Supporting Self-Regulated Learning and Academic Achievement with Personalized Peer-Comparison Feedback in Higher Education





learning analytics dashboard, self-regulated learning, social comparison, motivation, data and tools report


Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining meaningful feedback with well-designed peer comparison using a learning analytics dashboard provides a solution. Third-year bachelor students were randomly assigned to have access to the learning analytics dashboard IguideME (treatment, n=31) or no access (control, n=31). Dashboard users were asked to indicate their desired grade, which was used to construct peer-comparison groups. Personalized peer-comparison feedback was provided via the dashboard. The effects were studied using quantitative and qualitative data, including the Motivated Strategies for Learning Questionnaire (MSLQ) and the Achievement Goal Questionnaire (AGQ). Compared to the control group, the treatment group achieved higher scores for the MSLQ components “metacognitive self-regulation” and “peer learning,” and for the AGQ component “other-approach” (do better than others). The treatment group performed better on reading assignments and achieved higher grades for high-level Bloom exam questions. These data support the hypothesis that personalized peer-comparison feedback can be used to improve self-regulated learning and academic achievement.


Blanton, H., Buunk, B. P., Gibbons, F. X., & Kuyper, H. (1999). When better-than-others compare upward: Choice of comparison and comparative evaluation as independent predictors of academic performance. Journal of Personality and Social Psychology, 76(3), 420–430. https://doi.org/10.1037/0022-3514.76.3.420

Cury, F., Da Fonséca, D., Rufo, M., & Sarrazin, P. (2002). Perceptions of competence, implicit theory of ability, perception of motivational climate, and achievement goals: A test of the trichotomous conceptualization of endorsement of achievement motivation in the physical education setting. Perceptual and Motor Skills, 95(1), 233–244. https://doi.org/10.2466/pms.2002.95.1.233

Davis, D., Jivet, I., Kizilcec, R. F., Chen, G., Hauff, C., & Houben, G.-J. (2017). Follow the successful crowd: Raising MOOC completion rates through social comparison at scale. Proceedings of the 7th International Conference on Learning Analytics and Knowledge (LAK ’17), 13–17 March 2017, Vancouver, BC, Canada (pp. 454–463). ACM Press. https://doi.org/10/gk84vr

Day, E. A., Radosevich, D. J., & Chasteen, C. S. (2003). Construct- and criterion-related validity of four commonly used goal orientation instruments. Contemporary Educational Psychology, 28(4), 434–464. https://doi.org/10.1016/S0361-476X(02)00043-7

Duan, X., Wang, C., & Rouamba, G. (2022). Designing a learning analytics dashboard to provide students with actionable feedback and evaluating its impacts. Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022), 21–23 April 2022, Online (Vol. 2, pp. 117–127). ScitePress. https://doi.org/10.5220/0011116400003182

Elliot, A. J., & Harackiewicz, J. M. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality and Social Psychology, 70(3), 461–475. https://doi.org/10.1037/0022-3514.70.3.461

Elliot, A. J., Murayama, K., & Pekrun, R. (2011). A 3 × 2 achievement goal model. Journal of Educational Psychology, 103(3), 632–648. https://doi.org/10/ch6d89

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140. https://doi.org/10.1177/001872675400700202

Fleur, D. S., van den Bos, W., & Bredeweg, B. (2020). Learning analytics dashboard for motivation and performance. In V. Kumar & C. Troussas (Eds.), Proceedings of the 16th International Conference on Intelligent Tutoring Systems (ITS 2020), 8–12 June 2020, Athens, Greece (Lecture Notes in Computer Science, vol. 12149, pp. 411–419). Springer. https://doi.org/10.1007/978-3-030-49663-0_51

Garcia, S. M., Tor, A., & Schiff, T. M. (2013). The psychology of competition: A social comparison perspective. Perspectives on Psychological Science, 8(6), 634–650. https://doi.org/10.1177/1745691613504114

Gerber, J. P., Wheeler, L., & Suls, J. (2018). A social comparison theory meta-analysis 60+ years on. Psychological Bulletin, 144(2), 177–197. https://doi.org/10.1037/bul0000127

Guimond, S., Branscombe, N. R., Brunot, S., Buunk, A. P., Chatard, A., Désert, M., Garcia, D. M., Haque, S., Martinot, D., & Yzerbyt, V. (2007). Culture, gender, and the self: Variations and impact of social comparison processes. Journal of Personality and Social Psychology, 92(6), 1118–1134. https://doi.org/10/fdjrvk

