Effective Online Discussion Data for Teachers Reflective Thinking Using Feature base Model
Abstract
In this paper analysis automatic coding method by integrating the inductive content analysis and text classification techniques. In existing model acquire the reflective thinking categories by conducting an inductive content analysis and base our text classification algorithm on the categories, so we augment the manual method of coding. We apply the trained classification model to a large-scale and unexplored online discussion data set, so we can have a comprehensive understanding of teachers reflection. This paper also provides six types of visualizations of the text classification results: the visualization of teachers reflection level and the visualization of teachers? reflection evolution. By using the categories gained from inductive content analysis to create a radar map, we visually represent teachers? reflection level after obtain the results of text classification future classification model.
Keywords Data Mining, Teacher Reflection Model, TF-IDF Classification, Visualization Learning.
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