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Learning Analytics Dashboard for Motivation and Performance

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 12149)


Deploying Learning Analytics that significantly improve learning outcomes remains a challenge. Motivation has been found to be related to academic achievement and is argued to play an essential role in efficient learning. We developed a Learning Analytics dashboard and designed an intervention that relies on goal orientation and social comparison. Subjects can see a prediction of their final grade in a course as well as how they perform in comparison to classmates with similar goal grades. Those with access to the dashboard ended up more motivated than those without access, outperformed their peers as the course progressed and achieved higher final grades. Our results indicate that learner-oriented dashboards are technically feasible and may have tangible benefits for learners.


  • Learning Analytics
  • Motivation
  • Social comparison
  • Goal orientation

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  • DOI: 10.1007/978-3-030-49663-0_51
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  1. Brouwer, N., Bredeweg, B., Latour, S., Berg, A., van der Huizen, G.: Learning analytics pilot with Coach2 - searching for effective mirroring. In: Verbert, K., Sharples, M., Klobučar, T. (eds.) EC-TEL 2016. LNCS, vol. 9891, pp. 363–369. Springer, Cham (2016).

    CrossRef  Google Scholar 

  2. Davis, D., Jivet, I., Kizilcec, R.F., Chen, G., Hauff, C., Houben, G.-J.: Follow the successful crowd: raising MOOC completion rates through social comparison at scale. In: Proceedings of the Seventh International Learning Analytics and Knowledge Conference, pp. 454–463. ACM (2017).

  3. Bodily, R., Verbert, K.: Trends and issues in student-facing learning analytics reporting systems research. In: Proceedings of the Seventh International Learning Analytics and Knowledge Conference, pp. 309–318. ACM (2017).

  4. Gašević, D., Dawson, S., Siemens, G.: Let’s not forget: learning analytics are about learning. TechTrends 59, 64–71 (2015).

    CrossRef  Google Scholar 

  5. Schunk, D.H., Zimmerman, B.J.: Motivation and Self-Regulated Learning: Theory, Research, and Applications. Routledge, New York (2012)

    CrossRef  Google Scholar 

  6. Singh, K., Granville, M., Dika, S.: Mathematics and science achievement: effects of motivation, interest, and academic engagement. J. Educ. Res. 95, 323–332 (2002).

    CrossRef  Google Scholar 

  7. Schunk, D.H., Zimmerman, B.J.: Motivation an essential dimension of self-regulated learning. In: Motivation and Self-Regulated Learning, pp. 13–42. Routledge (2012)

    Google Scholar 

  8. Lee, L.H.: Goal orientation, goal setting, and academic performance in college students: An integrated model of achievement motivation in school settings (1998)

    Google Scholar 

  9. Schokker, M.C., et al.: The impact of social comparison information on motivation in patients with diabetes as a function of regulatory focus and self-efficacy. Health Psychol. 29, 438–445 (2010).

    CrossRef  Google Scholar 

  10. Festinger, L.: A theory of social comparison processes. Hum. Relat. 7, 117–140 (1954)

    CrossRef  Google Scholar 

  11. Gerber, J.P., Wheeler, L., Suls, J.: A social comparison theory meta-analysis 60+ years on. Psychol. Bull. 144, 177 (2018).

    CrossRef  Google Scholar 

  12. Locke, E.A.: Motivation through conscious goal setting. Appl. Prev. Psychol. 5, 117–124 (1996).

    CrossRef  Google Scholar 

  13. Dantzig, T.: Number, the language of science. Revised and augmented. J. Nerv. Ment. Dis. 92, 546 (1940)

    CrossRef  Google Scholar 

  14. Tipping, M.E.: Sparse Bayesian learning and the relevance vector machine. J. Mach. Learn. Res. 1, 211–244 (2001)

    MathSciNet  MATH  Google Scholar 

  15. Meier, Y., Xu, J., Atan, O., van der Schaar, M.: Predicting grades. IEEE Trans. Signal Process. 64, 959–972 (2016).

    CrossRef  MathSciNet  MATH  Google Scholar 

  16. Duncan, T.G., McKeachie, W.J.: The making of the motivated strategies for learning questionnaire. Educ. Psychol. 40, 117–128 (2005).

    CrossRef  Google Scholar 

  17. Harrison, G.M., Vallin, L.M.: Evaluating the metacognitive awareness inventory using empirical factor-structure evidence. Metacognition Learn. 13, 15–38 (2018).

    CrossRef  Google Scholar 

  18. Bates, D., Mächler, M., Bolker, B., Walker, S.: Fitting linear mixed-effects models using lme4. ArXiv Prepr. ArXiv14065823 (2014)

    Google Scholar 

  19. Berlyne, D.E., Craw, M.A., Salapatek, P.H., Lewis, J.L.: Novelty, complexity, incongruity, extrinsic motivation, and the GSR. J. Exp. Psychol. 66, 560 (1963)

    CrossRef  Google Scholar 

  20. Mutsuddi, A.U., Connelly, K.: Text messages for encouraging physical activity are they effective after the novelty effect wears off? In: 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, pp. 33–40 (2012).

  21. Jeno, L.M., Vandvik, V., Eliassen, S., Grytnes, J.-A.: Testing the novelty effect of an m-learning tool on internalization and achievement: a self-determination theory approach. Comput. Educ. 128, 398–413 (2019).

    CrossRef  Google Scholar 

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Correspondence to Damien S. Fleur .

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Fleur, D.S., van den Bos, W., Bredeweg, B. (2020). Learning Analytics Dashboard for Motivation and Performance. In: Kumar, V., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science(), vol 12149. Springer, Cham.

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