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Analysis of Free Description Data in an English Class Using Text Mining
The purpose of this paper is to investigate students’ reactions to re-presented TED conference presentations. A text mining method was used to analyze the data for this research. Text mining is a way to discover knowledge from text data. It is widely used not only in medicine and finance, but also in the humanities. Free software that allows quantitative analysis of free description responses is available.
In this study, the text data that were collected from the students in an English classroom were analyzed with the “KH Corder” software, which allows processing of the data, calculation of word frequency, extraction of colloquial expressions, and visualization of the data. As a result, the frequencies of particular words such as “time,” “remember,” “content,” and “difficult” were high. This result indicates that the students did not set aside enough time to prepare for the presentation, taking more time for their own research activity than for studying English, and that they had difficulty understanding and keeping up with what the speaker said in a presentation. This means that clear guidance on how to use and learn materials should be provided to students learning languages.
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