ES-KT-24: A Multimodal Knowledge Tracing Benchmark Dataset with Educational Game Playing Video and Synthetic Text Generation

ES-KT-24 is a multimodal Knowledge Tracing benchmark dataset derived from educational game-playing videos covering K-12 Mathematics, English, Indonesian, and Malaysian subjects, containing 15,032 users and 7.7M interactions with synthetically generated question texts and game logs. The paper benchmarks deep learning-based KT models against language model-based approaches to predict student performance in game-based learning environments.

This paper introduces ES-KT-24, a novel multimodal Knowledge Tracing (KT) dataset for intelligent tutoring systems in educational game contexts. Although KT is crucial in adaptive learning, existing datasets often lack game-based and multimodal elements. ES-KT-24 addresses these limitations by incorporating educational game-playing videos, synthetically generated question text, and detailed game logs. The dataset covers Mathematics, English, Indonesian, and Malaysian subjects, emphasizing divers

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