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Fill Students' Knowledge Gap by Recommending Remedial Learning Materials

Published: 07 October 2020 Publication History

Abstract

Identifying and filling the knowledge gap is one solution to improve students' learning performance. Several challenges are involved, such as how to identify the gap and how to fill the gap. In this paper, we propose to identify students' knowledge gap at the early stage by tracking their in-class emotions, and fill the gap by recommending remedial learning materials on time. The framework and workflow have been described in details in this work.

References

[1]
Konstantin Bauman and Alexander Tuzhilin. 2018. Recommending remedial learning materials to students by filling their knowledge gaps. MIS Quarterly, Vol. 42, 1 (2018), 313--332.
[2]
Glenda Crosling, Margaret Heagney, Liz Thomas, et al. 2009. Improving student retention in higher education: Improving teaching and learning. Australian Universities' Review, The, Vol. 51, 2 (2009), 9.
[3]
Ivan Damjanov, Bruce A Fenderson, Mohammadreza Hojat, and Emanuel Rubin. 2005. Curricular reform may improve students' performance on externally administered comprehensive examinations. Croatian medical journal, Vol. 46, 3 (2005).
[4]
Alejandro Susillo Ridao and Yong Zheng. 2020. A Comparison of Tools and Libraries for In-Class Face Detection and Emotion Recognition. In Proceedings of the 21st Annual SIG Conference on Information Technology Education.

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  1. Fill Students' Knowledge Gap by Recommending Remedial Learning Materials

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    cover image ACM Conferences
    SIGITE '20: Proceedings of the 21st Annual Conference on Information Technology Education
    October 2020
    446 pages
    ISBN:9781450370455
    DOI:10.1145/3368308
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Published: 07 October 2020

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    Author Tags

    1. emotion recognition
    2. knowledge gap
    3. recommender systems

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