanced peer mentoring program. In addition, academics were assigned to peer groups. A senior academic assumed the role of facilitator. The peer groups met four times a year over five years.
To decide which topics to discuss, peers discussed their main concerns and completed surveys. The facilitators choose topics that revolved around the key anxieties and worries of academics, such as how to balance work and family life, how to network effectively, how to pursue a promotion, and how to manage personal careers.
These peer groups were typically effective. After year five years, the research income these academics earned soared. In addition, the percentage of these academics who received promotions increased noticeably as well.
Concerns about existing policies around academic promotion: Reliance on journal impact factors
To evaluate the promotion applications of academics, promotion boards often consider the quality of journals in which the applicants have punished. For example, these boards might encourage applicants to specify the journal impact factor of each publication.
The problem, however, is that journal impact factors do not necessarily correspond to the quality of impact of a specific publication. Indeed, journal impact factors evolved as a measure that libraries could use to decide which journals to purchase. The San Francisco Declaration on Research Assessment, or DORA thus warned that institutions should not use journal impact factors, or other measures of journals, to gauge the quality of individual publications in decisions around promotions—a document that over 15 000 individuals have signed.
More disconcertingly, journal impact factors do not always differentiate genuine publications from predatory outlets. That is, when the journal impact factor is modest, the journal may publish valid and informative papers in some instances or may be a predatory outlet in other instances—in which the publication was not actually peer reviewed (Broome et al., 2021). Promotion guidelines seldom if ever allude to predatory journals (Broome et al., 2021). According to Broome et al. (2021), promotion boards should be more concerned about journals that are predatory than journals in which the impact factor is modest.
Rather than journal impact factors, Steck et al. (2020) recommended that promotion committees encourage applicants to specify the relative citation ratio of their publications. The relative citation ratio represents the number of citations a publication receives relative to other papers in the same field. Therefore
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a value that exceeds 1 indicates the publication has attracted more citations than a median paper in the field
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a value that is lower than 1 indicates the publication has attracted fewer citations than a median paper in the field
Indeed, Steck et al. (2020) showed that a journal impact factor is not an accurate surround of a relative citation ratio. That is, even if a journal is deemed as high quality, the publication may not be high in quality and vice versa. Indeed, the correlation between journal impact factor and relative citation ratio was only .34 in a sample of 1199 publications of one faculty.
Strategies to submit compelling promotion applications
Scholars have written many books, articles, and chapters on how academics can increase the likelihood their promotion applications will be successful (e.g., Cawkwell, 2019; Mahat & Tatebe, 2019). To illustrate, according to Roberts (2020), applicants should first develop a timeline. Often, the promotion guidelines of an institution might suggest a timeline—but applicants tend to feel especially motivated if they outperform this timeline (see Burgess et al., 2004). To illustrate
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about 14 months before the application is due, seek advice from a senior academic, such as a chair or director, about the strengths and limitations of your CV
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about 12 months before the application is due, collect relevant evidence of quality, such as teaching evaluations and external referees. Develop a narrative or statement that outlines your key goals and achievements cohesively. This narrative should outline the reasons various decisions were reached, such as the choice to change from one research topic to another research topic
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if necessary, at this time, plan how you to collate more evidence, such as designated leadership roles, letters from colleagues, or other metrics that assess scholarship activity and service. The narrative should demonstrate how the applicant is forging progress towards a particular vision and passion.
In addition, applicants should
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contact mentors in your institution—and seek advice insights about the problems that other academics have experienced and the differences between successful and unsuccessful applications. Also ask these mentors to consider which of your strengths you should underscore and which of your limitations you should address
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not only read the promotion guidelines carefully but also scrutinize other information, such as the position description of their role.
Cawkwell (2019) presents specific examples of the evidence and materials that academics could perhaps collate to demonstrate their proficiency in teaching and learning. For example, academics could uncover opportunities to collate
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publications, research proposals, or other evidence of research into teaching and education—such as research on some teaching innovations
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photographs of participation in student events, such as creative displays during open days or other community events
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evidence of occasions in which they taught the classes of peers who were absent or ill
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resources they developed to assist learning in other schools or departments, such as materials to assist doctoral candidates, assessment tools, and teaching activities
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evidence of attempts to disseminate knowledge about teaching in various forums, such as social media, university committees, and discussion groups
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information about the official and unofficial roles they assumed in teaching and learning, such as a program convenor, mentor of staff, especially during induction, or student services liaison
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evidence of personal development around teaching, such as reflective journals, peer observations, or course review
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feedback from students, peers, or alumni as well as teaching awards
Admittedly, some advice about promotions might seem generic. In contrast, some books offer advice to academics in specific nations (e.g., Mahat & Tatebe, 2019). This advice is often more pertinent because the suggestions consider the distinct priorities and frameworks of each nation.
Concerns about existing policies around academic promotion: Disregard of digital scholarship
An increasingly central feature of academia revolves around digital scholarships, such as posts on social media. That is, academics feel obliged to promulgate their work in social media—to disseminate their insights and to translate their research into practice. Yet, as many studies reveal, when they decide whether to approve a promotion application, promotion boards often disregard these activities. Indeed, according to Cabrera et al. (2018), members of these boards are often unfamiliar with altmetrics and other measures of these activities.
To address this concern, many scholars recommend that academics maintain a social media portfolio (Cabrera et al., 2018; Husain et al., 2020). When academics construct these portfolios, they should include
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the goals and objectives of this digital scholarship—such as to improve environmental practices in schools
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the audience that might directly or obliquely benefit from this digital scholarship
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how these social media activities might help these academics fulfill their career goals
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an outline of the original content, curated content, and other information that were posted on social media
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how this digital scholarship complements traditional scholarship, such as journal articles and conferences
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metrics around the impact of these activities, such as page views, altmetrics, and other measures
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how these social media activities are compatible with the institutional standards and expectations of these academics
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practices they applied to improve and to check the quality of their digital scholarship, such as external reviews
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other indices that measure the overall quality of their digital scholarship—perhaps with reference to measures such as the social media index, available at www.aliem.com/social-media-index/
Institutions should then clarify how they will measure social media and other digital activity.
References
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Abelson, J. S., Wong, N. Z., Symer, M., Eckenrode, G., Watkins, A., & Yeo, H. L. (2018). Racial and ethnic disparities in promotion and retention of academic surgeons. The American Journal of Surgery, 216(4), 678-682.
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Alali, S. (2022). A model for Enhancing Academic Staff Promotion System in Vocational and Technical Education: College of Technological Studies, As A Case Kuwait. International Journal of Teaching and Education, 10(1), 1-9.
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Bowering, E., & Reed, M. (2021). Achieving academic promotion: The role of work environment, role conflict, and life balance. Canadian Journal of Higher Education, 51(4), 1–25
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Broome, M. E., Oermann, M. H., Nicoll, L. H., Waldrop, J. B., Carter‐Templeton, H., & Chinn, P. L. (2021). Publishing in predatory journals: Guidelines for nursing faculty in promotion and tenure policies. Journal of Nursing Scholarship, 53(6), 746–752
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Burgess, M., Enzle, M. E., & Schmaltz, R. (2004). Defeating the potentially deleterious effects of externally imposed deadlines. Personality and Social Psychology Bulletin, 30, 868-877.
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Cabrera, D., Roy, D., & Chisolm, M. S. (2018). Social media scholarship and alternative metrics for academic promotion and tenure. Journal of the American College of Radiology, 15(1), 135-141.
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Cawkwell, J. (2019). Academic Promotion in the UK: Your Guide to Success. In Achieving Academic Promotion. Emerald Publishing Limited.
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DORA – San Francisco Declaration on Research Assessment (DORA).
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Durodoye, R., Gumpertz, M., Wilson, A., Griffith, E., & Ahmad, S. (2020). Tenure and promotion outcomes at four large land grant universities: Examining the role of gender, race, and academic discipline. Research in Higher Education, 61(5), 628-651.
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Forsberg, E., Levander, S., & Elmgren, M. (2022). Peer Review in Academic Promotion of Excellent Teachers. In Peer review in an Era of Evaluation (pp. 245-274). Palgrave Macmillan, Cham.
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Husain, A., Repanshek, Z., Singh, M., Ankel, F., Beck-Esmay, J., Cabrera, D., ... & Brumfield, E. (2020). Consensus guidelines for digital scholarship in academic promotion. Western Journal of Emergency Medicine, 21(4), 883.
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Johng, S., Mishori, R., & Korostyshevskiy, V. (2021). Social media, digital scholarship, and academic promotion in US medical schools. Family Medicine, 53(3), 215-219.
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Lissoni, F., Mairesse, J., Montobbio, F., & Pezzoni, M. (2011). Scientific productivity and academic promotion: a study on French and Italian physicists. Industrial and Corporate Change, 20(1), 253-294.
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Macfarlane, B. (2007). Defining and rewarding academic citizenship: The implications for university promotions policy. Journal of Higher Education Policy and Management, 29(3), 261-273.
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Mahat, M., & Tatebe, J. (2019). Achieving academic promotion (M. Mahat & J. Tatebe, Eds.). Emerald Publishing.
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Millar, P. E., & Barker, J. (2020). Gender and academic promotion to full professor in Ontario. Canadian Journal of Sociology, 45(1), 47-70.
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Mullangi, S., Blutt, M. J., & Ibrahim, S. (2020). Is it time to reimagine academic promotion and tenure? In JAMA Health Forum (Vol. 1, No. 2, pp. e200164-e200164). American Medical Association.
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Nezhad, M. A., Tatari, F., & Borji, A. (2019). A comprehensive approach to faculty members' promotion policies. Journal of Advanced Pharmacy Education & Research Jul-Sep, 9(3).
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Ngalomba, S. P. (2022). Influence of Salary and Promotion on Academic Staff's Job Performance in Tanzanian Universities. Papers in Education and Development, 40(1).
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Nonnemaker, L. (2000). Women physicians in academic medicine—new insights from cohort studies. New England Journal of Medicine, 342(6), 399-405.
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Teaching awards in tertiary education
Introduction
Many tertiary education institutions have introduced teaching awards to recognize teaching staff who demonstrate exemplary performance. Many national peak bodies also award excellent teaching (Chalmers 2011). For example, the UK government introduced the Teaching Excellence Framework—a scheme that evaluates the quality of undergraduate teaching, rates universities as gold, silver, or bronze, and affects some of the rights of these institutions. Research has revealed that teaching rewards can be beneficial but can also provoke a range of complications as well.
Introduction: Prevalent criteria
To evaluate applications, institutions often ascertain whether the practices of teaching staff fulfill a set of criteria. Miller-Young et al. (2020) conducted a study to identify the prevailing criteria that institutions utilize to appraise teaching practice. These authors examined the assessment criteria applied in 89 Canadian higher education institutions. The assessment criteria, listed from most to least common, revolved around the degree to which the applicant
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demonstrates concern for the growth and development of individual students, called student centeredness
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introduced a range of innovative, novel, and effective teaching practices
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attempted to promote exemplary teaching practices across the institution, called campus leadership
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demonstrated a positive impact on student learning
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engaged in research or scholarship around teaching practices, such as piloted various practices or attended conferences on teaching, called the scholarship of teaching
Miller-Young et al. (2020) uncovered some other criteria as well—although these criteria were assessed in fewer than 20% of the awards, such as professional development around teaching, innovation in curriculum or course design, mastery of the subject, diversity of teaching activities or practices, and tendency to integrate research into the classroom. About 20% of awards did not specify criteria at all.
The study also explored the evidence that applicants could submit to support their case. The most common examples of evidence were letters of support, statements about teaching philosophy, student evaluations, and to a lesser extent classroom observations. None of the evidence, however, could demonstrate careful reflection and personal growth around teaching.
Concerns about teaching awards: Cynicism
Despite the ubiquity of teaching awards, these schemes are sometimes contentious and can provoke a range of concerns. To illustrate, according to some research, teaching awards can provoke cynicism. To illustrate, some researchers and staff perceive teaching awards as an opportunity to reward exemplary staff and boost morale while circumventing the need to boost salaries (Mackenzie, 2007). Many awarded staff would rather be promoted or rewarded financially. Some individuals, therefore, might sometimes perceive awards as an attempt to manipulate staff, feigning support towards exemplary teaching but not willing to direct significant funds to this endeavor.
One possible solution would either be to accompany these awards with financial payments, such as funds to conduct research, or be more explicit about how promotion committees consider these awards. However, as Seppala and Smith (2020) revealed, after conducting interviews about teaching awards, this solution may culminate in a range of problems. In particular, if the stakes are raised too high, these awards may become more contentious and divisive. Individuals may become more concerned about potential biases—biases that are hard to eradicate completely.
Concerns about teaching awards: Reduced collaboration
Scholars have argued that teaching awards might also impede collaboration between colleagues. To illustrate, heads of departments often encourage colleagues to assist one another and to operate as a team. Teaching awards, however, are often directed at individuals rather than teams. Therefore, when one individual receives a reward, members of the team might feel their contributions have been overlooked (Chalmers, 2011; see also Madriaga & Morley 2016). Over time, this feeling could manifest as a reluctance to operate as a team and work collectively. Accordingly, some researchers argue that teaching awards will not necessarily improve the overall teaching performance of institutions (Halse et al., 2007). Even awards to specific teams might evoke similar resentment from the overarching department.
Feys et al. (2013) conducted a study that illustrates this dynamic in a scenario study, conducted in a health setting rather than education setting. Staff in this health setting completed a questionnaire. Embedded in the questionnaire was a scenario. This scenarios prompted the participants to imagine a colleague in their organization. Depending on which questionnaire they received, they needed to imagine either a colleague they trust and like or a colleague they distrust and dislike. Next, these participants were prompted to imagine this colleague had been praised or criticized strongly by a supervisor. Finally, participants completed questions that assess their mood and motivation to engage in helpful behaviors.
The results were interesting. If participants liked the colleague, they experienced more positive emotions whenever this colleague was praised rather than criticized and were less inclined to engage in behaviors that could hurt or offend this person. In contrast however, if participants disliked the colleague, they experienced more negative emotions whenever this colleague was praised rather than criticized and become more inclined to engage in behaviors that could hurt or offend this person, such as spreading rumors. Thus, people who receive awards or recognition might become targets of harassment or similar behaviors, but only if distrusted or disliked.
