Towards Adaptive Social Comparison for Education

Publication date

2020-08-21

Authors

Sosnovsky, S.A.ISNI 0000000352729779
Fang, QixiangORCID 0000-0003-2689-6653ISNI 0000000493063739
de Vries, Ben
Luehof, Sven
Wiegant, F.A.C.ISNI 000000036830621X

Editors

Alario-Hoyos, Carlos
Rodríguez-Triana, María Jesús
Scheffel, Maren
Arnedillo-Sánchez, Inmaculada
Dennerlein, Sebastian Maximilian

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

Informing students about their progress in comparison to their peers has been widely used in educational research as a strong motivational factor, effective gamification technique and means for adaptive guidance to learning material. A typical social comparison interface helps students weight their individual levels against the average levels of other students. However, such uniform approach may not be effective for every category of students and every learning situation. Underachieving students might find the displayed social goal impossible, while overachieving students might decide that the learning goal has been attained and stop investing time and efforts. An alternative approach is an adaptive social comparison strategy that chooses different levels of the social goal for different categories of students. This paper presents one of the first steps towards developing such a strategy.

Keywords

Social comparison, Learning analytics, Taverne

Citation

Sosnovsky, S A, Fang, Q, de Vries, B, Luehof, S & Wiegant, F A C 2020, Towards Adaptive Social Comparison for Education. in C Alario-Hoyos, M J Rodríguez-Triana, M Scheffel, I Arnedillo-Sánchez & S M Dennerlein (eds), Addressing Global Challenges and Quality Education : 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings. 1 edn, Lecture Notes in Computer Science, vol. 12315, Springer, Cham, pp. 421-426. https://doi.org/10.1007/978-3-030-57717-9_38