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A Motivational Science Perspective on the Role of Student Motivation in Learning and Teaching Contexts.
Abstract
A motivational science perspective on student motivation in learning and teaching contexts is developed that highlights 3 general themes for motivational research. The 3 themes include the importance of a general scientific approach for research on student motivation, the utility of multidisciplinary perspectives, and the importance of use-inspired basic research on motivation. Seven substantive questions are then suggested as important directions for current and future motivational science research efforts. They include (1) What do students want? (2) What motivates students in classrooms? (3) How do students get what they want? (4) Do students know what they want or what motivates them? (5) How does motivation lead to cognition and cognition to motivation? (6) How does motivation change and develop? and (7) What is the role of context and culture? Each of the questions is addressed in terms of current knowledge claims and future directions for research in motivational science.
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Cites
Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 54,599
Self-efficacy: The exercise of control
Bandura, A., Freeman, W. H., & Lightsey, R. (1999) · Journal of Cognitive Psychotherapy · doi:10.1891/0889-8391.13.2.158 · Cited by 46,835
The need to belong: Desire for interpersonal attachments as a fundamental human motivation.
Baumeister, R. F., & Leary, M. R. (1995) · Psychological Bulletin · doi:10.1037//0033-2909.117.3.497 · Cited by 23,245
Culture and the self: Implications for cognition, emotion, and motivation.
Markus, H. R., & Kitayama, S. (1991) · Psychological Review · doi:10.1037/0033-295x.98.2.224 · Cited by 21,995
Fredrickson, B. L. (2001) · American Psychologist · doi:10.1037//0003-066x.56.3.218 · Cited by 18,025
A social-cognitive approach to motivation and personality.
Dweck, C. S., & Leggett, E. L. (1988) · Psychological Review · doi:10.1037/0033-295x.95.2.256 · Cited by 9,745
Deci, E. L., Koestner, R., & Ryan, R. M. (1999) · Psychological Bulletin · doi:10.1037/0033-2909.125.6.627 · Cited by 7,176
Classrooms: Goals, structures, and student motivation.
Ames, C. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.3.261 · Cited by 6,468
Zimmerman, B. J. (2000) · Handbook of Self-Regulation · doi:10.1016/b978-012109890-2/50031-7 · Cited by 6,069
Rethinking individualism and collectivism: Evaluation of theoretical assumptions and meta-analyses.
Oyserman, D., Coon, H. M., & Kemmelmeier, M. (2002) · Psychological Bulletin · doi:10.1037/0033-2909.128.1.3 · Cited by 5,758
Cited by
A Review of Self-regulated Learning: Six Models and Four Directions for Research
Panadero, E. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00422 · Cited by 2,915
“In further research (Boekaerts et al., 2003; Boekaerts, 2007), it was found that outcome assessments after doing homework were positively influenced by both competence and value appraisals.”
BackgroundSkinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009) · Educational and Psychological Measurement · doi:10.1177/0013164408323233 · Cited by 1,587
Professional competence of teachers: Effects on instructional quality and student development.
Kunter, M., Klusmann, U., Baumert, J., Richter, D., Voss, T., & Hachfeld, A. (2013) · Journal of Educational Psychology · doi:10.1037/a0032583 · Cited by 1,553
Self-regulation in the classroom: a perspective on assessment and intervention.
Boekaerts, M., & Corno, L. (2005) · Applied Psychology · doi:10.1111/j.1464-0597.2005.00205.x · Cited by 1,479
Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis
Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016) · Review of Educational Research · doi:10.3102/0034654315582065 · Cited by 1,274
The making of the motivated strategies for learning questionnaire.
Duncan, T. G., & McKeachie, W. J. (2005) · Educational Psychologist · doi:10.1207/s15326985ep4002_6 · Cited by 1,024
Mega, C., Ronconi, L., & De Beni, R. (2014) · Journal of Educational Psychology · doi:10.1037/a0033546 · Cited by 1,007
Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014) · Journal of Computing in Higher Education · doi:10.1007/s12528-013-9077-3 · Cited by 870
Taylor, G., Jungert, T., Mageau, G. A., Schattke, K., Dedic, H., Rosenfield, S., & Koestner, R. (2014) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2014.08.002 · Cited by 816
Enhancing interest and performance with a utility value intervention.
Hulleman, C. S., Godes, O., Hendricks, B. L., & Harackiewicz, J. M. (2010) · Journal of Educational Psychology · doi:10.1037/a0019506 · Cited by 757
Autonomous, controlled, and amotivated types of academic motivation: A person-oriented analysis.
Ratelle, C. F., Guay, F., Vallerand, R. J., Larose, S., & Senécal, C. (2007) · Journal of Educational Psychology · doi:10.1037/0022-0663.99.4.734 · Cited by 754
Science Motivation Questionnaire II: Validation with Science Majors and Nonscience Majors
Glynn, S. M., Brickman, P., Armstrong, N., & Taasoobshirazi, G. (2011) · Journal of Research in Science Teaching · doi:10.1002/tea.20442 · Cited by 733
Self-regulated learning: the educational legacy of Paul R. Pintrich.