Concerns about teaching awards: Expectations on recipients
As some researchers argue, teaching awards might also elicit unpleasant emotions or experiences in the staff who receive the award. Some individuals might experience imposter syndrome, in which they feel their award is undeserved and are concerned their limitations will eventually surface. So, staff who receive awards might feel pressure to demonstrate they deserve this recognition, potentially culminating in anxiety or burnout (Mackenzie, 2007).
To illustrate, as Seppala and Smith (2020) reported, after staff earn a teaching award, they are often invited to share their practices around teaching innovations. Although they perceived these opportunities as beneficial to colleagues, these recipients of teaching awards often feel burdened by the need to engage in these activities despite their heavy workloads.
This expectation to share teaching is not only burdensome but can also bias perceptions about these recipients of teaching awards. For example, because they are renowned as exemplary teachers, these individuals may be equated with teaching instead of research. Hence, colleagues and managers may assume their research skills and productivity is limited—as some research verifies (e.g., Fitzpatrick & Moore, 2015; Seppala & Smith, 2019)
Benefits of teaching awards: Confidence and motivation
Despite some concerns, teaching awards may generate a range of benefits. Teaching awards, for example, can encourage innovation in teaching, both before and after individuals receive these awards (Willingham-McLain, 2015). In one study, conducted by Willingham-McLain (2015), online questionnaires were distributed to academics who had received teaching awards at one university. Thirty participants completed the questionnaire. The questions revolved around the impact of this award, attitudes towards this award, and how other people responded to this award. The award generated a range of benefits
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in general, the award improved their confidence of these individuals as teachers; consequently, these individuals often felt more inspired to pursue more innovation in teaching
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since the award, these individuals were more likely to be invited to workshops as panelists and asked to offer advice on how to improve teaching
Other studies have uncovered some analogous results. Brawer et al. (2006), for example, surveyed 33 academics who had received a teaching award in the Faculty of Medicine. About 45% of these individuals reported that, after they received the award, they felt even more inspired to enhance the quality of their teaching.
According to Seppala and Smith (2020), teaching awards may be especially inclined to improve the confidence and motivation of academics who are commencing their career. That is, as participants of this study reported, when academics commence their career, few colleagues are cognizant of their skills. Their confidence and status are often limited. To gain this confidence and status, some academics need to establish their research track record over many years. In contrast, recipients of teaching awards sometimes feel the award had circumvented this long route. That is, some but not all these recipients felt vindicated almost immediately.
Benefits of teaching awards: Opportunity to learn about exemplary teaching practices
Typically, to receive a teaching award, teaching staff need to submit an application that outlines some of their teaching innovations and philosophies. Institutions can utilize or integrate this information to generate reports, or other documents, that outline exemplary teaching practices.
To illustrate, Rossetti and Fox (2009) analyzed the applications of 35 university professors who had received teaching awards at an American university. These applications prompted these professors to outline their educational philosophy and goal statements. An analysis of these applications uncovered some key themes about exemplary teaching practice. For example, these professors tended to
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learn about each student, including his or her name, and attempt to customize their advice to accommodate the distinct needs, interests, problems, and experiences of each person
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help students perceive their learning as meaningful to their lives and values—partly by demonstrating and experiencing great enthusiasm about the topic and about teaching
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show respect to each student and demonstrate they are motivated to interact and listen to the perspectives of these individuals
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challenge themselves and experiment with novel methods and the latest advances in the field
Similarly, teaching awards can also benefit members on the judging committee. To illustrate, in one paper, several midcareer academics, who participated in a judging panel, wrote about the knowledge and insights they gained from this experience (Brawer et al., 2006). During this experience, the panel members needed to read nomination dossiers, compare these dossiers to the selection criteria, assemble to discuss their evaluations, prepare feedback letters, and attend the awards ceremony. The authors reflected on how these activities shaped their own perspectives and practices around teaching. For example, while reading the dossiers
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the members tended to contemplate why they adopted specific teaching practices and whether these reasons have limited the strategies they apply
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the members felt inspired to overcome their inertia or habits and instead attempt some of the innovations that other teachers outlined
Benefits of teaching awards: Increased attention to teaching initiatives
Teaching awards can also legitimize and attract more attention to other initiatives that are designed to improve teaching quality. For example, according to some academics that Seppala and Smith (2020) interviewed in their study about teaching awards, academic staff are often skeptical about the benefits of initiatives that institutions have introduced to improve teaching—such as learning workshops, teaching conferences, and mentoring programs. However, awards seem to legitimize the importance of these initiatives. When academics are informed that exemplary teaching will be awarded, they become more inclined to attend these events.
Costs versus benefits of teaching awards
As the research shows, teaching awards can benefit institutions but may also be detrimental. Whether the benefits outweigh the costs is likely to vary across institutions.
Besides institutions, applicants may also need to decide whether the potential benefits of these awards outweigh the costs of application. As Owence et al. (2018) showed, many academics feel the costs outweigh the benefits of applying for a Vice Chancellor or President teaching awards—that is, awards that are conferred by the institution. According to these academics
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the application is often taxing and cumbersome, demanding considerable time and effort
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yet, the likelihood of an award is limited, because the assessment may be unfair and biased, diminishing the potential value of this effort.
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even if they prevail, the award is often perceived as not as prestigious as research grants (Van Note Chism, 2006), at least in some departments.
This concern that teaching awards may be unfair, biased, or inaccurate may be founded. After all, as Van Note Chism (2006) revealed, about 50% of schemes around teaching awards do not define the hallmarks of good teaching or stipulate the criteria to evaluate these awards. Therefore, whether these teaching awards reflect good practice is uncertain.
Associations between teaching awards and student learning
To substantiate the benefits of teaching awards, researchers could examine whether these awards are indeed associated with student learning and student experience. For example, studies could explore whether the students taught by staff who receive these rewards were more satisfied with their learning experience and benefited from these staff.
Studies have not uncovered definitive results about the association between teaching awards and student experiences or learning. To illustrate, in an innovative study, Brew and Ginns (2008) examined whether an index that measures the scholarship of teachers was related to the responses of students on a questionnaire. The index of scholarship was related to
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the number of teaching awards this academic had received or whether they had been a finalist—including state awards, national awards, college or faculty awards, and the Vice Chancellor’s award
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whether the individuals had attained a qualification in university teaching
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the number of publications or conference papers on university teaching
This index was associated with some measures of student experience. For example, when teachers were high in this index of scholarship, their students were more likely to report
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greater satisfaction with the degree
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better development of generic skills, such as writing and communication,
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their goals and expectations were clear
Although encouraging, the results do not necessarily reveal that awarded teachers enhance the student experience. That is, scores on the index also depended on the number of publications around teaching and university qualifications around teaching—and these activities, rather than rewards, could explain the observed relationships.
Recommendations on how to improve teaching awards
After conducting 21 interviews about teaching awards—with a range of academics, only some of whom had received teaching awards—Seppala and Smith (2020) suggested a few recommendations on how to improve the awards. Specifically
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more awards should recognize teams rather than individuals, to promote collaboration and knowledge exchange about teaching
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more awards should recognize academics who mentor peers or share knowledge and resources about teaching
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during awards nights, individuals should be granted more opportunities to share insights on innovative and exemplary teaching practices, because the audience often feel motivated to improve their teaching at this time; the emphasis of these awards nights should be to celebrate the role of teaching and innovation rather than to boost the ego of some academics to the detriment of everyone else
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staff who receive awards should be granted opportunities to mentor colleagues—but should not feel obliged to assume this role, because otherwise awards are perceived as a source of elevated workload, unreasonable expectations, and increased pressure
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although tertiary education institutions must reward staff who excel in teaching—such as increase the degree to which student satisfaction and learning is considered in promotion applications—they should not accompany teaching awards with major financial benefits; otherwise, the awards can become too contentious and divisive.
Examples of national awards
Many countries have introduced national awards, designed to recognize and to inspire exemplary teaching. National awards often inspire the institutions to introduce analogous awards at a university or institution level. To illustrate a national award, in 1997, the Australian government introduced the Australian Awards for University Teaching—and revised these awards in 2006. By 2022, the Australian Awards for University Teaching comprised five categories:
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citations for outstanding contributions to student learning
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awards for programs that enhance learning
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awards for teaching excellence and award for Australian university teacher of the year
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career achievement award—only applicable to staff who have contributed over 25 years
Specifically, institutions can apply to receive up to six citations, each of which recognize the contributions of individuals or teams, including both academic and professional staff, to enhance student learning. Up to 100 citations can be awarded. Specific categories are available to early career staff and indigenous staff.
Second, institutions can also apply to receive up to two awards for programs that enhance learning—teams that have introduced some program or service that enhances the student experience. These programs could be initiatives that support inclusive practices, facilitate work integrated learning, or introduce some innovative pedagogy.
Third, institutions can also apply to receive up to three awards for teaching excellence. This award recognizes teachers who have shown leadership in their capacity to enhance the student experience and learning outcomes. The best application will be awarded Australian university teacher of the year.
The application must address the selection criteria in ten pages, together with evidence and references. For example, to evaluate the awards for programs that enhance learning, applicants need to show how the program
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enhanced the student experience or student learning
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gained recognition from other people and benefited other people, such as other departments
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demonstrated innovation and enhanced the learning environment
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was informed by the scholarly literature
References
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Bethel, K., Fuhrman, N. E., Copenheaver, C. A., & Hollandsworth, K. C. (2021). Winning an external teaching award in higher education: Teacher identity and recipient characteristics. Journal of Agricultural Education, 62(2).
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Bornais, J., & Buchholz, A. C. (2018). Becoming a more reflective teacher by serving on a university teaching awards committee. Transformative Dialogues: Teaching and Learning Journal, 11(1).
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Brawer, J., Steinert, Y., St-Cyr, J., Watters, K., & Wood-Dauphinee, S. (2006). The significance and impact of a faculty teaching award: disparate perceptions of department chairs and award recipients. Medical Teacher, 28(7), 614-617.
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Brew, A., & Ginns, P. (2008). The relationship between engagement in the scholarship of teaching and learning and students’ course experiences. Assessment & Evaluation in Higher Education, 33(5), 535-545.
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Chalmers, D. (2011). Progress and challenges to the recognition and reward of the scholarship of teaching in higher education. Higher Education Research & Development, 30(1), 25-38.
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Feys, M., Anseel, F., & Wille, B. (2013). Responses to co‐workers receiving recognition at work. Journal of Managerial Psychology.
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Fitzpatrick, M., & Moore, S. (2015). Exploring both positive and negative experiences associated with engaging in teaching awards in a higher education context. Innovations in Education and Teaching International, 52, 621-631.
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Frame, P., Johnson, M., & Rosie, A. (2006). Reward or award? Reflections on the initial experiences of winners of a National Teaching Fellowship. Innovations in Education and Teaching International, 43(4), 409-419.
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Gibbs, G. (2008). Designing teaching award schemes. York: The Higher Education Academy.
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Gunn, A. (2018). Metrics and methodologies for measuring teaching quality in higher education: developing the Teaching Excellence Framework (TEF). Educational Review, 70(2), 129-148.
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Halse, C., Deane, E., Hobson, J., & Jones, G. (2007). The research–teaching nexus: What do national teaching awards tell us? Studies in Higher Education, 32(6), 727-746.
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Kreber, C. (2000). How university teaching award winners conceptualise academic work: Some further thoughts on the meaning of scholarship. Teaching in Higher Education, 5(1), 61-78.
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Lewis, J. M. (2018). Teaching styles of award-winning professors. In Handbook of Quality Assurance for University Teaching (pp. 273-285). Routledge.
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Lowe, T., & Shaw, C. (2019). Student perceptions of the ‘best’ feedback practices: an evaluation of student-led teaching award nominations at a higher education institution. Teaching & Learning Inquiry, 7(2), 121-135.
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Mackenzie, N. (2007). Teaching excellence awards: An apple for the teacher? Australian Journal of Education, 51(2), 190-204.
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Madriaga, M., & Morley, K. (2016). Awarding teaching excellence: ‘What is it supposed to achieve?’ Teacher perceptions of student-led awards. Teaching in Higher Education, 21(2), 166-174.
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Miller-Young, J., Sinclair, M., & Forgie, S. (2020). Teaching excellence and how it is awarded: A Canadian case study. Canadian Journal of Higher Education/Revue canadienne d'enseignement supérieur, 50(1), 40-52.
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Owence, C., Newman, W., & Kwena J, M. (2018). Staff participation in Vice Chancellor’s Teaching Excellence Awards: Why develop cold feet? Journal of Educational Studies, 17(2), 60-70.
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Rossetti, J., & Fox, P. G. (2009). Factors related to successful teaching by outstanding professors: An interpretive study. Journal of Nursing Education, 48(1), 11-16.
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Ruedrich, S. L., Cavey, C., Katz, K., & Grush, L. (1992). Recognition of teaching excellence through the use of teaching awards. Academic Psychiatry, 16(1), 10-13.
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Seppala, N., & Smith, C. (2020). Teaching awards in higher education: a qualitative study of motivation and outcomes. Studies in Higher Education, 45(7), 1398-1412.
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Smith, J. (2013). Sink or swim: The climate for teaching as viewed by award-winning teachers. The Journal of Faculty Development, 27(1), 20-27.
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Van Note Chism, N. (2006). Teaching awards: What do they award? The Journal of Higher Education, 77(4), 589-617.
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Warren, R., & Plumb, E. (1999). Survey of distinguished teacher award schemes in higher education. Journal of Further and Higher Education, 23(2), 245-255.
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Willingham-McLain, L. (2015). Using a scholarship of teaching and learning approach to award faculty who innovate. International Journal for Academic Development, 20(1), 58-75.
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Zhu, E., & Turcic II, S. M. (2018). Teaching awards: Do they have any impact? The Journal of Faculty Development, 32(3), 7-18.
The motivation to develop
Introduction
Imagine a selection committee, deciding whether an applicant, a young female lecturer, is appointable. Although this lecturer seems bright and enthusiastic, she will need to teach online but, in the past, has instructed students only in person. The selection committee needs to decide whether she can acquire this skill rapidly. They need to consider whether she is someone who can change and develop swiftly. They need to decide whether she exhibits the qualities that facilitate this development.