Günther, S. A. (2021). The impact of social norms on students’ online learning behavior: Insights from two randomized controlled trials. Proceedings of the 11th International Conference on Learning Analytics and Knowledge (LAK ’21), 12–16 April 2021, Irvine, CA, USA (pp. 12–21). ACM Press. https://doi.org/10.1145/3448139.3448141

Hadwin, A., & Oshige, M. (2011). Self-regulation, coregulation, and socially shared regulation: Exploring perspectives of social in self-regulated learning theory. Teachers College Record, 113(2), 240–264. https://doi.org/10.1177/016146811111300204

Huguet, P., Dumas, F., Monteil, J. M., & Genestoux, N. (2001). Social comparison choices in the classroom: Further evidence for students’ upward comparison tendency and its beneficial impact on performance. European Journal of Social Psychology, 31(5), 557–578. https://doi.org/10.1002/ejsp.81

Huguet, P., Galvaing, M. P., Monteil, J. M., & Dumas, F. (1999). Social presence effects in the Stroop task: Further evidence for an attentional view of social facilitation. Journal of Personality and Social Psychology, 77(5), 1011–1025. https://doi.org/10.1037/0022-3514.77.5.1011

Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness is not enough: Pitfalls of learning analytics dashboards in the educational practice. Proceedings of the 12th European Conference on Technology Enhanced Learning (EC-TEL 2017), 12–15 September 2017, Tallinn, Estonia. (Lecture Notes in Computer Science, vol. 10474, pp. 82–96). Springer. https://doi.org/10/gg4jzv

Kang, P., Lee, Y., Choi, I., & Kim, H. (2013). Neural evidence for individual and cultural variability in the social comparison effect. Journal of Neuroscience, 33(41), 16200–16208. https://doi.org/10/gjjt7p

Knobbout, J., & Van Der Stappen, E. (2020). Where is the learning in learning analytics? A systematic literature review on the operationalization of learning-related constructs in the evaluation of learning analytics interventions. IEEE Transactions on Learning Technologies, 13(3), 631–645. https://doi.org/10.1109/TLT.2020.2999970

Lim, L., Dawson, S., Joksimović, S., & Gašević, D. (2019). Exploring students’ sensemaking of learning analytics dashboards: Does frame of reference make a difference? Proceedings of the 9th International Conference on Learning Analytics and Knowledge (LAK ’19), 4–8 March 2019, Tempe, AZ, USA (pp. 250–259). ACM Press. https://doi.org/10.1145/3303772.3303804

Linnenbrink, E. A., & Pintrich, P. R. (2002). Motivation as an enabler for academic success. School Psychology Review, 31(3), 313–327. https://doi.org/10.1080/02796015.2002.12086158

Matcha, W., Uzir, N. A., Gašević, D., & Pardo, A. (2020). A systematic review of empirical studies on learning analytics dashboards: A self-regulated learning perspective. IEEE Transactions on Learning Technologies, 13(2), 226–245. https://doi.org/10.1109/TLT.2019.2916802

Nebel, S., Beege, M., Schneider, S., & Rey, G. D. (2016). The higher the score, the higher the learning outcome? Heterogeneous impacts of leaderboards and choice within educational videogames. Computers in Human Behavior, 65, 391–401. https://doi.org/10.1016/j.chb.2016.08.042

Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00422

Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31(6), 459–470. https://doi.org/10/dwqb9s

Pintrich, P. R., & Garcia, T. (1994). Self-regulated learning in college students: Knowledge, strategies, and motivation. In P. R. Pintrich, D. R. Brown & C. E. Weintein (Eds.), Student motivation, cognition, and learning: Essays in honor of Wilbert J. McKeachie (pp. 113–133). Lawrence Erlbaum.

Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). The University of Michigan. https://eric.ed.gov/?id=ED338122

Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1993). Reliability and predictive validity of the motivated strategies for learning questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801–813. https://doi.org/10.1177/0013164493053003024

Russell, J.-E., Smith, A., & Larsen, R. (2020). Elements of success: Supporting at-risk student resilience through learning analytics. Computers & Education, 152, 103890. https://doi.org/10/gjk2jr

Schunk, D. H., & Zimmerman, B. J. (2007). Motivation and self-regulated learning: Theory, research, and applications. Routledge.

