Authors: Benjamin Clément, Hélène Sauzéon, Didier Roy, Pierre-Yves Oudeyer

Published on: January 16, 2024

Impact Score: 8.38

Arxiv code: Arxiv:2402.01669

Summary

• What is new: The introduction of student choice in the ZPDES algorithm for intelligent tutoring systems to evaluate its impact on learning efficiency and motivation.
• Why this is important: Large class sizes limit personalized learning, and existing ITS models lack motivational assessment and student agency.
• What the research proposes: Incorporating choice dimensions orthogonal to exercise difficulty in the ZPDES algorithm to assess impacts on motivation and learning efficiency.
• Results: ZPDES with choice enhances learning performance and motivation, showing intrinsic motivation and learning effectiveness are linked.

Technical Details

Technological frameworks used: ZPDES algorithm, based on Learning Progress Hypothesis and multi-armed bandit techniques

Models used: nan

Data used: 265 7-8 years old children in a randomized control trial

Potential Impact

Educational technology companies, particularly those developing or utilizing intelligent tutoring systems

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