Enhancement of personal concept map constructing for effective assessment

Li Yu Lee, Yu Shih Lin, Chih Ping Chu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Concept map model has been widely used in e-learning for various applications. However, in the past researches, there are few attentions paid on constructing the personal concept map for diagnosing learner's learning status. Actually, it is difficult to construct the individual concept maps to reflect the real knowledge structure by learners themselves. To cope with this problem, in our previous study, we proposed an approach employing the standard concept map from expert, correlative test-items structure and formulated questions to construct the personal concept map automatically [8]. But there were still some problems remained in [8]. In this study, we further propose different work to advance the mentioned problems. It not only modifies tests to be with more varieties, but also makes the proposed personal concept map constructing approach more completely and with effectiveness. The contribution of this study is to construct an enhanced personal concept map automatically according to the test result, to diagnose the learning barriers and to provide a suggestion of remedial learning paths as feedback for learners.

Original languageEnglish
Title of host publicationProceedings of IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2012
PagesW1A1-W1A7
DOIs
Publication statusPublished - 2012 Dec 28
Event1st IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2012 - Hong Kong, Hong Kong
Duration: 2012 Aug 202012 Aug 23

Publication series

NameProceedings of IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2012

Conference

Conference1st IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2012
Country/TerritoryHong Kong
CityHong Kong
Period12-08-2012-08-23

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Education

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