Learning Support by Novel Modality Process Analysis of Educational Big Data

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Based on the analysis of pen strokes conducted in the first year of this project, we focused on trying to identify possible problems that students were facing by having them self-explain the knowledge and skills using in the process of answering quiz questions. Students reviewed their pen stroke answers and self-explained at appropriate intervals, which generated annotated time series data of the answering process. This data was then analyzed to using NLP methods to generate sample self-explanations that contained the required knowledge components to solve the quiz item. The results were disseminated as an international conference paper. A self-explanation feedback and recommender system has been developed and implemented with results currently under analysis.