Often, when selection committees or managers need to decide whether a staff member, a PhD applicant, or some other candidate is suited to some role or opportunity, they need to estimate the likelihood this person can develop swiftly. That is, in most instances, applicants have not acquired the gamut of skills, capabilities, and qualities they need to thrive in this role or position. So, selection committees need to use their judgment to predict the future—to predict whether this person will develop the essential characteristics in a reasonable time.
No individual or organization has developed a standardized instrument to predict the likelihood these applicants will develop these skills rapidly enough. Instead, to reach these decisions, the selection committee need to
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assess whether the applicants exhibit the qualities that have been shown to enhance the motivation of individuals to develop
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assess whether the applicants exhibit the qualities that have been shown to enhance the capacity of individuals to develop
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determine the degree to which the qualities that applicants need to change are indeed modifiable
Motivation of individuals to change: A learning orientation
Scholars have uncovered a quality, called a learning orientation, that roughly corresponds to the extent to which individuals are motivated to develop, rather than merely to demonstrate, their capabilities. That is, some individuals often exhibit learning orientation, also called a mastery orientation or task orientation (Ames, 1984; Nicholls, 1984), in which their primary motivation is to enhance their knowledge, skills, capabilities, and qualities. Other individuals often exhibit a performance orientation, also called an ego orientation, in which their primary motivation is to demonstrate or show their capabilities and qualities. A learning orientation not only increases the likelihood that individuals might develop but also often coincides with other benefits, such as creativity (Janssen & Van Yperen, 2004) and altruism (Porter, 2005).
This distinction between a learning orientation and performance orientation emanated from research that Dweck and her colleagues conducted, primarily with primary school children (e.g., Diener & Dweck, 1978, 1980; Dweck, 1986). Children received problems to complete. As the problems became increasingly difficult, some children embraced the challenge, remaining confident and engaged as well adapting their strategies to solve these problems. Their principal goal was, seemingly, to develop their capabilities and to master these challenges, referred to as a learning orientation.
In contrast, other children become especially upset, disengaged, disinterested, and unconfident when they could no longer solve the problems, demonstrating a helpless rather than adaptive response. Their principal goal was to demonstrate and validate, rather than develop and refine, their capabilities, called a performance orientation (Dweck & Elliott, 1983.These goals orientations were later established in adults as well (Farr, Hofmann, & Ringenbach, 1993).
During the 1990s, researchers developed a more nuanced perspective. For example
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scholars recognized that individuals could demonstrate a strong motivation both to develop and to demonstrate their competence simultaneously (Button, Mathieu, & Zajac, 1996).
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researchers distinguished two variants of a performance orientation: a prove dimension, in which individuals strive to demonstrate favorable attributes, and an avoid dimension, in which individuals attempt to avoid or conceal unfavorable characteristics (e.g., VandeWalle, 1997).
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other researchers applied a comparably rationale to differentiate two variants of a learning orientation: mastery-approach in which individuals strive to develop additional capabilities and a mastery-avoidance in which individuals strive to prevent a decline in capabilities (Van Yperen et al., 2009)
Consequences of a learning orientation
Research indicates that, in general, a learning orientation, especially the variant called mastery-approach, is likely to facilitate personal development. To illustrate, when individuals report high levels of a learning orientation, but not a performance orientation
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they are more likely to seek and embrace feedback about their performance (VandeWalle & Cummings, 1997; VandeWalle et al., 2001). They are more receptive to criticism
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they are more inclined to set, and often achieve, steep goals (VandeWalle, 2001)—especially the goal to improve themselves (Brett & VandeWalle, 1999; Elliott & McGregor, 1999)
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they are more likely to perceive failures and challenges as opportunities to improve, diminishing the likelihood they will ruminate excessively after a failure (Linnenbrink et al., 2000); in contrast, a performance-avoid orientation is especially likely to elicit rumination and agitation (Cury et al., 2002)
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can often retain, transform, integrate, and consider many issues simultaneously, because they are not distracted by excessive rumination (Linnenbrink et al., 2000); that is, their working memory is often proficient (Avery & Smillie, 2012)
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learn tasks more effectively, especially when the tasks are confusing (Licht & Dweck, 1984), when participants feel stressed (e.g., Utman, 1997), or when failures are prevalent (Covington & Omelich, 1984). A performance orientation often impeded learning, partly because individuals become more inclined to learn by rote (Fisher & Ford, 1998).
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they are more receptive to diverse perspectives and thus tend to flourish in diverse teams (Pieterse et al., 2013)
Strategies to predict a learning orientation: Personality measures
To ascertain which applicants may be able to develop their capabilities and qualities, selection committees may assess the degree to which these individuals exhibit a learning orientation, especially the variant called mastery-approach. One complication, however, is that, during an interview, most applicants are likely to demonstrate, at least feign, a learning orientation. For instance, if asked to the degree to which they are motivated to improve their capabilities, most applicants will indicate this motivation is pronounced.
Instead, to assess the learning orientation of applicants, selection committees could instead monitor or gauge the personality of these individuals and utilize this information to estimate learning orientation. That is, many studies have revealed that personality is appreciably related to learning orientation.
To measure personality, these studies tend to adopt the five-factor model—a model in which proponents reduce personality to five key dimensions. In particular, according to this model, people vary on the extent to which they are
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extraverted—such as gregarious, assertive, warm, positive, active, and inclined to seek excitement
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neurotic—such as anxious, depressed, hostile, self-conscious, and volatile rather than resilient
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agreeable—such as trusting, honest, cooperative, compliant, modest, and sympathetic
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conscientious—such as methodical, motivated, disciplined, and dutiful
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open to experience—such as open to novel, intense, and diverse experiences, ideas, and values
As research suggests, these five traits are associated with a learning orientation. To illustrate
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extraversion is positively associated with a learning orientation (Zweig & Webster, 2004), inversely associated with a performance-avoid orientation (Lamm et al., 2017) in university students
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neuroticism is inversely associated a learning orientation (Lamm et al., 2017), but positively associated with a performance-avoid orientation (Zweig & Webster, 2004) in university students
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agreeableness is positively associated with a learning orientation (Zweig & Webster, 2004) and inversely associated with a performance-avoid orientation (Lamm et al., 2017) in university students
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conscientiousness is positively associated with a learning orientation (Lamm et al., 2017), but inversely associated with a performance-avoid orientation (Zweig & Webster, 2004) in university students
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openness to experience is positively associated with a learning orientation, and inversely associated with a performance-avoid orientation, in university students (Lamm et al., 2017; Zweig & Webster, 2004)
Admittedly, these associations may vary across settings. For example, Wang and Erdheim (2007) uncovered no significant association between three personality traits—agreeableness, conscientiousness, and openness to experience—and learning orientation in employees of an automobile manufacturer. Nevertheless, across studies, selection committee can assume that applicants who seem extraverted, emotionally stable, agreeable, conscientious, and open to experience a more likely to adopt a learning orientation. These applicants, therefore, will tend to be especially motivated to develop their capabilities and to adjust their qualities.
To some extent, these personality traits manifest during the interview. Nevertheless, selection committees may utilize various instruments, such as the NEO or OPQ, to measure personality. The NEO is designed to measure these five traits (Costa & McRae, 1992), although scholars have developed shorter methods too (e.g., Donnellan et al., 2006; John et al., 1991). In contrast, some personality instruments, such as the OPQ, developed by SHL, do not measure these five traits explicitly. Nevertheless, many of the traits the OPQ measures overlap with these five traits. To illustrate
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extraversion overlaps with at least two OPQ traits: outgoing and affiliative
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neuroticism overlaps with at least two OPQ traits: worrying and low relaxation
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agreeableness overlaps with at least two OPQ traits: trusting
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conscientiousness overlaps with at least two OPQ traits: achieving and conscientiousness
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openness to experience overlaps with at least three OPQ traits: adaptable, variety seeking, and low conventional
As this overlap implies, applicants are more likely to adopt a learning orientation, and thus experience a genuine motivation to develop their capabilities and qualities if they report specific characteristics on the OPQ: high levels of outgoing, affiliative, relaxation, trusting, achieving, conscientiousness, adaptable, and variety seeking as well as low levels of worrying and conventional.
Strategies to predict a learning orientation: Other correlates
Besides personality, selection committees may be able to gauge other qualities to predict the learning orientation of applicants. That is, studies have uncovered many other characteristics or attributes that tend to coincide with a learning orientation. For instance, whether individuals adopt a learning orientation or performance orientation partly depends on whether they perceive competence, character, and morality as modifiable or immutable.
As the work of Dweck has revealed (e.g., Dweck, 2006), some children, when young, receive feedback and encouragement that implies their qualities are modifiable. In response to failures or obstacles, their parents might refer to strategies these children can adopt to improve, such as “If you try this, you’ll get better”. Over time, these children espouse the assumption that, with effort, they can modify their capabilities or qualities. They perceive their characteristics as malleable. Consequently, they become more inclined to pursue opportunities to extend and to improve their capabilities and qualities, manifesting as a learning orientation.
In contrast, other children, when young, receive feedback that implies their qualities are entrenched rather than modifiable. In response to failures or obstacles, their parents might refer to enduring limitations, such as “You’re not good at sports”. Over time, these children espouse the assumption that many of their characteristics are enduring, insensitive to effort or training. Consequently, they are not as inclined to develop their qualities but instead to demonstrate their existing capabilities, manifesting as a performance orientation.
Consistent with this premise, research does show that a growth mindset, in which individuals assume their qualities are modifiable, is indeed associated with a learning orientation (e.g., Farr et al., 1993)
Converssely, individuals who report a performance orientation feel that effort reflects limited ability (Brett & VandeWalle, 1999). Because they feel that effort is futile, their self-efficacy declines, especially when setbacks arise (Stevens & Gist, 1997). This sensitivity to setbacks amplifies resistance to feedback and advice.
Other characteristics may also coincide with a learning orientation. To illustrate
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People who are older that all their other siblings, called first borns, are usually more like to report a learning or mastery orientation. In contrast, people who are the second oldest sibling in their family are usually more likely to report a performance orientation, perhaps because they often compare themselves to first-born individuals (Carette, Anseel, & Van Yperen, 2011).
Strategies to develop a learning orientation
If applicants do not exhibit a learning orientation, selection committees may be reluctant to hire these individuals. Nevertheless, particular circumstances or conditions can foster a learning orientation. Specifically, as research has revealed
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when individuals feel their workload is manageable, they are more likely to adopt a learning orientation (Beck & Schmidt, 2013). In contrast, when individuals feel inundated, they are more concerned about the problems that could unfold soon instead of the benefits of skill development to the future
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when their leaders promulgate and pursue an inspiring vision of the future, called a transformational leadership style, individuals are more likely to adopt a learning orientation (Coad & Berry, 1998). They are more likely to recognize how the development of skills now could benefit their lives in the future
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when students or employees receive instructions that prioritize the importance of learning, understanding, and uncovered novel ideas—over other measures of performance—they are more likely to adopt a learning orientation (cf Wang & Takeuchi, 2007)
Conditions that amplify or diminish the benefits of a learning orientation: Cognitive ability and intelligence
Individuals who adopt a learning orientation are more inclined than individuals who adopt a performance orientation to pursue learning goals—that is, the goal to develop skills and experiment with novel strategies. Yet, as research indicates, the benefits of learning goals, compared to performance goals, are especially pronounced when cognitive ability is limited. In one study, conducted by Seijts and Crim (2009), participants completed a cognitive task, in which they needed to be able to formulate timetables or schedules of classes for each student, attempting to minimize clashes. They were exposed to the materials for 4 minutes, before completing the task over a period of 24 minutes.
In practice, several strategies can be applied to perform this task effectively. Participants, for example, can rearrange the classes and times in chronological order. They can schedule some classes at night, and so forth. Usually, after 24 minutes, participants can perform this task effectively and can apply many effective strategies.
After they were exposed to the materials, some participants were instructed to pursue a learning goal. In particular, they were asked to uncover and to implement at least four distinct strategies (cf., Noel & Latham, 2006). Other participants pursued a performance goal: They were instructed to complete 11 or more schedules. Furthermore, to assess general cognitive ability, they completed the Wonderlic Aptitude Test.
When cognitive ability was limited, participants could schedule more classes correctly if they were governed by a learning, rather than performance, goal. When cognitive ability was high, however, a performance goal was appreciably more effective.
Learning goals tend to be more effective than performance goals when the task is challenging or unfamiliar—and thus novel approaches, skills, and techniques must be developed or refined (cf., Brown & Latham, 2002; Kozlowski & Bell, 2006). Performance goals can disrupt the acquisition of skills and knowledge (Kanfer & Ackerman, 1989; Winters & Latham, 1996). Thus, when cognitive ability was low, learning goals might have enhanced the capacity of individuals to uncover suitable strategies.
In contrast, when cognitive ability was elevated, the participants might have uncovered these strategies rapidly. That is, they can learn tasks effectively. Consequently, the detrimental effects of performance goals might not be as apparent. Instead, the clarity of these goals might have enhanced motivation, without impeding progress.
Conditions that amplify or diminish the benefits of a learning orientation: Uncertainty
As Darnon, Butera, and Harackwiewicz (2007) showed, a learning orientation may facilitate learning, particularly while individuals feel a sense of uncertainty. In this research, participants studied some text. They were granted opportunities to share their interpretations of this text with someone else, over computer. This other person would either agree or disagree with their interpretations. If the other person disagreed with their interpretations, a learning orientation enhanced their capacity to understand this material, as gauged by a subsequent test. If the other person agreed with their interpretations, a learning orientation was not significantly more helpful than a performance orientation.
Presumably, if individuals adopt a learning orientation, they perceive moments in which someone disagrees with their interpretation as opportunities to advance their knowledge. They, therefore, remain engaged in their task and attempt to explore the source of this uncertainty or disagreement. In contrast, if individuals adopt a performance orientation, they perceive these moments of disagreement as obstacles to their goals. Their confidence declines, their engagement in the task diminishes, and their learning deteriorates.
