The Impact of Emotions on Learning and Achievement: Towards a Theory of Cognitive/Motivational Mediators
Abstract
Cet article esquisse les grandes lignes d'une modélisation de l'influence des émotions sur la formation et la réussite des étudiants. De tels effets ont été abordés empiriquement pour ce qui est de l'anxiété due au testing et de l'état d'esprit positif ou négatif. On peut soutenir que bien d'autres émotions agissent sur la performance. L'élaboration d'hypothèses sur ce genre d'influences présuppose qu'elles doivent être médiatisées a) par des mécanismes cognitifs de stockage, de traitement et de restitution de l'information; par l'impact de l'émotion sur l'attention et b) par les motivations intrinsèques et extrinsèques liées au travail universitaire. On fait l'hypothèse que les effets globaux des émotions dépendent de l'intéraction de différents mécanismes. Les effets nets des émotions positives sont supposés être positifs dans la plupart des cas tandis que les effets bruts des émotions négatives peuvent être ambivalents. Les principales retombées sur la recherche en psychologie appliquée sont décrites. This paper outlines assumptions of a model on how emotions influence students' learning and achievement. Such effects have been studied empirically for test anxiety, and for positive vs. negative mood. It may be assumed, however, that many other emotions exert effects on performance as well. Assumptions on such influences imply that they may be mediated: (1) by cognitive mechanisms of storage and retrieval of information, of processing information, and of emotion's attentiona…
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Emotions are an important factor in any learning process, since they influence information processing, memory and performance.
“It is commonly acknowledged that emotions are an important factor in any learning process, since it influences information processing, memory and performance (Pekrun, 1992).”
From Towards multimodal emotion recognition in e-learning environments (2016) · cites this paper as Pekrun, 1992
Cites
An attributional theory of achievement motivation and emotion
Weiner, B. (1985) · Psychological Review · doi:10.1037/0033-295x.92.4.548 · Cited by 7,846 · see citing works
Positive affect facilitates creative problem solving.
Isen, A. M., Daubman, K. A., & Nowicki, G. P. (1987) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.52.6.1122 · Cited by 2,986 · see citing works
Correlates, Causes, Effects, and Treatment of Test Anxiety
Hembree, R. (1988) · Review of Educational Research · doi:10.3102/00346543058001047 · Cited by 1,723 · see citing works
Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems.
Bandura, A., & Cervone, D. (1983) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.45.5.1017 · Cited by 1,511 · see citing works
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Pekrun, R. (2006) · Educational Psychology Review · doi:10.1007/s10648-006-9029-9 · Cited by 5,566 · see citing works
Self-citationPekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002) · Educational Psychologist · doi:10.1207/s15326985ep3702_4 · Cited by 3,931 · see citing works
Self-citationPekrun, R., Goetz, T., Frenzel, A. C., Barchfeld, P., & Perry, R. P. (2011) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2010.10.002 · Cited by 2,248 · see citing works
Self-citationThe Emotional Brain, Fear, and the Amygdala
LeDoux, J. (2003) · Cellular and Molecular Neurobiology · doi:10.1023/a:1025048802629 · Cited by 1,818 · see citing works
Academic Emotions and Student Engagement
Pekrun, R., & Linnenbrink-Garcia, L. (2012) · Handbook of Research on Student Engagement · doi:10.1007/978-1-4614-2018-7_12 · Cited by 1,181 · see citing works
Self-citationEmotional design in multimedia learning: Effects of shape and color on affect and learning
Plass, J. L., Heidig, S., Hayward, E. O., Homer, B. D., & Um, E. (2014) · Learning and Instruction · doi:10.1016/j.learninstruc.2013.02.006 · Cited by 550 · see citing works
The Prevalence and Effects of Test Anxiety in School Children
McDonald, A. S. (2001) · Educational Psychology · doi:10.1080/01443410020019867 · Cited by 437 · see citing works
Academic boredom in under- and over-challenging situations
Acee, T. W., Kim, H., Kim, H. J., Kim, J.-I., Chu, H.-N. R., Kim, M., Cho, Y., & Wicker, F. W. (2010) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2009.08.002 · Cited by 237 · see citing works
Artificial intelligence moving serious gaming: Presenting reusable game AI components
Westera, W., Prada, R., Mascarenhas, S., Santos, P. A., Dias, J., Guimarães, M., Georgiadis, K., Nyamsuren, E., Bahreini, K., Yumak, Z., et al. (2020) · Education and Information Technologies · doi:10.1007/s10639-019-09968-2 · Cited by 136 · see citing works
Towards multimodal emotion recognition in e-learning environments
Bahreini, K., Nadolski, R., & Westera, W. (2016) · Interactive Learning Environments · doi:10.1080/10494820.2014.908927 · Cited by 137 · see citing works
Ouherrou, N., Elhammoumi, O., Benmarrakchi, F., & El Kafi, J. (2019) · Education and Information Technologies · doi:10.1007/s10639-018-09852-5 · Cited by 83 · see citing works
A Review of Emotion-Aware Systems for e-Learning in Virtual Environments
Feidakis, M. (2016) · Formative Assessment, Learning Data Analytics and Gamification · doi:10.1016/b978-0-12-803637-2.00011-7 · Cited by 54 · see citing works
Kotler, S., Mannino, M., Kelso, S., & Huskey, R. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104956 · Cited by 52 · see citing works
Researching state shame with the experiential shame scale.
Turner, J. E. (2014) · The Journal of Psychology · doi:10.1080/00223980.2013.818927 · Cited by 52 · see citing works
Testing Stylistic Interventions to Reduce Emotional Impact of Content Moderation Workers
Karunakaran, S., & Ramakrishan, R. (2019) · Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · doi:10.1609/hcomp.v7i1.5270 · Cited by 28 · see citing works
Vidanaralage, J., Dharmaratne, A., & Haque, S. (2022) · Australasian Journal of Educational Technology · doi:10.14742/ajet.7473 · Cited by 8 · see citing works
“Emotions drive attention (Vuilleumier, 2005), influencing learning motivation and facilitating active encoding in memory (Pekrun, 1992; Seli et al., 2016).”
Background
- Authors
- Pekrun, R.
- Affiliations
- University of Regensburg (DE)
- Corresponding author
- Pekrun, Reinhard
- ORCID
- Pekrun, Reinhard
- Venue
- Applied Psychology
- Publisher
- Wiley
- Published
- 1992-10
- Volume
- 41
- Issue
- 4
- Pages
- 359-376
- ISSN
- 0269-994X (ISSN-L)
- 1464-0597
- OpenAlex
- W2054420970
- Cited by
- 691
- References
- 4
- Citations by year
- 2026: 19 · 2025: 35 · 2024: 61 · 2023: 48 · 2022: 41 · 2021: 44 · 2020: 40 · 2019: 43 · 2018: 35 · 2017: 35 · 2016: 27 · 2015: 30 · 2014: 28 · 2013: 38 · 2012: 26
- FWCI
- 0.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Applied Psychology (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Social Sciences › Education › Educational Outcomes and Influences
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- emotions, learning, academic performance, test anxiety, positive mood, negative mood, cognitive mediation, attention, intrinsic motivation, extrinsic motivation, information storage and retrieval
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