Schunk, D. H. (2005) · Educational Psychologist · doi:10.1207/s15326985ep4002_3 · Cited by 678
Roscoe, R. D., & Chi, M. T. H. (2007) · Review of Educational Research · doi:10.3102/0034654307309920 · Cited by 647
Motivation Interventions in Education: A Meta-Analytic Review
Lazowski, R. A., & Hulleman, C. S. (2016) · Review of Educational Research · doi:10.3102/0034654315617832 · Cited by 607
Liaw, S.-S., & Huang, H.-M. (2013) · Computers & Education · doi:10.1016/j.compedu.2012.07.015 · Cited by 571
Measuring cost: The forgotten component of expectancy-value theory
Flake, J. K., Barron, K. E., Hulleman, C., McCoach, B. D., & Welsh, M. E. (2015) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2015.03.002 · Cited by 554
Harackiewicz, J. M., Rozek, C. S., Hulleman, C. S., & Hyde, J. S. (2012) · Psychological Science · doi:10.1177/0956797611435530 · Cited by 503
Bureau, J. S., Howard, J. L., Chong, J. X. Y., & Guay, F. (2022) · Review of Educational Research · doi:10.3102/00346543211042426 · Cited by 414
Routledge Handbook of Physical Education Pedagogies
(2016) · doi:10.4324/9781315743561 · Cited by 297
Theories of motivation: A comprehensive analysis of human behavior drivers
Bandhu, D., Mohan, M. M., Nittala, N. A. P., Jadhav, P., Bhadauria, A., & Saxena, K. K. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104177 · Cited by 555
Enhancing student motivation and engagement: The effects of a multidimensional intervention
Martin, A. J. (2008) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2006.11.003 · Cited by 293
Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning
Rau, M. A. (2017) · Educational Psychology Review · doi:10.1007/s10648-016-9365-3 · Cited by 281
A Meta-Analytic Review of the Relations Between Motivation and Reading Achievement for K–12 Students
Toste, J. R., Didion, L., Peng, P., Filderman, M. J., & McClelland, A. M. (2020) · Review of Educational Research · doi:10.3102/0034654320919352 · Cited by 269
Exploring feedback and student characteristics relevant for personalizing feedback strategies
Narciss, S., Sosnovsky, S., Schnaubert, L., Andrès, E., Eichelmann, A., Goguadze, G., & Melis, E. (2014) · Computers & Education · doi:10.1016/j.compedu.2013.09.011 · Cited by 260
Ackerman, R., & Lauterman, T. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.04.023 · Cited by 254
Stability, change, and implications of students’ motivation profiles: A latent transition analysis
Gillet, N., Morin, A. J. S., & Reeve, J. (2017) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2017.08.006 · Cited by 252
A Review of Self-Report and Alternative Approaches in the Measurement of Student Motivation
Fulmer, S. M., & Frijters, J. C. (2009) · Educational Psychology Review · doi:10.1007/s10648-009-9107-x · Cited by 227
(2011) · Cited by 218
de Boer, H., Donker, A. S., Kostons, D. D. N. M., & van der Werf, G. P. C. (2018) · Educational Research Review · doi:10.1016/j.edurev.2018.03.002 · Cited by 210
The structure of academic self-concepts revisited: The nested Marsh/Shavelson model.