Conditions that amplify or diminish the benefits of a learning orientation: Workplace environment
Because they embrace change and variety, individuals with a learning orientation are more likely than individuals with a performance orientation to flourish in dynamic, innovative environments. That is, some cultures are characterized by innovation, change, and flux. Creative products, procedures, and programs are introduced frequently. These environments offer the variety and challenges that are needed to facilitate growth, fulfilling the needs, and thus enhancing the motivation, of individuals with a learning orientation. These environments, however, obstruct the attempts of individuals to exceed some target or standard, compromising the needs, motivation, and ultimately performance of people with a performance orientation.
Potosky and Ramakrishna (2006) uncovered some findings that confirm these assumptions. The learning orientation of individuals was assessed. Evaluations of their job performance were also collated. Finally, the degree to which the culture embraces change and innovation was assessed. Learning orientation was positively associated with performance but only if the culture was sufficiently innovative and dynamic.
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Conflict monitoring theory in education
Introduction
Often, students and staff need to complete a sequence of activities. Students, for example, might need to watch a chemistry lecture and then complete a mathematics test. Staff might need to teach a business class and then analyze some data. According to conflict monitoring theory, the order in which individuals complete sequences of tasks—and the range of tasks that individuals complete in one day—can significantly affect performance and learning. Thus, conflict monitoring theory may inform a range of decisions, such as
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how classes should be scheduled across the day
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which activities should students complete between classes to enhance their concentration
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how students should distribute their studies across the day, and so forth
In particular, conflict monitoring theory implies that
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whenever tasks demand appreciable concentration, staff and students should attempt to schedule similar tasks on the same day and different tasks on separate days
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if staff and students need to complete different, but demanding tasks, on the same day, these individuals should also complete an enjoyable or rewarding activity. They should insert this enjoyable activity between the two demanding tasks
History of conflict monitoring theory: Executive control
Conflict monitoring theory originally emanated from the notion of executive control—that capacity of individuals to pursue and to achieve a significant goal despite other temptations. Researchers in this field recognized an important paradox. Specifically, to achieve challenging but important goals, individuals need to direct their efforts almost exclusively on this pursuit. Yet, when individuals direct their efforts almost exclusively towards one goal, several problems unfold. Specifically, if individuals devote effort to one goal and suppress competing inclinations, they may inadvertently inhibit an action or response that might be beneficial at this time. Researchers, therefore, wanted to explore how people know when to direct effort to these tasks and when to withdraw this effort when needed.
Botvinick et al. (2001) proposed the conflict monitoring theory to explain how individuals resolve this paradox. According to this model, a circuit in the brain, at least partly residing in the anterior cingulate cortex, attempts to monitor the degree to which individuals are experiencing conflicts between response tendencies. For example,
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if their surroundings elicit the inclination both to raise and to lower their right hand, they will experience significant conflict
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if the surroundings elicit the inclination to raise their right hand, but lower their left hand, this conflict is not as pronounced.
If individuals experience a pronounced conflict, this circuit will significantly prime or incite the responses that are compatible with the goal that is dominating their awareness. To illustrate, when the dominant goal of individuals is to study, but the level of conflict is pronounced, this circuit will appreciably prime actions that facilitate study, such as reading a book or transcribing notes, experienced as effort. In contrast, if individuals experience only a modest conflict, this circuit will not prime these actions to the same extent, experienced as the withdrawal of effort.
Researchers have proposed many variants of this theory (e.g., Chuderski & Smolen 2016). For example, the degree to which this circuit primes specific responses may not depend on the level of conflict but other circumstances. Specifically, this circuit might prime specific responses, manifesting as effort, especially when
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the outcomes of some action diverged from expectations (Alexander & Brown 2011),
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the outcomes of some action could generate significant adversity and hence the behaviors are risky (Brown & Braver 2007), and so forth
History of conflict monitoring theory: Ego depletion
Conflict monitoring theory then surfaced in another literature: the literature that explores how mental energy persists across the day. Specifically, conflict monitoring theory was conceptualized as a rival to renowned theory: the theory of ego depletion (Baumeister et al., 1994), sometimes called the strength model of self-control. According to this theory
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individuals can access a limited supply of mental effort— sometimes called self-regulatory resources
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to complete tasks that diverge from their natural inclinations or habits and thus demand mental effort, individuals need to utilize these resources
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these tasks thus deplete this reservoir of resources
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various experiences or events, such as sleep, can replenish these resources
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after individuals complete tasks that demand mental effort and thus deplete these resources , their capacity to override their natural inclinations or habits subsides—until they can replenish these resources
Many studies have confirmed these principles, at least in particular settings. Most of these studies conform to the same design. In particular,
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participants first complete a task that either overrides natural inclinations, demanding significant mental effort, or does not override natural inclinations. For example, they might need to trace a figure with their non-preferred hand and can only watch their hand in a mirror or their preferred hand and can watch this hand directly (Quinn et al., 1996; for other techniques, see DeWall et al., 2007; Fischer et al., 2008; Muraven et al., 2006)
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next, participants complete a second task that purportedly overrides their natural inclinations and thus demands mental effort. They might, for example, need to suppress their emotions while they watch a distressing movie
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the most common finding is that, after individuals complete a task in which they need to override their natural inclinations, the performance on a subsequent task that also demands effort declines.
After their mental effort is depleted, the performance of individuals on a range of tasks diminishes. To illustrate, after individuals complete a task in which they need to override their natural inclinations
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they are not as likely to assist a stranger (e.g., DeWall et al., 2007, 2008)
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they are more inclined to cheat on tasks (e.g., Mead et al., 2009)
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their performance on tasks that demand logical reasoning, but not memorizing, deteriorates (Schmeichel et al., 2003)
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the capacity to complete tasks while feeling anxious declines (Bertrams et al., 2013)
These findings imply these tasks demand mental effort. Indeed, Baumeister (2002) classified the tasks that are dependent on mental effort into three clusters: tasks that demand executive functioning, social interactions in which individuals need to accommodate other people, and personal introspection.
Researchers have shown that several experiences or practices, such as sleep or rest, might restore mental effort and thus enhance the capacity of individuals to override natural inclinations over a prolonged duration. These experiences or practices diminish the extent to which one demanding task will disrupt performance on a subsequent demanding task and include
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feelings of optimism (In Den Bosch-Meevissen, Peters, & Alberts, 2014)
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positive emotions (Tice et al., 2007)
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glucose in the mouth, potentially stimulating dopaminergic pathways (Molden et al., 2012).
Conflict monitoring theory versus ego depletion
Conflict monitoring theory (Dewitte, Bruyneel, & Geyskens, 2009; Robinson, Schmeichel, & Inzlicht, 2010) is an alternative explanation of these findings. According to conflict monitoring theory, the first task that individuals complete might elicit tendencies that undermine performance on the second task.
To illustrate, in the first task, participants might learn they should refrain from a response when a green word appears. In the second task, they might learn to press a bar when a noun appears in any color. If, during the second task, a noun appears in green, they experience the conflicting tendency to refrain from a response, learnt during the previous task, as well as to press the bar. To resolve this conflict, they need to register the conflict, underpinned by the anterior cingulate cortex, and then inhibit the incorrect response, underpinned by the prefrontal cortex. This process demands time and can, therefore, impair performance.
Conflict monitoring theory versus ego depletion: Effect of positive emotions
Ego depletion and conflict monitoring theory differ in how they explain a key finding: the finding that positive emotions often diminish the extent to which performance of one challenging task may impair performance on a subsequent challenging task. To illustrate, in one study, conducted by Tice et al. (2007), participants were instructed to inhibit a specific impulse or thought during a period of 5 minutes. Specifically, they were told to abstain from any thoughts about a white bear—a task that depletes resources.
Participants were then granted a short break. Some participants watched a comedic movie clip during the break. Other participants either sat quietly or watched a sad movie clip.
Before abstaining from thought about a white bear, as well as after the break, participants were instructed to squeeze a handgrip. If participants had watched no movie clip or a sad movie clip during the break, their capacity to maintain this grip deteriorated after suppressing thoughts about the white bear. In contrast, if participants had watched a comedic movie during the break, this capacity remained intact. According to ego depletion theory, these findings imply that positive affect might replenish these depleted resources (Tice et al., 2007).
However, as Wenzel, Conner, and Kubiak (2013) argued, conflict monitoring theory may also explain this pattern of findings. This argument can be traced to the work of Dreisbach and Goschke (2004). According to Dreisbach and Goschke (2004), and consistent with conflict monitoring theory, sometimes individuals need to devote their effort and attention to one goal or pursuit and disregard other alternatives, called stability. In other circumstances, individuals need to shift their effort and attention from one pursuit to another pursuit, called flexibility. Positive emotions imply the original pursuit has been fulfilled and, therefore, tends to promote flexibility—or shifts to another goal.
Consequently, when individuals experience positive emotions, they can readily shift their effort and attention from the first task to the second task. A demanding first task, therefore, is not as likely to disrupt performance on a demanding second task.
To assess whether ego depletion or conflict monitoring theory better explains the effects of positive emotions on the performance of sequential tasks, Wenzel, Conner, and Kubiak (2013) designed an interesting study. All participants completed one demanding task, watched a movie, and then completed a second demanding task.
Specifically, half the participants first completed the Stroop test in which a series of words, each representing one color appear in a different color. For example, the word blue might appear in a red font. Participants need to specify the font of each color—a demanding task. Next, participants watched a short comedic movie, to evoke positive emotions, or an unemotional movie, to evoke neutral emotions. Finally, these participants completed the Stroop task again. In contrast, other participants first completed another demanding task: in which they needed to refrain from consuming sweats. Otherwise, they completed the same tasks as the other participants.
According to the notion of ego depletion, the positive emotions should enhance performance on the second task, regardless of whether they completed the Stroop task or refrained from the sweets first. That is, the positive emotions should restore the mental resources the first task consumed. In contrast, according to the conflict monitoring theory, the positive emotions should enhance performance on the second task but only when the first task was to refrain from the sweets. That is, positive emotions should enable individuals to switch tasks—and this switch is unnecessary if both demanding tasks are the same. The pattern of results corroborated the conflict monitoring theory: Positive emotions improved performance on the second task only if participants needed to switch activities.
Primoceri, Ramer, Ullrich, and Job (2021) also revealed how the similarity between the two demanding tasks affects performance. In some conditions, the two demanding tasks were different: For example, participants might have first attempted unsolvable anagrams and then completed a Stroop task. In these instances, consistent with both ego depletion and the conflict monitoring theory, one demanding task compromised performance on a subsequent, but different, demanding task.
In other conditions, the two demanding tasks were similar or the same. In these instances, consistent with conflict monitoring theory but in contrast to ego depletion, one demanding task was not as likely to compromise performance on a subsequent, but similar, demanding task. In these conditions, participants did not need to shift their goals or intentions. Therefore, the two tasks do not conflict with each other.
These findings do not necessarily discount ego depletion altogether. Perhaps, two demanding activities that are similar might consume less mental effort, because participants do not need to switch their goals or mindsets. Conversely, two demanding activities that are different might consume more mental effort, because the switch is demanding. Regardless, the findings do suggest that a switch between two distinct activities, and not only the activities themselves, compromise performance.
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Introduction
Scholars, consultants, and practitioners have developed an endless array of programs and initiatives to facilitate the development of leaders. Nevertheless, approaches that are effective and prevalent in many other industries might not be helpful in tertiary education. That is, leaders in tertiary education, especially academic heads of university departments, often experience a raft of distinct challenges.
To illustrate, as Bryman and Lilley (2009) observed, after these authors completed an analysis of interviews with tertiary education leaders, academics often perceive themselves as detached from the institution. They tend to be more loyal to their field of research than to their department or institution. They often chose a research career because of a predilection towards autonomy and independence. Consequently, academics, in general, are not especially amenable to actions that are implemented to manage or to limit their behavior.
Besides this impediment in their capacity to manage and to influence academic staff, leaders in tertiary education may experience other distinct challenges. To illustrate, heads or directors of academic units, such as departments, often experience conflicting demands. For example
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if they do not pursue their research, their credibility in the field might subside; but if they do pursue their research, they might be perceived as unsupportive of their department
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the requests they receive from executives often conflict with the requests they receive from staff
These challenges and conflicts may be especially pronounced in female leaders. To illustrate, as Blackmore and Sachs (2000) revealed, after they interviewed 50 female leaders at Australian universities
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because of the neoliberal agenda, many of the values these leaders cherished—such as teaching and service—were superseded by an increasing obsession with research income and ranking
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university rhetoric often underscored the importance of equality and diversity; yet, more established universities actually valued privilege, tradition, and thus male dominance, despite this rhetoric.
Content of leadership development programs in tertiary education: Overview of effective behaviors
To facilitate the design of leadership development programs, some researchers have attempted to identify the leadership behaviors that characterize effective leadership in tertiary education. For example, after a comprehensive review of the literature, Bryman (2007) unearthed 13 leadership behaviors that are assumed to exemplify or demonstrate exemplary leadership. Specifically, these leaders
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promulgate a clear and inspiring vision or sense of direction, sometimes called visionary
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initiate changes and arrangements that enable the institution or department to pursue this vision—sometimes called initiating structure
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develop mutually respectful and warm relationships that accommodate the needs of other individuals, sometimes called individualized consideration
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treat other individuals with fairness, impartiality, and integrity, regardless of personal interests
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fulfill their promises and communicate transparently, representing trustworthiness
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grant all staff opportunities to contribute towards decisions—and show a willingness to genuinely debate these choices
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communicate frequently and candidly about the plans, changes, and progress in an institution or department
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act as role models, epitomizing the behaviors they advocate, called idealized influence
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foster a collegial, collaborative, and supportive atmosphere, encouraging staff to communicate honestly and encouragingly
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advocate effectively on behalf of staff, promoting the achievements and seeking the necessary support and resources
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deliver regular and constructive feedback to staff
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manage workloads effectively, to enable academic staff to pursue their research and scholarship
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appoint suitable, productive staff
Bryman (2007), however, recognized that few leaders will manage to demonstrate all these exemplary behaviors. In particular, some behaviors might impede their capacity to demonstrate other behaviors. For example, to act as a role model, leaders might need to maintain an exemplary track record of research. Yet, this pursuit of research might limit the time that is available to initiate all the other behaviors.
