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ERIC Number: EJ1090919
Record Type: Journal
Publication Date: 2016-Mar
Pages: 23
Abstractor: As Provided
Reference Count: 47
ISSN: ISSN-0735-6331
Identifying Engineering Students' English Sentence Reading Comprehension Errors: Applying a Data Mining Technique
Tsai, Yea-Ru; Ouyang, Chen-Sen; Chang, Yukon
Journal of Educational Computing Research, v54 n1 p62-84 Mar 2016
The purpose of this study is to propose a diagnostic approach to identify engineering students' English reading comprehension errors. Student data were collected during the process of reading texts of English for science and technology on a web-based cumulative sentence analysis system. For the analysis, the association-rule, data mining technique was applied to mine students' reading errors. Specific association rules of reading errors were identified and distinctive patterns of error production have been recognized among different groups of students. This article addresses the issue of English reading difficulty frequently found among engineering students and discovered possible tendencies of student reading errors. By using the techniques in this article to identify students' reading problems, instructors will be able to construct learning materials for adaptive learning, and thus reduce the cost of teaching and facilitate students' learning outcome. Pedagogical implications were provided based on the results of the study.
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Taiwan