Abstract
In this paper, we propose an efficient English vocabulary learning system using repetitive learning and the rate-matching rule. The proposed system provides a learning method based on the user’s learning skill. By using the proposed system, users can solve exam-style questions wherever and whenever they choose. Efficient repetition learning is provided by using repetition periods based on the forgetting curve for long-term memory. The answered questions are then evaluated to update the user’s learning skill and the question difficulty. Due to this adaptive difficulty adjustment, users almost always receive questions that are appropriate for their skill level. If users answer questions correctly or learn more than the defined amount, then the proposed system provides them with encouraging feedback imagery. This is very similar to being rewarded for an achievable challenge in a game, and it can encourage users to study consistently.
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Acknowledgments
This work was supported by the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government (MEST) (No. 2011-0012214).
This work was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (No.10047039, Development of the realtime inspection SW and reverse engineering SW based on multiple 2D x-ray images and CT images).
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Yang, J., Oh, K., Youm, K. (2016). English Vocabulary Learning System Based on Repetitive Learning and Rate-Matching Rule. In: De Gloria, A., Veltkamp, R. (eds) Games and Learning Alliance. GALA 2015. Lecture Notes in Computer Science(), vol 9599. Springer, Cham. https://doi.org/10.1007/978-3-319-40216-1_20
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DOI: https://doi.org/10.1007/978-3-319-40216-1_20
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