Rather than depend on a literature review, Hamlin and Patel (2017) undertook a critical incident analysis to uncover effective and ineffective leadership behaviors. Specifically, the researchers interviewed 37 staff in higher education, living in France, 16 of whom were leaders and managers. Participants were prompted to describe critical incidents they had observed in which managers or leaders demonstrated helpful or unhelpful behaviors. The responses were subjected to open coding and then axial coding to identify 17 clusters of effective leadership behaviors and 21 clusters of ineffective leadership behaviors.
Many of the 17 effective leadership behaviors overlapped with the inventory that Bryman (2007) had proposed. However, Hamlin and Patel (2017) did uncover some effective leadership behaviors that Bryman (2007) had not revealed. These disparities might reflect differences in the nations and methods across studies. According to Hamlin and Patel (2017), effective leaders also
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recognize and reward staff who contribute effectively and work assiduously
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are attuned to the personal challenges of staff and supports their staff in these circumstances
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grant staff autonomy on how to fulfill goals or solve problems
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empower staff to assume leadership roles, such as chair meetings, propose recommendations, or reach decisions
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inspire staff to seek opportunities that could facilitate their learning and development
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chair meetings effectively; they prepare helpful agendas, allot a reasonable duration to each item, and generates decisions or actions
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clarify the roles and responsibilities of staff
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resolve the problems that staff experience, such as conflict with colleagues, as soon as possible
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monitor the performance and progress of staff effectively, with reference to suitable reports, evaluations, and feedback
Similarly, Hamlin and Patel (2017) unearthed some ineffective leadership practices—practices that are not merely the converse of the effective leadership practices. For instance, ineffective leaders often
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favor some members of staff unfairly, exhibiting discrimination or prejudice
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speak deceitfully or uncivilly, such as shouts at staff
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defer important decisions or shifts their decisions erratically
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disregard the novel or unconventional suggestions of staff—or disregards the decisions of staff
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overlook the resource implications of their decisions
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communicate information hurriedly or unclearly, at inappropriate times and places
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impose unreasonable demands on staff, augmenting their workload substantially
Content of leadership development programs in tertiary education: Key topics
Leadership development programs in tertiary education institutions cannot inculcate all the effective behaviors that studies indicate are effective. Instead, within the timeframes that are usually available, the programs must be confined to some key themes. Some of the most important topics, according to researchers who have conducted a needs analysis in this field, include some insights on
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how to promote changes in culture and practices as well as manage the performance of academic staff (Deem et al., 2007)
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communication during crises, such as funding cuts, including how to balance the need to communicate regularly but to choose courses of action decisively (Haddon et al., 2015)
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financial management, risk management and entrepreneurship (Deem et al., 2007)
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how to balance and integrate the diverse, and often conflicting roles of academic leaders (Rowley & Sherman, 2003; McGivern et al., 2015)—such as academic pursuits and management responsibilities or tensions between collaboration and competition (Akbulut et al., 2015)
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how to prioritize the various responsibilities of academic leaders (Vilkinas & Ladyshewsky, 2012; Wolverton et al., 2005)
Content of leadership development programs in tertiary education: The Bass taxonomy
To inform these topics, the specialists who design leadership programs often invoke leadership theories and frameworks that have been developed outside the education sector—primarily because researchers have not developed leadership theory or frameworks that are specific to tertiary education. Indeed, according to Dopson et al. (2019), to develop a leadership development program, specialists should ask four questions:
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what are the strategic goals and aspirations the institution wants to achieve
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what are the models or theories of leadership that could enable the institution to achieve these goals and aspirations
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what leadership development programs—and potentially other interventions—can enable the institutions to inculcate or apply these models and theories
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how can institution evaluate whether these programs facilitate the achievement of the strategic goals and aspirations
Accordingly, these specialists should be cognizant of the range and validity of leadership theories that scholars have proposed. To facilitate this pursuit, researchers have attempted to reduce this vast array of leadership theory or frameworks into a few main approaches (see Antonakis & Day, 2017; Bass, 1990; Northouse, 2016).
To illustrate, Bass (1990) proposed that most leadership theories, framework, and models can be divided into five constellations. The first constellation of theories, called the trait approach, tended to ascribe leadership to outstanding or helpful personality traits. These theories assumed that leadership was predicated on greatness—on qualities that were either inherited or developed over an extended time. The research in this field attempted to characterize the traits or tendencies that epitomize great leaders, such as intelligence, confidence, determination, integrity, and charm.
During the 1950s, however, researchers challenged the assumption that leadership can be ascribed to enduring traits and instead directed attention the specific behaviors and practices that differentiate effective leaders from ineffective leaders. Many researchers attempted to enumerate the behaviors that effective leaders exhibit (e.g., Lawrence et al., 2009; Stogdill, 1963). For example, exemplary leaders tolerate uncertainty, inspire productivity, encourage collaboration, resolve conflicts, grant autonomy, and devolve responsibility when appropriate.
Subsequently, researchers attempted to divide these behaviors into clusters (e.g., Lawrence et al., 2009). For example, scholars recognized that effective leaders tend to direct or coordinate the activities of other individuals, called initiating structure, but offer support and encouragement to help individuals complete these activities and overcome challenges, called consideration (e.g., Judge, Piccolo, & Ilies, 2004). Because of this emphasis on behaviors, leadership programs, designed to enhance the leadership skills of many staff, burgeoned.
Over time, scholars began to question whether these leadership practices are indeed useful in all circumstances. This pursuit engendered a range of arguments, epitomized by leadership contingency theory (Fiedler, 1971), the path-goal theory (House & Mitchell, 1997), and substitutes for leadership (Kerr & Jermier, 1978). These theories, in general, attempted to characterize the circumstances in which leadership should not be as directive, but instead grant staff more discretion over the goals they pursue and the methods they apply. According to the situational-leadership model, for example, leaders should impose progressively less direction as staff mature and assume responsibility (Hersey & Blanchard, 1977).
Thompson and Vecchio (2009) distinguished three main variants of this situational-leadership model. According to the first variant, before employees have matured in their role, supervisors should be very prescriptive. As employees mature, supervisors should attempt to be more persuasive rather than prescriptive. Eventually, quite mature employees should be encouraged to participate in decisions. Finally, supervisors should delegate important tasks to very mature employees. In this variant, maturity is primarily defined by a combination of commitment and competence.
The second main variant of situational leadership theory distinguishes commitment and competence. According to this variant, supervisors of employees who are committed but not competent, called the enthusiastic beginner, should be more directive. In contrast, employees who are not especially committed or competent, but feel disillusioned, may benefit from coaching. Third, employees with reasonable competence, but varying commitment, may benefit from supportive leaders. Finally, supervisors should delegate tasks to employees who exhibit both competence and commitment.
The third main variant of situational leadership theory, in essence, assumes that maturity primarily depends on experience. The main premise is merely that experienced individuals should be granted more autonomy.
Past research has uncovered some, but limited, evidence of these variants of situational leadership. The first variant seems to be valid, but almost only in recent recruits (for a review, see Thompson & Vecchio, 2009). The second variant has not been tested as extensively and initial tests have not been encouraging (Thompson & Vecchio, 2009). Furthermore, this variant does not describe how supervisors should behave for every combination of competence and commitment. The final variant has received tentative support. As Thompson and Vecchio (2009) showed, for example, autonomy is more likely to be effective, as gauged by the relationship between supervisors and subordinates, in experienced rather than inexperienced employees.
These contingency theories, however, did not clarify how leaders should direct or influence their staff. This shortfall inspired the power-influence approach (Bass, 1990). This approach explored the tactics and strategies that leaders invoke to sustain power and to influence other people
Finally, this emphasis on influence evolved into the transformation approach. This approach underscored how the role of leaders is to promote an inspiring vision of the future and then enable people to transform the culture and practices of the organization.
According to Bass and Avolio (1990, 1994, 1997), transformational leaders tend to initiate four main behaviors. First, these leaders invite followers to challenge conventional practices and reflect upon issues from a novel perspective, called intellectual stimulation. Second, rather than follow these traditional customs and conventions, transformational leaders promulgate an inspiring, challenging, and shared vision of the future, called inspirational motivation. Third, to enable followers to adopt and embrace this vision, these leaders strive to understand and accommodate the unique preferences, concerns, perspective, motives, and qualities of each individual, offering coaching and support, called individualized consideration. Finally, these leaders demonstrate the vision and values they convey and they show respect towards followers, called idealized influence (attributes), and maintain exemplary conduct, called idealized influence (behavior). The notion of inspirational motivation and idealized influence were borrowed from a previous leadership theory, called charismatic leadership (Conger & Kanungo, 1998)
Content of leadership development programs in tertiary education: The Antonakis and Day (2017) taxonomy
In their attempt to outline the main theoretical contributions to leadership, Antonakis and Day (2017) also recounted the history of trait theories, behavioral theories, the contingency or situational theories, and the transformational theories. Antonakis and Day (2017) then outlined some of other key schools or approaches that have significantly permeated and shaped the literature on leadership.
The first approach is sometimes called the relational school and revolves around the notion of leader-member exchange theory (Gerstner & Day, 1997). In contrast to the transformational approaches, in which leaders are perceived as charismatic vehicles of change, this approach underscores the significance of individual relationships between each staff member and the leader. As research on this theory has revealed, leaders need to develop trusting, respectful, and reciprocal relationships with their followers. These relationships, called leader-member exchange, tend to improve the satisfaction, dedication, performance, and wellbeing of staff (Gerstner & Day, 1997).
Presumably, leaders who are empathic—and can appreciate the feelings and perspectives of other people—are more likely to develop these trusting relationships, sometimes called empathic leadership. To illustrate, in one study, conducted by Cornelis et al. (2013), participants believed they had been assigned to a group of six people, who would interact over computer. They were assigned the role of team leader, supposedly because of their scores on a questionnaire. To evoke an empathic leadership style, they were told that successful leaders empathize with their subordinates. They were also encouraged to consider how the other people experience the task. In the control group, participants were told that successful leaders are rational and focus objectively on tasks and goals. They were told to maintain a rational and detached perspective.
In this study, the participants then learnt information about one of their supposed team members. This team member indicated that he or she either needs or does not need to be accepted by other people, indicating high or low need to belong respectively. Finally, participants indicated the degree to which they would like to know the perspectives of their team members, called voice.
If leaders were empathic, they wanted to know the perspectives of their team members, especially if they recognized the team members show a need to belong. Accordingly, empathic leaders are sensitive to the needs of followers. Followers who experience a need to belong are especially sensitive to procedural justice. That is, they perceive justice as a sign of respect and acceptance. Empathic leaders, aware of this sensitivity, will thus offer more voice to people who need to belong.
The notion that leaders may not always transform organizations is augmented in the skeptics-of-leadership school. In particular, the skeptics-of-leadership school presupposes the role of leadership may have been overstated and is primarily a construction that people utilize to explain productive and unproductive performance (e.g., Lord, Binning, Rush, & Thomas, 1978). Indeed, some variants of this theory assume that perhaps leadership does not appreciably shape the performance of individuals, teams, or organizations (Meindl & Ehrlich, 1987).
Although this school has waned in recent decades, some of the assumptions that underpin this skepticism have permeated other theories. To illustrate, as this skepticism implied, leadership behavior is partly a construction of followers: Whether a leader is effective is primarily a function of the cognitions and thoughts of followers and is not an inherent attribute of this leader. Specifically, the information-processing perspective, as defined by Antonakis and Day (2017), examines the thoughts and beliefs of staff that explain why some managers are perceived as legitimate leaders. According to some variants of this perspective, individuals develop expectations of a prototypical leader. Managers who match this prototype tend to be perceived as a legitimate or effective leader (e.g., Lord, Foti, & De Vader, 1984; Lord & Maher, 1991)
The biological and evolutionary school, as delineated by Antonakis and Day (2017), explored how these leadership traits, behaviors, or prototypes may have evolved. That is, this school examines the evolutionary benefits of these qualities to consider why these characteristics might have evolved (see Antonakis & Dalgas, 2009)
Content of leadership development programs in tertiary education: The Northouse (2016) taxonomy
Northouse (2016) also outlined some more specific leadership theories that have surfaced in the last few decades. First, the notion of authentic leadership partly emanated from concerns about transformational leadership. One concern was that perhaps transformational leadership, such as an inspiring vision, might not always reflect communal values. Instead, the motivation to maintain power or to attract rewards and recognition might sometimes motivate the behaviors of transformational leaders. In contrast, authentic leaders pursue meaningful, moral values—pursuits that overlap with the intrinsic needs of staff.
According to recent conceptualizations of this style, authentic leaders exhibit four main clusters of behavior: balanced processing, internalized moral perspective, relational transparency, and self-awareness (e.g., Avolio & Gardner, 2005; Gardner et al., 2005; Walumbwa et al., 2008, 2010). Balanced processing refers to the capacity of some leaders to integrate all information, rather than merely sources that confirm their preferences or assumptions, to reach a decision. Internalized moral perspective relates to the extent to which the personal values of leaders—instead of other pressures or tangible rewards—govern the choices and behaviors of these individuals. Relational transparency concerns the tendency of leaders to disclose and share information, thoughts, and feelings candidly. Finally, self-awareness reflects the degree to which leaders rate their strengths, limitations, motives, and reputation accurately.
Walumbwa, Wang, et al. (2010) confirmed that authentic leadership enhances work attitudes and performance in followers. Specifically, when leaders were authentic, followers reported elevated levels of engagement. They also tended to show more organizational citizenship behavior, including activities like helping colleagues, behaving courteously, and accepting unpleasant changes. The extent to which employees experienced a sense of identity with the supervisor as well as feelings of empowerment, representing a feeling of choice, meaning, competence, and impact, mediated these associations.
Second, rather than inspire their staff, some leaders primarily strive to cultivate the conditions that support their staff, called servant leadership. As several researchers argue (e.g., Graham, 1991; Greenleaf, 1977, 1996; Hale & Fields, 2007; Walumbwa et al., 2010), moral considerations tend to govern the decisions of these servant leaders. Because of this moral stance, these leaders attempt to satisfy the needs of all stakeholders, including customers and suppliers. In pursuit of this goal, servant leaders strive to facilitate the growth and well-being of employees as an end in itself—and not merely to pursue some grand vision of the future, like charismatic, transformational leaders. Finally, these leaders attempt to maintain humility and overcome hubris, by reflecting upon their limitations.
