Semi-Automatic Concept Map Generation Approach of Web-Based Kit-Build Concept Map Authoring Tool

Authors

DOI:

https://doi.org/10.3991/ijim.v15i08.20489

Keywords:

concept map, Concept Map Mining, EFL, Kit-Build

Abstract


Apart from contributing to students’ learning outcomes, learning activities with digital concept maps were useful, fun, and engaging. Kit-Build concept map is a learning framework that incorporated concept map recomposition as its essential activity. It has been used to learn English as a Foreign Language (EFL) reading comprehension. Students learn through recomposing digital concept maps from a set of teacher’s concept map components; hence, the teacher’s concept map is essential in Kit-Build. A teacher’s concept map should reflect the learning context and strategy, the teacher’s purpose and intention, students’ understanding level, and focus questions. However, automatic-generated concept maps with Concept Map Mining (CMM) can only produce general concept maps that are not fit and difficult to correspond to said reasons. As teacher’s concept maps are essential in learning with Kit-Build, improving teachers’ productivity in composing concept maps of a particular learning material becomes necessary. This study proposed a semi-automatic concept map generation approach of EFL reading comprehension texts with CMM to assist teachers composed their concept maps. The proposed concept map generation approach was integrated into the current Kit-Build concept map authoring tool as an authoring support feature. The accuracy of the support feature in generating concept map components is presented in this research. The result suggested that the proposed authoring support tool is better used to refine a concept map.

Author Biographies

Aryo Pinandito, Hiroshima University

Aryo Pinandito is a lecturer of Information System Department and a member of Mobile, Game, and Multimedia Research Group at Computer Science Faculty, Universitas Brawijaya, Indonesia. He is currently pursuing his doctoral degree from Learning Engineering Laboratory, Information Engineering Department, Graduate School of Engineering, Hiroshima University, Japan. Recently, he has been granted an international award as the Best Poster Presentation Award of ICCE2020.

Didik Dwi Prasetya, Hiroshima University

Didik Dwi Prasetya is with the Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Malang, Indonesia. He is currently a doctoral student of Information Engineering Department, Graduate School of Engineering, Hiroshima University, Japan.

Yusuke Hayashi, Hiroshima University

Yusuke Hayashi is an associate professor of the Graduate School of Engineering at Hiroshima University since 2012. He has been engaged in research on knowledge modeling, ontological engineering, and learning engineering. He has received international awards as the Best Paper Award of ICCE2006 and the Best Technical Design Paper Award of ICCE2015.

Tsukasa Hirashima, Hiroshima University

Tsukasa Hirashima has been a professor of the Graduate School, Department of Information Engineering, Hiroshima University since 2004. Learning Engineering is his major research field. He has received international awards as the Outstanding Paper Award of EDMEDIA95, the Best Paper Award of ICCE2001 & 2002, Honorable Mention Award of AIED2009, APSCE Distinguished Researcher Award in 2009, and the ICCE2015 Best Technical Design Paper Award.

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Published

2021-04-23

How to Cite

Pinandito, A., Prasetya, D. D., Hayashi, Y., & Hirashima, T. (2021). Semi-Automatic Concept Map Generation Approach of Web-Based Kit-Build Concept Map Authoring Tool. International Journal of Interactive Mobile Technologies (iJIM), 15(08), pp. 50–70. https://doi.org/10.3991/ijim.v15i08.20489

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Section

Papers