Effects of concept map extraction and a test-based diagnostic environment on learning achievement and learners' perceptions.

• Autores: Yu-Shih Lin, Yi-Chun Chang, Keng-Hou Liew, Chih-Ping Chu
• Localización: British journal of educational technology, ISSN 0007-1013, Vol. 47, Nº. 4, 2016, págs. 649-664
• Idioma: inglés
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• Resumen

  • Computerised testing and diagnostics are critical challenges within an e-learning environment, where the learners can assess their learning performance through tests. However, a test result based on only a single score is insufficient information to provide a full picture of learning performance. In addition, because test results implicitly include information about the underlying subject concepts and their relationships to each other, this paper proposes a more effective method for analysing test results by providing a concept map ( CM) to facilitate learners' understanding of their learning performance. An innovative approach, not explored in previous studies, is proposed to automatically construct a personalised CM. A CM-smart extraction and explicit diagnosis ( CM-SEED) learning system has been developed to diagnose learning barriers and misconceptions and to supply relevant suggestions and guidance for remedial learning. This study examined 90 students from two classes at a university and assigned one class to be the experimental group and another class to be the control group. The results indicated that the students who used the CM-SEED learning system had superior perceptions regarding their learning; furthermore, they accomplished superior learning achievement that displayed statistical significance. Consequently, the study concluded that CM extraction in a test-based diagnostic environment can lead learners to enhanced learning performance. [ABSTRACT FROM AUTHOR]