Walumbwa, Hartnell, and Oke (2010) conducted a study to explore the reasons that servant leadership tends to enhance the performance of organizations. Employees rated the extent to which their supervisor demonstrated servant leadership. Three weeks later, they also evaluated the degree to which the procedures were just, represented by items like "To what extent are procedures in your workgroup based on accurate information", and the degree to which a service climate prevails, corresponding to items like "How would you rate the recognition and rewards employees receive for the delivery of superior work and service". Furthermore, they evaluated their own self-efficacy and commitment to their supervisor. Finally, two weeks later, supervisors rated the extent to which these employees enacted citizenship behaviors, such as helping colleagues.
Some leaders not only serve their followers but even sacrifice their personal needs to benefit their organization, called self-sacrificial leadership. These leaders experience a profound sense of duty to fulfill workgroup goals, even willing to engage in risky behavior to achieve this objective (De Cremer, van Knippenberg, van Dijke, & Bos, 2006). De Cremer, Mayer, van Dijke, Schouten, and Bardes (2009) developed a measure of sacrificial leadership that comprises four items: "goes beyond self-interest for the good of the group," "considers the moral and ethical consequences of decisions," "emphasizes the importance of having a collective sense of mission," and "specifies the importance of having a strong sense of purpose". These leaders tend to boost the self-esteem of followers, especially in staff who feel a strong connection to the team: Presumably, when leaders sacrifice their personal interests to benefit the team, members feel their work must be important and valuable.
Other leaders not only pursue these ethical or moral values but instill these ethical beliefs in followers and reinforce ethical behavior (Brown & Trevino, 2006). They underscore the significance of ethics and values, even offering incentives to shape the ethical conduct of individuals. Brown, Trevino, and Harrison (2005) developed a measure to assess ethical leadership, with items such as "...disciplines employees who break ethics rules".
Procedural justice, a service climate, self-efficacy, and commitment to the supervisor partly mediated the association between servant leadership and organizational citizenship behavior (Walumbwa, Hartnell, & Oke, 2010). In addition, the positive association between procedural justice and organizational citizenship behavior, as well as the positive association between a service climate and organizational citizenship behavior, was more pronounced when employees were committed to the supervisor. This commitment, presumably, increases the extent to which the culture of organizations governed the behavior of employees.
Third, in contrast to servant leadership, the psychodynamic approach to leadership explores the origins of irrational behaviors and beliefs in both leaders and followers. This approach explores the rich and paradoxical motivations and urges that shape the decisions and interactions of leaders and followers in organizations. Without these insights, many of the causes of unproductive patterns of behavior are overlooked (for a review, see Northouse, 2016).
Finally, rather than explore the effects of individual leaders, many researchers have explored the impact of shared leadership—leadership that is distributed across teams. That is, teams perform more effectively, fulfilling their goals and targets, when most or all the individuals demonstrate leadership behaviors (Carson, Tesluk, & Marrone, 2007). To illustrate, Solansky (2008) showed that shared leadership confers a sense of team efficacy—a sense the team has developed the necessary skills to be competent and effective. In addition, shared leadership was also positively related to transactive memory or the extent to which members recognize the talents, skills, and knowledge of each other (Solansky, 2008). Carson et al (2007), however, argue that shared leadership is more likely to be beneficial when the culture is egalitarian, rather than hierarchical, when the tasks are complicated rather than routine, and when the roles in the team are interdependent.
Designs of leadership development programs in tertiary education: An overview
Rather than delineate the content of leadership development programs in tertiary education, other studies have explored the features of these programs that could benefit participants (e.g., Scott et al., 2010; Tolar, 2012; Turnbull & Edwards, 2005). Collectively, these studies indicate that
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leadership development programs should be tailored to the distinct needs of each academic leader—or at least customized to their management level—and delivered just before these skills are relevant (Scott et al., 2010);
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leaders should be granted opportunities to discuss the matters they need to manage with their experienced and successful academic counterparts (Scott et al., 2010)
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leaders should be able to access case studies on how past individuals in their role managed challenging circumstances (Scott et al., 2010)
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leaders should be granted the time to develop rather than feel inundated with trivial and menial demands (Scott et al., 2010)
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the most senior leaders of the organization should be inspired to practice transformational leadership—in which they promulgate an inspiring, moral vision, pursue this vision with determination and integrity, encourage innovative suggestions on how to pursue this vision, and coach individuals on how to achieve these goals, customizing their advice to accommodate the needs of each person; this leadership style grants other staff opportunities to lead effectively (Turnbull & Edwards, 2005)
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the program should grant leaders many opportunities to apply and to practice their skills (Turnbull & Edwards, 2005)
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the institution must encourage a subset of staff to assume ownership over this leadership program (Turnbull & Edwards, 2005)
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to sustain these changes, the institution must identify how to inculcate the lessons of this program into the fabric of this organization; role modeling, networking, succession planning, and delegation are crucial to this endeavor (Hargreaves & Fink, 2006). Leadership development should not be conceptualized as an attempt to transform individual leaders, but to develop and support a distributed network of staff.
These recommendations were derived from interviews and focus groups with participants of leadership programs. Consequently, whether all these features actually enhance the efficacy of leadership development programs in tertiary education warrants further research.
Consequences of leadership development programs in tertiary education
Despite the extensive literature on leadership development programs in tertiary education, Dopson et al. (2019) bemoaned the scarcity of studies that have explored the consequences of these programs over time. Only a few studies have shown some lasting benefits of these programs, but the designs of these studies tend to preclude definitive conclusions.
To illustrate, Chibucos and Green (1989) conducted a longitudinal evaluation of one leadership program—the American Council on Education Fellows, designed to enhance the leadership capabilities of aspiring university and college leaders. The study showed that 56% of these participants were later appointed to positions of Dean or higher—sometimes even university president. Yet, because these participants may have been a selective elite, whether they would have achieved this success without this program remains contentious.
Subsequently, McDaniel (2002) showed the same program did enhance the leadership competencies of participants, such as their understand of academic administration and their capacity to communicate effectively. However, participants evaluated their own behavior before and after this program. Whether these perceived changes translated to observed improvements in their behavior was not determined.
Similarly, Ladyshewsky and Flavell (2011) showed that one leadership program, implemented at an Australian university, did improve the confidence and empowerment of these program coordinates. This improvement was sustained at least 12 months. However, this finding was not derived from an objective measure but from interviews of over 10 participants.
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Introduction
Institutions have introduced an array of programs to support early career academics, particular early career researchers. Fewer institutions, however, implement programs to support midcareer academics. Yet, midcareer academics often fulfill many vital roles and experience many distinct challenges. They assume many of the leadership roles at tertiary education institutions (Baker & Manning, 2020)—because early career academics have not developed the requisite experience and experienced academics often confine their attention to their research agendas. But, unlike these other academics, the pathways or aspirations of midcareer academics is often uncertain and ambiguous. Accordingly, midcareer academics are especially inclined to feel dissatisfied with their role, uncertain of their direction, and trapped in their existing position (e.g., Petter et al. 2018).
Admittedly, the experience of midcareer academics depends on how this cohort is defined. Scholars recognize the midcareer academics cannot be readily demarcated (Baldwin & Chang, 2006). Even in America, in which the distinction between contingent staff and tenure academics is distinct, whether midcareer academics correspond to one or both of these divisions remains contentious (for a review, see Baker & Manning, 2020)
This cohort of midcareer academics are not homogenous either. For example, as Baldwin et al. (2005) revealed, midcareer academics in their forties experience distinct challenges and needs than midcareer academics in their fifties.
Even individual midcareer academics may experience an array of conflicting attitudes about academic life. To illustrate, in a series of interviews, Karpiak (1997) explored the fulfilling and challenging experiences of mid-career academics, aged 41 to 59, employed in the Faculty of Arts, as well as the practices of institutions that affect these experiences. Many academics perceived some of their academic roles and responsibility, especially around teaching, as meaningful, interesting, and central to their identities. Yet, other mid-career academics, or sometimes the same midcareer academics, also expressed feeling of malaise—a feeling their work had stagnated and their interest or commitment had declined, partly because of the excessive hours that teaching and administration consumed. Some participants also felt the institution had marginalized the needs and significance of midcareer academics, contrary the motivation of these individuals to feel important and beneficial to the university.
The challenges that midcareer academics experience: Burgeoning responsibilities.
To support the work and development of midcareer academics, institutions need to appreciate the distinct profile of challenges these academics often endure. One of these challenges revolves around their unrecognized workload.
Of course, most academics work extensive hours, often culminating in stress and burnout. For example, early career academics often teach many classes, grade many assignments, and launch their research careers. Yet, many of these activities can be planned carefully, diminishing the likelihood that workloads will escalate inexorably. That is, early career academics tend to be able to regulate their workload to some extent, diminishing stress.
Senior academics, towards the zenith of their careers, may also be inundated with managerial responsibilities, sometimes managing enormous research programs, for example. Yet, these roles are often rewarding. These academics may publish extensively, attract research income, and feel important to their institution.
In contrast, as Baldwin (1981) recognized decades ago, midcareer academics may not be afforded these luxuries. Unlike early career academics, midcareer academics not only continue to teach classes and to conduct research, at least sporadically, but also must often fulfill other responsibilities, such as the need to update curriculum and serve on committees (Baldwin, 1981). These other responsibilities are not confined to specific times or work hours—and may swell uncontrollably.
This burgeoning workload is especially frustrating to midcareer researchers because, in many instances, these individuals feel they have finally earned the right and autonomy to explore the matters they cherish and value. Lamber et al. (1993), in a qualitative study of 33 midcareer researchers, from a variety of disciplines, uncovered this tension between autonomy and workload.
After academics have progressed, perhaps attracting tenure for example, these individuals finally experience a sense of autonomy. They feel empowered to explore other research and leadership pursuits. They feel they forge their own pathway, diverging from past supervisors, mentors, and advocates. Yet, at the same time, these midcareer academics discover they cannot arrange the time they need to pursue these pathways. They often feel inundated with their existing responsibilities. And these other responsibilities, such as curriculum development, although often encouraged by leaders, are not rewarded in practice.
Furthermore, unlike their more senior counterparts, midcareer academics often cannot dedicate enough time to their teaching and research to progress significantly in these activities either. Their efforts do not feel as rewarded, a key determinant of burnout.
To illustrate, Karpiak (1996) showed how institutions do not seem to reward the activities of midcareer academics sufficiently. Specifically, to appreciate the barriers that hinder midcareer academics, Karpiak interviewed 20 associate professors in Canada, aged between 41 and 59, studying in the humanities and social sciences, to discuss the impediments to promotion at this level. Many of these participants felt their administrative efforts, although vital to the institutions, were not often appreciated or even acknowledged. These individuals were seldom granted the time to pursue these responsibilities effectively.
The challenges that midcareer academics experience: Uncertain goals
Because of their burgeoning responsibilities, midcareer academics need to learn which goals and pursuits to prioritize. Yet, these academics often receive conflicting advice and cues about which activities to prioritize.
To illustrate, as Karpiak (1996) showed, the promotion criteria at these levels are ambiguous. Early career researchers are likely to receive promotions if they receive favorable teaching evaluations, publish their research, and attract some research income. Senior academics tend to seek more responsible leadership positions, perhaps as chair or director of academic units or research institutions. In contrast, many of the midcareer academics that Karpiak (1996) interviewed felt that promotion criteria were ambiguous. And these participants also felt that opportunities to seek feedback or advice about these criteria were limited, amplifying this uncertainty
Yet, as some research shows, when midcareer academics do receive advice or other information about promotion and development, these insights are often conflicting. For example, as Sorcinelli (1985) reported in one study, midcareer academics often dedicate most of their work hours to activities that revolve around teaching or curriculum. Chairs or other leaders will advocate the significance of these pursuits. Yet, these academics soon discover that promotions and pay are primarily dependent on success in research and not education. Indeed, even academics who earn teaching awards tended to be paid less than professors of similar experience but oriented more to research.
The challenges that midcareer academics experience: A sense of redundancy
Paradoxically, despite their burgeoning responsibilities, midcareer academics often felt redundant. To illustrate, in their review of past literature, Caffarella et al. (1989) revealed that many executives at institutions seem to conceptualize novice academics, who have recently completed their doctorates, as inexpensive, flexible, motivated, and energetic, at least compared to their older, midcareer counterparts. These executives also perceive the most senior academics as valuable because of their research programs, networks, and wisdom. Midcareer academics thus often feel vulnerable and uncertain about their role in the institution.
Yet, Caffarella et al. (1989) proposed an alternative perspective. According to these researchers, the midcareer stage, relative to their inexperienced and more experienced counterparts, represents the greatest source of impact and growth. Midcareer academics have developed the experience they need to contribute their insights and perspectives towards key decisions but are still flexible enough to embrace change and innovation.
The challenges that midcareer academics experience: Isolation
Partly as a consequence of their distinct roles and responsibilities, midcareer academics often feel especially isolated. As Lamber et al. (1993) revealed in a series of interviews, some midcareer academics felt they were not granted enough opportunities to collaborate intellectually and to explore scholarly opinions collectively. During an interview at one research university, for example, one midcareer academic described a feeling of intellectual isolation—a feeling that ultimately prompted the departure of this person from academia. Research activities, even in collaborations, were often conducted remotely or independently. These academics perceived research as ultimately a lonely affair. They felt their work and insights are not recognized—a concern because this sense of detachment is a key impediment to a sense of meaning. Conversely, only when individuals experience a sense of connection or belonging at work do their pursuits feel meaningful and significant (Lambert et al., 2013).
The challenges that female midcareer academics experience
Some of the challenges that midcareer academics experience may be exacerbated in specific demographics, such as females or minorities. To illustrate, as Ward and Wolf-Wendel (2012, 2015) revealed, many female academics, especially during midcareer, feel they cannot fulfill the norms of an ideal worker. To clarify, in academia, many individuals, perhaps unconsciously, assume that ideal workers pursue tenure as soon as they complete their doctorate, working in the lab or office late at night, while participating in conferences and other scholarly events, regularly and frequently. To maintain these hours and devote themselves to their work, ideal workers are presumed to depend on the support of their spouse or other family members to fulfil their family responsibilities.
