Challenge Balancing for a Kanji E-Tutoring System

Marysia Winkels, D.M. Roijers, Maarten van Someren, Emi Yamamoto, Richard Pronk, Edwin Odijk, Maarten de Jonge

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper, we investigate the potential of direct challenge balancing in e-tutoring, especially in domains where there are many skills to acquire. As a case study, we create an e-tutoring system for kanji. Our system estimates the perceived challenge level using both the correctness of the answers of the students and implicit feedback, and adapts accordingly. In order to make this estimation we train a classifier on labelled data collected via the same system. We show empirically that the perceived challenge can be estimated well using implicit feedback, and that the adaptive system based on challenge balancing is preferred over a system in which the student selects a difficulty setting, indicating that directchallenge balancing is a promising research direction for e-tutoring.
Original languageEnglish
Title of host publicationARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers
PublisherSpringer
Pages331-340
Number of pages10
ISBN (Print)9783030319779
Publication statusPublished - 2019
Event30th Benelux Conference on Artificial Intelligence (BNAIC 2018) - Den Bosch
Duration: 8 Nov 20189 Nov 2018
Conference number: 30th

Conference

Conference30th Benelux Conference on Artificial Intelligence (BNAIC 2018)
Abbreviated titleBNAIC 2018
CityDen Bosch
Period8/11/189/11/18

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Students
Feedback
Adaptive systems
Classifiers

Cite this

Winkels, M., Roijers, D. M., van Someren, M., Yamamoto, E., Pronk, R., Odijk, E., & de Jonge, M. (2019). Challenge Balancing for a Kanji E-Tutoring System. In ARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers (pp. 331-340). Springer.
Winkels, Marysia ; Roijers, D.M. ; van Someren, Maarten ; Yamamoto, Emi ; Pronk, Richard ; Odijk, Edwin ; de Jonge, Maarten. / Challenge Balancing for a Kanji E-Tutoring System. ARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers. Springer, 2019. pp. 331-340
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title = "Challenge Balancing for a Kanji E-Tutoring System",
abstract = "In this paper, we investigate the potential of direct challenge balancing in e-tutoring, especially in domains where there are many skills to acquire. As a case study, we create an e-tutoring system for kanji. Our system estimates the perceived challenge level using both the correctness of the answers of the students and implicit feedback, and adapts accordingly. In order to make this estimation we train a classifier on labelled data collected via the same system. We show empirically that the perceived challenge can be estimated well using implicit feedback, and that the adaptive system based on challenge balancing is preferred over a system in which the student selects a difficulty setting, indicating that directchallenge balancing is a promising research direction for e-tutoring.",
author = "Marysia Winkels and D.M. Roijers and {van Someren}, Maarten and Emi Yamamoto and Richard Pronk and Edwin Odijk and {de Jonge}, Maarten",
year = "2019",
language = "English",
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Winkels, M, Roijers, DM, van Someren, M, Yamamoto, E, Pronk, R, Odijk, E & de Jonge, M 2019, Challenge Balancing for a Kanji E-Tutoring System. in ARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers. Springer, pp. 331-340, 30th Benelux Conference on Artificial Intelligence (BNAIC 2018), Den Bosch, 8/11/18.

Challenge Balancing for a Kanji E-Tutoring System. / Winkels, Marysia; Roijers, D.M.; van Someren, Maarten; Yamamoto, Emi; Pronk, Richard; Odijk, Edwin; de Jonge, Maarten.

ARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers. Springer, 2019. p. 331-340.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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T1 - Challenge Balancing for a Kanji E-Tutoring System

AU - Winkels, Marysia

AU - Roijers, D.M.

AU - van Someren, Maarten

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AU - Pronk, Richard

AU - Odijk, Edwin

AU - de Jonge, Maarten

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AB - In this paper, we investigate the potential of direct challenge balancing in e-tutoring, especially in domains where there are many skills to acquire. As a case study, we create an e-tutoring system for kanji. Our system estimates the perceived challenge level using both the correctness of the answers of the students and implicit feedback, and adapts accordingly. In order to make this estimation we train a classifier on labelled data collected via the same system. We show empirically that the perceived challenge can be estimated well using implicit feedback, and that the adaptive system based on challenge balancing is preferred over a system in which the student selects a difficulty setting, indicating that directchallenge balancing is a promising research direction for e-tutoring.

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Winkels M, Roijers DM, van Someren M, Yamamoto E, Pronk R, Odijk E et al. Challenge Balancing for a Kanji E-Tutoring System. In ARTIFICIAL INTELLIGENCE - 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers. Springer. 2019. p. 331-340