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 language | English |
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Title of host publication | ARTIFICIAL INTELLIGENCE |
Subtitle of host publication | 30th Benelux Conference, BNAIC 2018, Den Bosch November 8-9 2018, Revised Selected Papers |
Editors | Martin Atzmueller, Wouter Duivesteijn |
Publisher | Springer |
Pages | 331-340 |
Number of pages | 10 |
ISBN (Electronic) | 9783030319786 |
ISBN (Print) | 9783030319779 |
Publication status | Published - 2019 |
Event | 30th Benelux Conference on Artificial Intelligence (BNAIC 2018) - Den Bosch Duration: 8 Nov 2018 → 9 Nov 2018 Conference number: 30th |
Publication series
Name | Belgian/Netherlands Artificial Intelligence Conference |
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ISSN (Print) | 1568-7805 |
Conference
Conference | 30th Benelux Conference on Artificial Intelligence (BNAIC 2018) |
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Abbreviated title | BNAIC 2018 |
City | Den Bosch |
Period | 8/11/18 → 9/11/18 |
Keywords
- Challenge Balancing
- E-Tutoring
- Kanji
- Machine Learning