Towards Adaptive Social Comparison for Education

S.A. Sosnovsky; Q. Fang; Ben de Vries; Sven Luehof; F.A.C. Wiegant

doi:10.1007/978-3-030-57717-9_38

Towards Adaptive Social Comparison for Education

S.A. Sosnovsky^*, Q. Fang, Ben de Vries, Sven Luehof, F.A.C. Wiegant

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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.

Original language	English
Title of host publication	Addressing Global Challenges and Quality Education
Subtitle of host publication	15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings
Editors	Carlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Inmaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein
Place of Publication	Cham
Publisher	Springer
Pages	421-426
Edition	1
ISBN (Electronic)	978-3-030-57717-9
ISBN (Print)	978-3-030-57716-2
DOIs	https://doi.org/10.1007/978-3-030-57717-9_38
Publication status	Published - 21 Aug 2020

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	12315
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Keywords

Social comparison
Learning analytics

Access to Document

10.1007/978-3-030-57717-9_38

Sosnovsky2020_Chapter_TowardsAdaptiveSocialComparisoFinal published version, 629 KBLicence: Taverne

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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 ed., pp. 421-426). (Lecture Notes in Computer Science; Vol. 12315). Springer. https://doi.org/10.1007/978-3-030-57717-9_38

Sosnovsky, S.A. ; Fang, Q. ; de Vries, Ben et al. / Towards Adaptive Social Comparison for Education. Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings. editor / Carlos Alario-Hoyos ; María Jesús Rodríguez-Triana ; Maren Scheffel ; Inmaculada Arnedillo-Sánchez ; Sebastian Maximilian Dennerlein. 1. ed. Cham : Springer, 2020. pp. 421-426 (Lecture Notes in Computer Science).

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title = "Towards Adaptive Social Comparison for Education",

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",

author = "S.A. Sosnovsky and Q. Fang and {de Vries}, Ben and Sven Luehof and F.A.C. Wiegant",

year = "2020",

month = aug,

day = "21",

doi = "10.1007/978-3-030-57717-9_38",

language = "English",

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series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "421--426",

editor = "Alario-Hoyos, {Carlos } and Rodr{\'i}guez-Triana, {Mar{\'i}a Jes{\'u}s } and Scheffel, {Maren } and Arnedillo-S{\'a}nchez, {Inmaculada } and Dennerlein, {Sebastian Maximilian }",

booktitle = "Addressing Global Challenges and Quality Education",

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Sosnovsky, SA , Fang, Q, de Vries, B, Luehof, S & Wiegant, FAC 2020, Towards Adaptive Social Comparison for Education. in C Alario-Hoyos, MJ Rodríguez-Triana, M Scheffel, I Arnedillo-Sánchez & SM 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

Towards Adaptive Social Comparison for Education. / Sosnovsky, S.A.; Fang, Q.; de Vries, Ben et al.
Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings. ed. / Carlos Alario-Hoyos; María Jesús Rodríguez-Triana; Maren Scheffel; Inmaculada Arnedillo-Sánchez; Sebastian Maximilian Dennerlein. 1. ed. Cham: Springer, 2020. p. 421-426 (Lecture Notes in Computer Science; Vol. 12315).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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PY - 2020/8/21

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N2 - 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.

AB - 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.

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Sosnovsky SA , Fang Q, de Vries B, Luehof S, Wiegant FAC. Towards Adaptive Social Comparison for Education. In Alario-Hoyos C, Rodríguez-Triana MJ, Scheffel M, Arnedillo-Sánchez I, Dennerlein SM, editors, Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings. 1 ed. Cham: Springer. 2020. p. 421-426. (Lecture Notes in Computer Science). doi: 10.1007/978-3-030-57717-9_38

Towards Adaptive Social Comparison for Education

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