A Tag-Based Approach for Learning Ergonomic Concepts

被引:2
|
作者
Tsai, Li Chen [1 ]
Tang, Kuo Hao [2 ]
Hwang, Sheue Ling [1 ]
机构
[1] Natl Tsing Hua Univ, Dept Ind Engn & Engn Management, Hsinchu, Taiwan
[2] Feng Chia Univ, Dept Ind Engn & Syst Management, Taichung 40724, Taiwan
关键词
Web learning; Keyword-based tag; Knowledge acquirement; Conceptualization; Expert; KNOWLEDGE; EDUCATION; TECHNOLOGY; ANNOTATION; SEARCH;
D O I
10.1002/hfm.20552
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The rapid advance of web technologies has enabled people to get a tremendous amount of information by clicking browser hyperlinks or typing query-terms (keywords) into search engines. Users are no longer limited to specialized databases; an isolated search can lead to exploration, learning, and sharing. Collaborative information networks, such as Delicious, CiteULike, and others, can support information searching and self-learning. In the context of ergonomics, we hypothesized that tags chosen by experts would facilitate knowledge acquisition, understanding, and self-learning. These tags act as "learning cues"; they are intrinsic to the subject matter but extrinsic to the experts who apply them. Before the main experiment, a prior test collected tags applied to articles by experts and novices. The main experiment compared the effects of expert tagging with the effects of novice tagging on the self-learning behavior of novices. It was intended to discover whether tag-mediated conceptualization could help novices spontaneously formalize original ergonomics concepts. The result revealed that tags chosen by experts reflected better understanding of the content, and that expert tags significantly helped self-learning of the structure of the ergonomic knowledge. The present article presents the results and discusses the implications of this research. (C) 2014 Wiley Periodicals, Inc.
引用
收藏
页码:574 / 584
页数:11
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