How these norms affect the experience of female academics differs between early career and midcareer individuals. Specifically, to thrive in academia, female academics early in their career often feel obliged to work as if they were not mothers, eliciting pronounced stress. As they progress, however, midcareer female academics often recognize they cannot fulfill this ideal while maintaining a rewarding home life, as Ward and Wolf-Wendel (2012, 2015) showed. Rather than experience the stress of this tension between career and family, midcareer female academics are more inclined to resist the temptation to model the ideal worker, prioritizing their parental and family responsibilities and their physical health if needed (Ward & Wolf-Wendel, 2012, 2015). They carefully and systematically contemplate decisions about their careers, aspirations, and priorities, but are often cognizant of the political dynamics that could stifle their progress.
Yet, many circumstances and conditions affect the experience of these female midcareer academics. For example, Ward and Wolf-Wendel (2012, 2015) recognized how the experience of midcareer female academics varies across disciplines and settings. Inspired by this insight, some researchers explored the experience of these female academics in particular fields. Hart (2016), for example, investigated the experience of midcareer female academics in STEM. In this qualitative enquiry, Hart revealed that female associate professors, when seeking promotions, felt that leaders were more inclined to challenge the publication records of women than men. Leaders might assume that female academics who have not published extensively might not prioritize their work, deviating from the ideal worker. In contrast, leaders might ascribe the modest publication records of male academics to other causes, such as limited opportunities or mentoring.
Furthermore, as Hart (2016) showed, midcareer female academics also often felt excluded from leadership positions. Many institutions purported to embrace diversity in leadership. However, the practices of these institutions—such as the inclination to promote academics who worked extensively, if not excessively—reinforced norms that disadvantage many women.
Initiatives to support midcareer academics: Meaningful goals
Institutions have implemented, or at least attempted, a range of initiatives and programs to support the wellbeing, development, and productivity of midcareer academics. For example
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institutions often encourage midcareer academics to participate in mentoring schemes (Huston & Weaver, 2008), both as mentor and mentee, given that both roles can be invaluable
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indeed, midcareer academics should be encouraged to establish relationships with several mentors and mentees, each corresponding to distinct needs and goals (Sorcinelli & Yun, 2007)
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some institutions, such as Kansas State University, encourage midcareer academics, in consultation with department heads, to redesign the roles of these academics, embedding more leadership development and opportunities in lieu of other responsibilities (Baldwin & Chang, 2006)
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some institutions, such as Macalester College, introduced more leadership seminars and opportunities to develop leadership skills (Baldwin & Chang, 2006), ultimately to renew the pathways of these individuals
Regardless of the platform or mode, many of these interventions revolve around the importance of meaningful goals. These goals are not as pressing early in the careers of academics. At this time, the main goals of academics revolve around the continuity and stability of their jobs—to seek tenure or to develop a track record. But once these goals are satisfied, academics, in the middle of their career, need to manufacture other meaningful goals (Baldwin & Chang, 2006). They need to reignite their sense of vigor and endeavor (Strage et al., 2008).
Yet, because these goals vary considerably across these academics and depend on the unique circumstances of each person, these midcareer staff can no longer emulate role models. They need to forge their own unique pathway, integrating their interests, strengths, capabilities, opportunities, and experiences to clarify their aspirations and to construct a plan, often in concert with their line manager (Baldwin & Chang, 2006).
To help midcareer academics forge this pathway and reignite their enthusiasm, Strage et al. (2008) suggested that institutions should introduce several interrelated actions that are specific to the needs of this career stage. For example, institutions should
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inspire midcareer academics to pursue unfamiliar roles, such as mentor junior staff
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balance the need to grant midcareer academics more opportunities to explore their personal interests but still maintain accountability
Initiatives to support midcareer academics: Customized programs
Although meaningful goals may be relevant to all midcareer academics, the initiatives that support these academics must be customized and personalized. That is, as participants in the study that Lamber et al. (1993) conducted suggested, professional development programs, designed to facilitate the progress and productivity of midcareer academics, must accommodate the diverse needs and concerns of these individuals.
To justify this perspective, participants recognized that early career academics often experience shared needs. They need to learn about pedagogy, publications, and other activities that most academics undertake. In contrast, midcareer academics are not as likely to experience shared needs. As their roles progress, these individuals may consider a range of pathways. They can pursue a broader array of roles and responsibilities. Hence, initiatives and programs that are directed to this cohort must accommodate this variability. These initiatives must revolve around the distinct pathways of each person rather than, for example, comprise a series of standardized workshops and seminars.
Initiatives to support midcareer academics: The role of departmental heads or chairs
As Creswell and Brown (1992) showed, the attitudes of departmental chairs, or similar roles, can also influence the degree to which midcareer academics are afforded opportunities to develop. Creswell and Brown conducted a series of interviews with departmental chairs in North America. These chairs, although motivated to help academics who had recently been granted tenure to progress and to become full professors, often experienced particular challenges with these midcareer staff.
For example, some midcareer academics, at this stage in their career, had developed skills or practices that had been helpful in the past but might not benefit their progress in the future. For example, staff who had flourished in teaching, and thus defined themselves as exemplary in this role, would often shun research. Or staff who had become specialists in research practices that may have benefited their junior roles were not always willing to embrace more innovative research practices—practices that are vital to maintain their relevance in the future.
To overcome these problems, chairs attempted to inspire these individuals with specific challenges, to offer individual mentoring, to deliver positive reinforcement when appropriate, and to act as an advocate, striving to uncover resources and opportunities that enable these academics to thrive. Yet, simple acts were often especially beneficial. For example
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when one chair expressed appreciation in the work of some midcareer academics, their productivity tended to improve
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when another chair utilized the term “we” when discussing problems, the academics felt the problems were shared, promoting a sense of collaboration and accountability
Despite these actions, chairs felt that midcareer academics were harder to shift or to transform that early career academics. Therefore, to support the progress of midcareer academics, chairs would initiate simple goals initially—such as discussions about the possibility of publishing or presenting a literature review. Gradually, over time, these chairs would encourage loftier goals, such as grant applications.
Initiatives to support midcareer academics: Determinants of engagement
As these perspectives of chairs implies, midcareer academics are not always motivated to embrace opportunities to develop. Caffarella and Zinn (1999) proposed a framework, and presented a case study, to integrate the range of events and practices that affect the motivation of academics, especially midcareer, to embrace professional development. As this framework indicates, if midcareer academics have developed relationships with people who value and model personal development, these academics are more inclined to seek development opportunities themselves. Because of a variety of constraints however, such as an excessive workload, limited funding, unsupportive spouses, or family responsibilities, midcareer academics may perceive these development opportunities are luxuries they cannot afford at this time. Yet, even if they can pursue these development opportunities, some midcareer academics might shun these programs or initiatives. Specifically, midcareer academics tend to shun these development opportunities if
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they feel they cannot readily improve their competence—perhaps because these capabilities and qualities as entrenched or innate rather than characteristics that people can readily develop
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they overestimate their existing capabilities and qualities—common in competitive academic environments in which individuals feel compelled to promote their competence
Midcareer academics often experience a paradox. They want to participate in professional development so they can be promoted to meaningful roles and manage their workload better. Yet, because their roles are not always meaningful and their workload is excessive, they feel too exhausted to embrace professional development. As participants in the study that Lamber et al. (1993) recommended, to address these concerns, institutions should not only improve the programs that support wellbeing and family responsibilities of these midcareer academics, but also should understand, and address, the barriers that discourage the uptake of these provisions
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Introduction
Sometimes, often unexpectedly, individuals become aware of some solution, insight, opportunity, or possibility they had overlooked before. They might, for example, become aware that, from now on, all the skills and knowledge have been developed are relevant to a particular cause, such as elderly care. This awareness, realization, solution, or insight often seems to emerge from outside their conscious mind—almost from the ether. After they experience this awareness, they often feel an incredible urge to transmit this information or perspective to other people. They feel a profound motivation to act.
These three features—an awareness of some undiscovered possibility, the sense this awareness transpired from outside their conscious mind, and an urge to transmit this realization—are collectively called inspiration. Thus, inspiration comprises three distinct, but interrelated, facets:
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transcendence: a sense in which individuals become aware of some possibilities, opportunities, or avenues they had not recognized or appreciated before; this awareness feels vivid, as illustrated by metaphors like "illumination"
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evocation: the sense this awareness seems to emerge from some origin or agent outside their conscious mind; that is, individuals feel they are not responsible for this awareness—and hence inspiration thus feels passive
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approach motivation: a profound urge to transmit this awareness to other people or to implement this solution or insight; they feel compelled to promulgate and actualize this insight or opportunity.
Research into inspiration has uncovered some interesting insights (for a review, see Thrash et al., 2014). For example, when individuals observe a remarkable feat, they often feel inspired (Thrash, Maruskin, Cassidy, Fryer, & Ryan, 2010). When inspired, they often write and generate output more efficiently and concisely (Thrash, Elliot, Maruskin, & Casidy, 2010).
The topic of inspiration is vital to tertiary education institutions because of several reasons. Specifically
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staff at these institutions need to know how to inspire their students
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leaders at these institutions need to know how to inspire their staff
Consequences of inspiration: Creative production
Feelings of inspiration do not only energize people, such as students and staff, but also generate other benefits. For example, as Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010) revealed, inspiration predicts the production of creative work, whereas effort predicts the production of technical merit. Specifically, in this study, psychology students were instructed to write a paper, on any topic that was related to their course, in line with the guidelines and conventions of the American Psychological Association. Judges later rated the extent to which this paper was novel and creative as well as supported by the literature and consistent with American Psychological Association conventions.
In addition, the participants completed questions that assess the extent to which they experienced the three facets of inspiration while writing this essay: transcendence, evocation, and approach motivation, with items such as "I had important insights or revelations that I strove to express", "These ideas came to me unexpectedly or spontaneously", and "These ideas energized and motivated me" respectively. In addition, other questions evaluated the degree to which they engaged in effort, epitomized by items such as "I put forth a great deal of effort in writing this page".
Interestingly, only inspiration, and not effort, was positively related to whether the work was judged as creative and novel. In contrast, effort, but not inspiration, was positively related to the technical merit of this work, represented by the degree to which the paper was supported by the literature and consistent with American Psychological Association conventions.
A further study that Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010) reported showed the motivation to transmit or actualize these insights or opportunities ensured that individuals expressed their ideas efficiently. To demonstrate, in this study, participants read a fragment of a mystery, about a man and woman alarmed by a nearby sound. Participants first generated an idea about how to complete this story. They were also granted 30 minutes to write this ending.
In addition, participants specified the extent to which they felt their idea was inspiring. Interestingly, if they felt inspired by their idea, they wrote the ending more efficiently. That is, most of the words they typed were retained in the final draft rather than deleted during the process. Furthermore, they wrote more words across the course of this task. Finally, they used shorter words—words that can be typed more efficiently. As these findings reveal, when students feel inspired, their work is not only more creative but also more likely to be communicated efficiently and effectively
Consequences of inspiration: Wellbeing
Feelings of inspiration can also improve the emotions and satisfaction of students, staff, and other individuals. To demonstrate, as Thrash, Elliot, Maruskin, and Casidy (2010) showed, experiences of inspiration can promote wellbeing. In the first study, some participants watched an inspiring video, depicting the extraordinary talents and performance of Michael Jordan. Other participants merely watched a screen saver. Next, participants completed questionnaire that assessed their positive and negative affect, specifying the extent to which they felt excited or upset, for example. In addition, they completed a questionnaire to determine the extent to which they felt inspired.
The degree to which they felt inspired was positively related to positive affect but not related to negative affect. Furthermore, the inspiring video increased levels of positive affect, mediated by the reported level of inspiration. The inspiring video also diminished levels of negative affect—but level of inspiration did not mediate this effect (Thrash, Elliot, Maruskin, & Casidy, 2010).
The second study was similar, but explored more extensive measures of wellbeing, and controlled social desirability and personality. Furthermore, this study was longitudinal, conducted over a period of three months, called a cross-lagged design.
First, participants completed a measure of personality, the NEO-FFI, to assess the traits of extraversion, neuroticism, agreeableness, conscientious, and openness. A few days later they completed a measure of social desirability biases, using the Paulhus deception. In addition, on this day, they completed a set of scales, all representing various forms of subjective and eudaimonic wellbeing: positive affect, negative affect, life satisfaction, vitality (e.g., "I feel alive and vital"), and self-actualization (e.g., ""It is better to be yourself than to be popular"). The next day, they completed the trait version of the inspiration scale. Finally, several months later, the wellbeing of participants was again tested.
Significantly, inspiration at one time was positively related to all facets of wellbeing, except negative affect, three months later. These relationships persisted even after personality, social desirability biases, and previous wellbeing were controlled. These findings, thus, indicate that inspiration might subsequently improve wellbeing (Thrash, Elliot, Maruskin, & Casidy, 2010).
The third study was like the second study, apart from two key amendments. First, in addition to trait inspiration, a measure of goal inspiration was included. Participants specified eight goals they would like to achieve. For each goal, they answered two questions, such as "I am inspired to reach this goal". Second, inspiration was measured at both times.
Two key findings emerged. Trait and goal inspiration at one time predicted improvements in wellbeing several months later. In contrast, wellbeing at one time did not predict changes in inspiration several months later. Thus, inspiration facilitates wellbeing rather than vice versa.
Consequences of inspiration: The capacity to inspire other people
When people feel inspired, not only do they enjoy a range of benefits, but other individuals may also benefit from their inspiration. That is, inspiration may be contagious. If people write an article while inspired, readers may also feel inspired. If people speak while inspired, listeners might feel inspired as well
Thrash et al. (2017) examined this possibility. That is, in this study, 195 students wrote poems. In addition, 220 students read these poems. Both the writers and readers completed questionnaires that assessed the degree to which they felt inspired as well as their openness to experience, a personal trait. As hypothesized
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if the writers felt inspired while constructing the poetry, readers felt inspired while reading the poetry—and they perceived the text is more insightful and pleasant
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readers who are open to experience were especially likely to be inspired when writers were inspired.
Consequences of inspiration: Entrepreneurship
Inspiration might promote entrepreneurial behavior as well. After all, entrepreneurs often refer to feelings of inspiration when they promote an idea or venture.
