How To Motivate Students Through mining Educational Data
-
2018-12-06 https://doi.org/10.14419/ijet.v7i4.32.23250 -
educational data mining, the learning theories, performance, motivating students -
Abstract
Despite having educational data mining as a new research area, it has already made contributions to the learning theories and their teaching practices. The aims of this article are to present a way of improving both the student and the teacher performance, and to empower educational institutions through exploring data and through examining them with the purpose of motivating students in different aspects of their performance.
Â
 -
References
[1] IEDMS. 2009. International Educational Data Mining Society. Retrieved February 22, 2018 from http://www.educationaldatamining.org 00000
[2] Heiner, C., N. Heffernan and T. Barners. July, 2007. Educational Data Mining. Supplementary Proceedings of the 13th International Conference of Artificial Intelligence in Education. USA: Marina del Rey, CA.0000
[3] Lai, M. K. and K. Schildkamp. 2013. Data-based Decision Making: An Overview. In K. Schildkamp, Lai M.K. and L. Earl (Eds.). Data-based decision making in education: Challenges and opportunities. Dordrecht: Springer.
[4] Arcia, G., K. Macdonald, H. Patrinos and E. Porta. 2011. School autonomy and accountability.System Assessment and Benchmarking for Education Results (SABER)
[5] Romero, C. and S. Ventura. November 2010. Educational Data Mining: A Review of the State of the Art. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS, 40 (6), pp. 601-618.
[6] AlaouiHarouni, H., E. Hachem and C. Ziti. 2O16. Data Mining for the Service of Intelligent Tutoring System. The International Journal of Multi-disciplinary Sciences, 2 (2), pp. 61-65.000
[7] Brusilovsky, P. 2001. Adaptive hypermedia. Journal of user modeling and user adapted interaction. Pages 87 - 110 Kluwer AcademicPublishersHingham, MA, USA.
[8] DEROUICH, A. 2011. Conception et réalisation d’un hypermédia adaptatif dédié à l’enseignement à distance. Sidi Mohammed Ben Abdellah University, Fez.
[9] Felder, RM. 1993. Reaching the Second Tier: Learning and Teaching Styles in College Science Education, J. College Science Teaching, 23(5), pp.286.290.
[10] Deci, E.L. and R. M. RYAN. 1985. Intrinsic motivation and self-determination in human behaviour. New York: Plenum.
[11] Vallerand, R.J., L.G. Pelletier and R.M Ryan. 1991. Motivation and education: the self-determination perspective. The Educational Psychologist , 26, 325-346.
[12] Ryan, R. M. and E.L. Deci. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and wellbeing. American Psychologist, 55, p. 68-78.
[13] Ryan R.M., S.C. Rigby and A. Przybylski. 2006. The Motivational Pull of Video Games: A Self-Determination Theory Approach. Journal of Motivation and Emotion, 30, p. 347-363.
[14] Cohn, J.F. and G.S. Katz. 1998. Bimodal Expression of Emotion by Face and Voice, Proceedings of the sixth ACM international conference on Multimedia : Face/gesture recognition and their applications, pp.44.
[15] Baker, R.S.J.d. and G. Siemens. 2013. Educational Data Mining and Learning Analytics.
[16] Romero, C. and S. Ventura. 2007. Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications, 33 (1).135–146.0000
[17] Ingram, A. 1999. Using web server logs in evaluating instructional web sites. Journal of EducationalTechnologySystems 28(2), pp. 137–157.0000
-
Downloads
-
How to Cite
Hachem Alaoui Haroun, M., Hachem, E.-K., Ziti, C., & Bassiri, M. (2018). How To Motivate Students Through mining Educational Data. International Journal of Engineering & Technology, 7(4.32), 75-78. https://doi.org/10.14419/ijet.v7i4.32.23250Received date: 2018-12-06
Accepted date: 2018-12-06
Published date: 2018-12-06