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Twitter news-in-education platform for social, collaborative, and flipped learning

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Abstract

NIE (newspaper in education), which is the study utilizing newspaper-based educational resources in the classroom, has been pursued for a long time. Traditional NIE allows only one-way interaction and available media are limited. In addition, it has difficulty in capturing the latest “hot” issues or recognizing public opinions. In this paper, we propose a platform called TNIE (Twitter news in education) that utilizes Twitter in NIE. TNIE has many advantages compared to traditional NIE: (1) it classifies the latest news into various topics, (2) the classified news content can be browsed effectively via a hierarchical visualization scheme, and (3) effective discussion or debate groups can be easily formed based on the learners’ news selection. To evaluate the performance of our scheme, we implemented a prototype system and performed several experiments. According to the results, our news classification scheme achieved an 87.8 % F-measure on average, which is superior to the 78.94 % of previous studies. We also had volunteers use our prototype system and evaluate its main functions, e.g., news visualization, classification, learner clustering, and collaborative learning. We report some of these evaluation results.

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Acknowledgments

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. 2.150379.01, High Performance Big Data Analytics Platform Performance Acceleration Technologies Development).

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Correspondence to Eenjun Hwang.

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This paper is an extended version of our conference paper [30].

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Kim, Y., Hwang, E. & Rho, S. Twitter news-in-education platform for social, collaborative, and flipped learning. J Supercomput 74, 3564–3582 (2018). https://doi.org/10.1007/s11227-016-1776-x

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