A New Approach for Constructing the Concept Map

Autor/inn/en	Tseng, Shian-Shyong; Sue, Pei-Chi; Su, Jun-Ming; Weng, Jui-Feng; Tsai, Wen-Nung
Titel	A New Approach for Constructing the Concept Map
Quelle	In: Computers & Education, 49 (2007) 3, S.691-707 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0360-1315
DOI	10.1016/j.compedu.2005.11.020
Schlagwörter	Concept Mapping; Educational Technology; Virtual Classrooms; Junior High Schools; Computer Software; Teaching Methods; Individualized Instruction; Student Records; Data Analysis; Computer Assisted Testing; Heuristics; Pilot Projects; Adaptive Testing; Theories + Suchen Sie Ihr Suchwort? Concept Map; Unterrichtsmedien; Sekundarstufe I; Teaching method; Lehrmethode; Unterrichtsmethode; Individualisierender Unterricht; Schülerakte; Auswertung; Heuristik; Pilot project; Modellversuch; Pilotprojekt; Theory; Theorie
Abstract	In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners' historical testing records. Phase 1 is used to preprocess the testing records; i.e., transform the numeric grade data, refine the testing records, and mine the association rules from input data. Phase 2 is used to transform the mined association rules into prerequisite relationships among learning concepts for creating the concept map. Therefore, in Phase 1, we apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic data, apply Education Theory to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also discussed. Moreover, we also develop a prototype system of TP-CMC and then use the real testing records of students in junior high school to evaluate the results. The experimental results show that our proposed approach is workable. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10