Accordingly, Wartiovaara, Lahti, and Wincent (2019) proposed a theory that can explain both the antecedents of this inspiration and the consequences of this inspiration in an entrepreneurial setting. Specifically, the authors propose that entrepreneurs are more likely other individuals or managers to be susceptible to inspiration. Specifically, inspiration could explain many of the qualities and behaviors that epitomize these entrepreneurs.
First, inspiration may increase the likelihood that entrepreneurs perceive the value of some opportunity. The sense of transcendence that inspired entrepreneurs feel might elicit strong optimism. The approach motivation could absorb entrepreneurs in the opportunity—sometimes disregarding other complications and perspectives. Therefore, when inspired, entrepreneurs may even overestimate the value of their opportunities.
Similarly, because of this approach motivation and subsequent absorption, entrepreneurs may pursue this opportunity with vigor and concentration. They are, therefore, more likely to contemplate, refine, enhance, and thus optimize the opportunity, called elaboration. Indeed, inspired entrepreneurs may become so immersed in their pursuit that, in some circumstance, they may almost define themselves by these opportunities. That is, the inspiration can transform their sense of self.
Furthermore, when entrepreneurs feel inspired, their creative output and wellbeing improve. In this moment, they seem like they are flourishing. Research on emotional contagion suggest that people who feel a sense of alignment or affiliation with these entrepreneurs will also experience these positive emotions. Thus, individuals will naturally tend to gravitate towards these entrepreneurs, partly to experience this positive state.
Taken together, Wartiovaara et al. (2019) argue that some individuals—such as individuals who are especially receptive to experience and stirred to achieve may be more sensitive to novel ideas, possibilities, and opportunities, increasing the likelihood they will feel inspired. Once inspired, these individuals will tend to evaluate these opportunities positively, to immerse themselves in this pursuit, to improve and elaborate on these possibilities, and motivate other people to join this quest.
Indeed, Van Ewijk et al. (2021) showed empirically that inspiration is indeed associated with entrepreneurial behavior. In this study, 342 business and engineering university students completed a survey before and after a course on entrepreneurship. The survey included questions that assess the degree and frequency with which individuals feel inspired. The survey also included questions that assess entrepreneurial intentions, such as “I am very seriously thinking of starting my own venture or business”. Furthermore, the survey assessed the degree to which students felt the course inspired these entrepreneurial intentions, with questions like “The course inspired me to consider becoming an entrepreneur myself”. As the results revealed,
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individuals who reported trait inspiration were more likely to feel inspired by the course to consider entrepreneurial activities
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this inspiration from the course increased the likelihood that individuals genuinely intended to pursue entrepreneurial activities, but only if they had not accrued experience of entrepreneurial activities before
Accounts that explain the benefits of inspiration: Purpose in life and gratitude
Some researchers have explored the reasons that inspiration can be beneficial. For example, Thrash, Elliot, Maruskin, and Casidy (2010) contend that purpose in life and gratitude should mediate the association between inspiration and wellbeing. That is, these authors maintain that inspiration should instill purpose in life. Purpose in life emerges when individuals feel connected to something that transcends the self (cf., Buber, 1996; Seligman, 2002). Furthermore, purpose in life emanates from the pursuit of valued goals—goals that seem to be inherently or intrinsically significant (Emmons, 1999).
Inspiration implies an awareness of unrecognized opportunities; individuals thus feel they can transcend the self, integral to purpose in life. Similarly, the motivation to promulgate or actualize this awareness implies the insight is intrinsically important and valuable. Thus, inspiration should instill a sense of purpose in life (Thrash, Elliot, Maruskin, & Casidy, 2010)—a key source of wellbeing (e.g., Keyes, Shmotkin, & Ryff, 2002; Zika & Chamberlain, 1992).
Furthermore, inspiration should elicit gratitude. Gratitude is the response that individuals feel when they receive a gift, in some sense—that is, they experience some gain or benefit that can be attributed to someone else (e.g., Solomon, 1983). Inspiration should inculcate this sense of gratitude. That is, inspiration implies that individuals have become aware of a desirable opportunity, representing a gain, that emanated from some other origin. This gratitude, in turn, has been shown to be associated with wellbeing (e.g., Adler, M. G., & Fagley, 2005).
Thrash, Elliot, Maruskin, and Casidy (2010) conducted a study to assess these propositions. This study showed that purpose in life, represented by items like "I have no goals or aims at all" versus "I have very clear goals and aims", and gratitude, represented by the degree to which individuals felt grateful and thankful, mediated the association between inspiration and wellbeing (Thrash, Elliot, Maruskin, & Casidy, 2010).
Accounts that explain the benefits of inspiration: Inspired by and to
To characterize inspiration in more detail, Thrash and Elliot (2004) distinguish two main experiences that underpin inspiration: inspired by and inspired to. The first process entails the appreciation and recognition of an evocative opportunity, possibility, insight, awareness, and understanding, called inspired by. Transcendence and evocation manifest this process. The second process is the urge to extend, disseminate, utilize, and promulgate this opportunity, called inspired to. Approach motivation manifests this process. Confirmatory factor analysis substantiated these propositions (Thrash & Elliot, 2004).
Thrash and Elliot (2004) maintain this distinction between inspired by and inspired to is important. Specifically, this distinction implies that individuals might be inspired by an opportunity or awareness, regardless of their motivational concerns. These authors, for example, allude to the possibility that individuals can be inspired by the Grand Canyon, but nor inspired to act in response.
Sources of inspiration: Display of competence
Because of the apparent benefits of inspiration, teachers, leaders, and other individuals may be interested in how to promote this state in other people. Therefore, research has been conducted to ascertain the determinants of inspiration. For example, when individuals observe extraordinary skill and performance, they often experience this inspiration (e.g., Thrash & Elliot, 2004). In one study, conducted by Thrash, Elliot, Maruskin, and Casidy (2010), some participants watched two video clips of Michael Jordan, the basketball player. These clips portrayed remarkable performance and task mastery (Thrash & Elliot, 2008). Other participants, in the control condition, watched a saver on a computer screen instead.
Next, participants completed a state variant of the inspiration scale, with items like "I was inspired to do something". Relative to participants who watched the computer screen saver, participants who watched the Michael Jordan clip reported elevated levels of inspiration.
Conceivably, however, remarkable performance can promote envy rather than inspiration. if individuals are aware of differences between themselves and this inspiring person, a sense of inspiration tends to be elicited. Conversely, if individuals consider similarities between themselves and this inspiring person, negative affective states might be evoked (LeBouf & Estes, 2004). After individuals consider these similarities, this remarkable person becomes a benchmark of comparison; they might perceive themselves as incompetent in comparison (for empirical support, see LeBouf & Estes, 2004; for related studies, see Lockwood & Kunda, 1997).
Therefore, to inspire students, teachers might present some inspiring performances or skills that are relevant to the course or degree. But, to prevent envy, the individuals who performed these skills need to be, if possible, appreciably older than most of the students and had refined these skills over many years.
Sources of inspiration: Creative ideas
To foster inspiration, students or staff also need to be exposed to exciting and creative innovations. Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010) showed that creative ideas can also inspire a sense of inspiration rather than vice versa. In the first study conducted by Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010), participants completed a questionnaire each week, over a month. The questionnaire assessed both creative ideation, with items like "How often do you think of creative solutions to problems", and inspiration, with items like "How often did you (feel inspired) during the past week".
Confirmatory factor analysis confirmed that creative ideation and inspiration were distinct; structural equation modeling showed that creative ideation tended to proceed inspiration; that is, creative ideation one week tended to predict inspiration the next week, rather than vice versa.
In a subsequent study, also reported by Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010), participants were instructed to write a poem about the human condition. Next, they evaluated whether they felt the seminal idea or ideas were original, unique, and creative. In addition, they assessed whether they felt inspired, with items like "I was inspired to write". Finally, nine judges evaluated the poem; they assessed the degree to which the poem was creative, novel, original, and unusual as well as written grammatically and correctly.
Structural equation modeling indicated that fit was highest in a model that assumed that creative ideas, as represented by whether the seminal idea seemed novel, was related to inspiration, which in turn predicted whether the poem was judged as creative. That is, creative ideation seems to evoke a sense of inspiration, and this inspiration compels individuals to express these novel and original insights or ideas (Thrash, Maruskin, Cassidy, Fryer, & Ryan, 2010).
In this study, participants had also specified the degree to which they felt awe while they completed this task and dedicated effort to the activity. Awe predicted the degree to which the writing was grammatical and correct. Effort predicted the likelihood that individuals ensured the poem rhymes.
Sources of inspiration: Receptive engagement
Inspiration does entail transcendence—an awareness of unrecognized possibility. Thus, inspiration should be more pronounced in individuals who can surpass habitual patterns of thought and embrace novel perspectives, called receptive engagement (Thrash & Elliot, 2004). According to Thrash and Elliot (2004), this receptive engagement is epitomized by concepts like openness to aesthetics--a facet of openness to experience--as well as absorption and self-forgetfulness. Thrash and Elliot (2004) did indeed show these variables are related to inspiration and, specifically, transcendence.
Measures and correlates of inspiration
Researchers have developed both trait and state measures of inspiration (see Thrash & Elliot, 2003). Trait measures reflect the tendency of individuals to experience inspiration, either frequently or intensely. State measures assess whether a specific task, such as writing a poem, evoked this inspiration (Thrash & Elliot, 2003).
The trait measure comprises four items, each rated twice. The four items entail "I experience inspiration, "Something I encounter or experience inspires me", "I am inspired to do something", and "I feel inspired". For each item, participants rate "How often does this happen" to represent frequency and "How deeply or strongly " to represent intensity, each on seven-point rating scales. Internal consistency exceeded 0.9 for each subscale—frequency and intensity—as well as overall. Test-retest correlation over 7.5 weeks was .77 (Thrash & Elliot, 2003).
Across a few studies, Thrash and Elliot (2003) also examined factors that correlated with inspiration. Inspiration was positively associated with behavioral activation, sometimes called BAS, intrinsic motivation, openness to experience, number of majors, especially in humanities, absorption, experiential processing, rational processing, work mastery, perceived competence, self-esteem, optimism, self-determination, and positive emotions. Inspiration was not significantly related to social desirability biases. Thus, the confidence and willingness to engage in experiences and entertain many thoughts seems to be related to inspiration.
Researchers occasionally administer a state variant of this measure, usually after individuals complete a specific task, like a poem (Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010). The items need to be adapted but only slightly. The stem "I experience inspiration" is changed to "I experienced inspiration", for example.
Other measures of inspiration have been developed. Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010), for example, administered a state variant of inspiration that also distinguishes the three facets: transcendence, evocation, and approach motivation.
Nomological networks
Two of the studies conducted by Thrash, Maruskin, Cassidy, Fryer, and Ryan (2010) have attempted to clarify the nomological network of inspiration. Specifically, participants were instructed to write a poem about the human condition and, then, rate the extent to which they felt the seminal idea or ideas were creative. Next, they answered a series of questions on the perceived origin of these ideas, such as whether the idea seemed to emerge from conscious deliberation, the unconscious mind, a supernatural source, careful deliberation, and automatic processes. Similarly, the extent to which the ideas emerged suddenly, provoked surprise, seemed gripping, and surfaced as a complete idea was assessed. Finally, participants completed a scale to ascertain whether they experienced a sense of inspiration.
The correlations between the perceived origin of these ideas and inspiration uncovered some key insights. In particular, inspiration was positively associated with the sense the idea emerged automatically and suddenly from an unconscious or spiritual origin, often as a complete rather than partial insight that seemed gripping and riveting.
Thrash and Elliot (2004), in Study 1, investigated the nomological network of the three facets separately: transcendence, evocation, and approach motivation. In one study, for example, some participants were asked to write about an experience in which they felt inspired. Other participants wrote a typical experience in their everyday life.
Compared to other participants, individuals who wrote about an inspiring event were more likely to report some of the states that characterize transcendence. They experienced elevated levels of spirituality and meaning, as derived from self0report measures. They also used more words that reflect insight, such as "realized".
In addition, individuals who wrote about the inspiring event were more likely to report states that reflect evocation. Self-report measures indicated they felt more passive, rather than exerted willful control, during the task.
Finally, these individuals demonstrated more approach motivation. They experienced more positive affect, and less negative affect, than did participants who did not write about an inspiring event. They also reported they felt more involved in the task.
Neural underpinnings of inspiration
Research has not yet confirmed the brain regions and neurophysiological processes that underpin inspiration. Nevertheless, the regions that underpin related states, such as insight, have been explored. An important caveat, however, is that inspiration is not equivalent to insight. Insight entails a powerful sense of surprise (Bowden & Jung-Beeman, 2003). Inspiration is not related to surprise after controlling other positive mood states (Thrash, Maruskin, Cassidy, Fryer, & Ryan, 2010).
Bowden and Jung-Beeman (2003) showed that insight experiences tend to be associated with the right hemisphere. In one study, participants competed a remote associates task—a task in which the solutions sometimes materialize suddenly, called insight. Specifically, on each trial, three words appeared, such as palm, shoe, and house. The task of participants was to uncover a term that, if combined with each item, would form a compound word or phrase. They were granted seven seconds to answer. If they could not answer in this time, a word appeared, on either the left or right of the screen; participants had to name this word as rapidly as possible. Next, they had to decide whether this word was indeed the solution or answer to the previous problem. Finally, they specified the extent to which they experienced a sense of insight.
Often, even if participants could not identify the answer in seven seconds, they could name words more rapidly if these terms were indeed the answers than if these words were not the answers. In other words, the solution, even if not identified, was perhaps partially activated. Interesting, this finding was primarily observed if these solutions were presented to the left side, corresponding to the right hemisphere.
This finding is consistent with the right-hemisphere course semantic coding theory (e.g., Beeman & Bowden, 2000; Beeman, Bowden, & Gernsbacher, 2000; Beeman, Friedman, Grafman, Perez, Diamond, & Lindsay, 1994; Nakagawa, 1991; Titone, 1998). In particular, according to this theory, the right hemisphere, when exposed to a word, represents this term more diffusely. That is, many concepts that are only remotely associated with this word are partly activated. The left hemisphere, when exposed to a word, represents this term more precisely, activating only concepts that are closely associated with this word; only a single interpretation of this word also prevails.
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