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Learning by Searching: A Learning Environment that Provides Searching and Analysis Facilities for Supporting Trend Analysis Activities

Chengjiu Yin, Han-Yu Sung, Gwo-Jen Hwang, Sachio Hirokawa, Hui-Chun Chu, Brendan Flanagan and Yoshiyuki Tabata
Journal of Educational Technology & Society
Vol. 16, No. 3 (July 2013), pp. 286-300
Stable URL: http://www.jstor.org/stable/jeductechsoci.16.3.286
Page Count: 15
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Learning by Searching: A Learning Environment that Provides Searching and Analysis Facilities for Supporting Trend Analysis Activities
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Abstract

ABSTRACT With the popularity of the Internet, online searching is becoming an important part of learning. In this paper, based on the “Learning by Searching” theory, a learning environment is developed, which includes a search engine to assist students in recognizing the progression of trends and keyword transitions for specific domains. To efficiently support research trend surveys, an automatic data accumulation and classification approach is proposed to construct the database excerpts instead of manual keyword registration or any other heuristic preprocesses. With an associative search module, the search engine dynamically searches for relevant words that are frequently used in the targeted academic field, and provides learners with effective visualizations to understand the trend transitions. An experiment has been conducted on a college information management course to show the effectiveness of the proposed approach. The experiment results show that the students who learned with the new approach had significantly better learning performance in terms of recognizing the trend transitions of the targeted issues than those who learned with conventional search engines.

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