Using collaborative annotating and data mining on formative assessments to enhance learning efficiency

被引:12
作者
Lin, Jian-Wei [1 ]
Lai, Yuan-Cheng [2 ]
机构
[1] Ching Yun Univ, Dept Int Business, Taoyuan, Taiwan
[2] Natl Taiwan Univ Sci & Technol, Dept Informat Management, Taipei, Taiwan
关键词
formative assessment; data mining; collaborative annotating; e-Learning; FUZZY RULES; FEEDBACK; DIAGNOSIS; KNOWLEDGE; INSTRUCTION; SYSTEMS;
D O I
10.1002/cae.20561
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (c) 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:364-374, 2014; View this article online at ; DOI
引用
收藏
页码:364 / 374
页数:11
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