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Title:
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A VISUALIZATION SYSTEM FOR PREDICTING LEARNING ACTIVITIES USING STATE TRANSITION GRAPHS |
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Author(s):
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Fumiya Okubo, Atsushi Shimada, Yuta Taniguchi and Shinichi Konomi |
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ISBN:
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978-989-8533-68-5 |
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Editors:
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Demetrios G. Sampson, J. Michael Spector, Dirk Ifenthaler and Pedro Isaías |
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Year:
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2017 |
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Edition:
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Single |
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Keywords:
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Learning log, predication of learning activity, state transition graph |
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Type:
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Full Paper |
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First Page:
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173 |
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Last Page:
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180 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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In this paper, we present a system for visualizing learning logs of a course in progress together with predictions of learning activities of the following week and the final grades of students by state transition graphs. Data are collected from 236 students attending the course in progress and from 209 students attending the past course for prediction. From these data, the system constructs a state transition graph, where the prediction is based on the Markov property. We verify the performance of predictions by experiments in which the accuracy of prediction using the data of the course in progress and the one by 5-fold cross validation. |
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