Brunner, M., Keller, U., Dierendonck, C., Reichert, M., Ugen, S., Fischbach, A., & Martin, R. (2010) · Journal of Educational Psychology · doi:10.1037/a0019644 · Cited by 181
Lin, P.-Y., Chai, C.-S., Jong, M. S.-Y., Dai, Y., Guo, Y., & Qin, J. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2020.100006 · Cited by 171
Zepeda, C. D., Richey, J. E., Ronevich, P., & Nokes-Malach, T. J. (2015) · Journal of Educational Psychology · doi:10.1037/edu0000022 · Cited by 167
Mohebbi, A. (2025) · Cogent Education · doi:10.1080/2331186x.2024.2433814 · Cited by 161
Motivation for PhD studies: Scale development and validation
Litalien, D., Guay, F., & Morin, A. J. S. (2015) · Learning and Individual Differences · doi:10.1016/j.lindif.2015.05.006 · Cited by 143
A comparison of high and low achieving students on self-regulated learning variables
DiFrancesca, D., Nietfeld, J. L., & Cao, L. (2016) · Learning and Individual Differences · doi:10.1016/j.lindif.2015.11.010 · Cited by 141
(2006) · Cited by 126
Calvo‐Ferrer, J. R. (2017) · British Journal of Educational Technology · doi:10.1111/bjet.12387 · Cited by 120
Tseng, S.-C., & Tsai, C.-C. (2010) · The Internet and Higher Education · doi:10.1016/j.iheduc.2010.01.001 · Cited by 118
Hazari, Z., Cass, C., & Beattie, C. (2015) · Journal of Research in Science Teaching · doi:10.1002/tea.21214 · Cited by 111
Factors that promote high school graduation: a review of the literature
Zaff, J. F., Donlan, A., Gunning, A., Anderson, S. E., McDermott, E., & Sedaca, M. (2017) · Educational Psychology Review · doi:10.1007/s10648-016-9363-5 · Cited by 102
Garn, A. C., Morin, A. J. S., & Lonsdale, C. (2019) · Journal of Educational Psychology · doi:10.1037/edu0000283 · Cited by 92
Self-regulation strategies in blended learning environments in higher education: a systematic review
Eggers, J. H., Oostdam, R., & Voogt, J. (2021) · Australasian Journal of Educational Technology · doi:10.14742/ajet.6453 · Cited by 89
The instrumental value of conceptual frameworks in educational technology research
Antonenko, P. D. (2015) · Educational Technology Research and Development · doi:10.1007/s11423-014-9363-4 · Cited by 81
Investigating the Impact of Gamification on Student Motivation, Engagement, and Performance
García-López, I. M., Acosta-Gonzaga, E., & Ruiz-Ledesma, E. F. (2023) · Education Sciences · doi:10.3390/educsci13080813 · Cited by 78
Lai, C.-L., & Hwang, G.-J. (2015) · Computers & Education · doi:10.1016/j.compedu.2015.02.011 · Cited by 78
Balluerka, N., Gorostiaga, A., Alonso‐Arbiol, I., & Aritzeta, A. (2016) · Journal of Adolescence · doi:10.1016/j.adolescence.2016.08.009 · Cited by 71
Do students distinguish between different types of performance goals?
Bong, M., Woo, Y., & Shin, J. (2013) · The Journal of Experimental Education · doi:10.1080/00220973.2012.745464 · Cited by 57
Using Value-Added Models to Measure Teacher Effects on Students’ Motivation and Achievement
Ruzek, E. A., Domina, T., Conley, A. M., Duncan, G. J., & Karabenick, S. A. (2015) · The Journal of Early Adolescence · doi:10.1177/0272431614525260 · Cited by 57
What motivates enrolment in programming MOOCs?
Luik, P., Suviste, R., Lepp, M., Palts, T., Tõnisson, E., Säde, M., & Papli, K. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12600 · Cited by 44
Valero, D., & Hirschi, A. (2016) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2016.01.003 · Cited by 44
De Clercq, M., Galand, B., & Frenay, M. (2013) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2012.10.003 · Cited by 37
Huang, H.-W., Teng, D. C.-E., & Tiangco, J. A. N. Z. (2025) · Journal of Science Education and Technology · doi:10.1007/s10956-024-10179-9 · Cited by 23
Student-involved data use: Establishing the evidence base
Jimerson, J. B., & Reames, E. (2015) · Journal of Educational Change · doi:10.1007/s10833-015-9246-4 · Cited by 23
Moderator effects of mobile users’ pedagogical role on science learning: a meta-analysis.
Shi, L., & Kopcha, T. J. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13210 · Cited by 17
Engineering Motivation Using the Belief-Expectancy-Control Framework
E. Clark, R., & Saxberg, B. (2018) · Interdisciplinary Education and Psychology · doi:10.31532/interdiscipeducpsychol.2.1.004 · Cited by 17
Kokkinos, C. M., & Voulgaridou, I. (2018) · Educational Psychology · doi:10.1080/01443410.2018.1456651 · Cited by 15
How and why teachers engage students with data
Jimerson, J. B., Cho, V., Scroggins, K. A., Balial, R., & Robinson, R. R. (2019) · Educational Studies · doi:10.1080/03055698.2018.1509781 · Cited by 13
Konradt, U., Ellwart, T., & Gevers, J. (2021) · Learning and Individual Differences · doi:10.1016/j.lindif.2021.102003 · Cited by 11
Imhof, M., & Schulte-Jakubowski, K. (2015) · Social Psychology of Education · doi:10.1007/s11218-015-9301-2 · Cited by 2
Wagner, D., & Perels, F. (2012) · ISRN Education · doi:10.5402/2012/848562 · Cited by 2
Metadata
- Authors
- Pintrich, P. R.
- Venue
- Journal of Educational Psychology
- Published
- 2003-12
- Volume
- 95
- Issue
- 4
- Pages
- 667-686
- ISSN
- 0022-0663 (ISSN-L)
- 1939-2176
- OpenAlex
- W2104264329
- Cited by
- 3,047
- References
- 36
- FWCI
- 40.77
- Type
- journal article
- Language
- en
- Open access
- closed
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