Schwendimann, B. A., Rodríguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet, D., & Dillenbourg, P. (2017). Perceiving learning at a glance: A systematic literature review of learning dashboard research. IEEE Transactions on Learning Technologies, 10(1), 30–41. https://doi.org/10/f9t33q

Smith, M., Duda, J., Allen, J., & Hall, H. (2002). Contemporary measures of approach and avoidance goal orientations: Similarities and differences. British Journal of Educational Psychology, 72(2), 155–190. https://doi.org/10.1348/000709902158838

Suls, J., Martin, R., & Wheeler, L. (2002). Social comparison: Why, with whom, and with what effect? Current Directions in Psychological Science, 11(5), 159–163. https://doi.org/10/cwtnsg

Summers, J. J., Schallert, D. L., & Muse Ritter, P. (2003). The role of social comparison in students’ perceptions of ability: An enriched view of academic motivation in middle school students. Contemporary Educational Psychology, 28(4), 510–523. https://doi.org/10.1016/S0361-476X(02)00059-0

Susnjak, T., Ramaswami, G. S., & Mathrani, A. (2022). Learning analytics dashboard: A tool for providing actionable insights to learners. International Journal of Educational Technology in Higher Education, 19, 12. https://doi.org/10.1186/s41239-021-00313-7

Trias, D., Huertas, J. A., Mels, C., Castillejo, I., & Ronqui, V. (2021). Self-regulated learning, academic achievement and socioeconomic context at the end of primary school. Revista Interamericana de Psicología/Interamerican Journal of Psychology, 55(2), e1509. https://doi.org/10.30849/ripijp.v55i2.1509

Tsai, Y.-S., Rates, D., Moreno-Marcos, P. M., Muñoz-Merino, P. J., Jivet, I., Scheffel, M., Drachsler, H., Delgado Kloos, C., & Gašević, D. (2020). Learning analytics in European higher education: Trends and barriers. Computers & Education, 155, 103933. https://doi.org/10/gg2v3t

van Vliet, E. A., Winnips, J. C., & Brouwer, N. (2015). Flipped-class pedagogy enhances student metacognition and collaborative-learning strategies in higher education but effect does not persist. CBE—Life Sciences Education, 14(3), ar26. https://doi.org/10.1187/cbe.14-09-0141

Viberg, O., Khalil, M., & Baars, M. (2020). Self-regulated learning and learning analytics in online learning environments: A review of empirical research. Proceedings of the 10th International Conference on Learning Analytics and Knowledge (LAK ’20), 23–27 March 2020, Frankfurt, Germany (pp. 524–533). ACM Press. https://doi.org/10.1145/3375462.3375483

Williamson, G. (2015). Self-regulated learning: An overview of metacognition, motivation and behaviour. Journal of Initial Teacher Inquiry, 1, 25–27. http://dx.doi.org/10.26021/851

Wolters, C. A., Yu, S. L., & Pintrich, P. R. (1996). The relation between goal orientation and students’ motivational beliefs and self-regulated learning. Learning and Individual Differences, 8(3), 211–238. https://doi.org/10/bhggr3

Xu, K. M., Cunha-Harvey, A. R., King, R. B., de Koning, B. B., Paas, F., Baars, M., Zhang, J., & de Groot, R. (2023). A cross-cultural investigation on perseverance, self-regulated learning, motivation, and achievement. Compare: A Journal of Comparative and International Education, 53(3), 361–379. https://doi.org/10.1080/03057925.2021.1922270

Zell, E., & Alicke, M. D. (2010). Comparisons over time: Temporal trajectories, social comparison, and self-evaluation. European Journal of Social Psychology, 40(3), 375–382. https://doi.org/10.1002/ejsp.737

Zimmerman, B. J. (1995). Self-regulation involves more than metacognition: A social cognitive perspective. Educational Psychologist, 30(4), 217–221. https://doi.org/10.1207/s15326985ep3004_8

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183. https://doi.org/10.3102/0002831207312909

Zimmerman, B. J., & Schunk, D. H. (Eds.). (2001). Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed.). Routledge.




How to Cite

Fleur, D. S., Marshall, M., Pieters, M., Brouwer, N., Oomens, G., Konstantinidis, A., Winnips, K., Moes, S., van den Bos, W., Bredeweg, B., & van Vliet, E. A. (2023). IguideME: Supporting Self-Regulated Learning and Academic Achievement with Personalized Peer-Comparison Feedback in Higher Education. Journal of Learning Analytics, 10(2), 100-114. https://doi.org/10.18608/jla.2023.7853



Data and Tools Reports