JSAI2023

Presentation information

General Session

General Session » GS-10 AI application

[1N4-GS-10] AI application

Tue. Jun 6, 2023 3:00 PM - 4:40 PM Room N (D2)

座長:曽我 真人(和歌山大学) [オンライン]

3:00 PM - 3:20 PM

[1N4-GS-10-01] Monotonic Variational AutoEncoder based Individually Optimized Problem Recommender System

〇Takashi Hattori1, Hiroshi Sawada1, Sanae Fujita1, Tessei Kobayashi1, Koji Kamei1, Futoshi Naya1 (1. NTT)

Keywords:Problem recommendation, Variational AutoEncoder, Learning support

We propose a novel problem recommender system that can suggest moderately challenging problems to learners. By training a Variational AutoEncoder to reconstruct problem-answer data with a small number of latent variables, we can predict the likelihood of a learner's ability to correctly solve unanswered problems. Experimental results showed that the system's predictions were accurate for learners who had solved a sufficient number of problems, even for a wide variety of problems, and that the system was able to recommend problems of moderate difficulty for individual learners.

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