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Using collaborative annotating and data mining on formative assessments to enhance learning efficiency
Author(s) -
Lin JianWei,
Lai YuanCheng
Publication year - 2014
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20561
Subject(s) - formative assessment , summative assessment , computer science , annotation , world wide web , collaborative learning , artificial intelligence , knowledge management , mathematics education , mathematics
This research applies the techniques of collaborative annotating and data mining into formative assessments and further develops an annotation‐sharing and intelligent formative assessment (ASIFA) system as an auxiliary Web learning tool. The collaborative annotating technique is based on collaborative annotations made by peers while the data mining technique is used to identify the learning bottlenecks suffered by most students on a formative assessment. The ASIFA system combines these two techniques, deemed as scaffolding learning, to furnish students with adequate annotations to clarify their confused concepts on formative assessments and to further improve their learning achievements on summative assessments. Finally, some experiments are conducted in order to evaluate the effectiveness of the proposed system and investigate the effects of the students' behaviors of inputting and reviewing annotations on learning achievements. © 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:364–374, 2014; View this article online at wileyonlinelibrary.com/journal/cae ; DOI 10.1002/cae.20561