Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment

Guadalupe Elizabeth Morales-Martinez, Claudia Jaquelina Gonzalez

Research output: Contribution to journalArticle

Abstract

Empirical directions to innovate e-assessments and to support the theoretical development of e-learning are discussed by presenting a new learning assessment system based on cognitive technology. Specifically, this system encompassing trained neural nets that can discriminate between students who successfully integrated new knowledge course content from students who did not successfully integrate this new knowledge (either because they tried short-term retention or did not acquire new knowledge). This neural network discrimination capacity is based on the idea that once a student has integrated new knowledge into long-term memory, this knowledge will be detected by computer-implemented semantic priming studies (before and after a course) containing schemata-related words from course content (which are obtained using a natural semantic network technique). The research results demonstrate the possibility of innovating e-assessments by implementing mutually constrained responsive and constructive cognitive techniques to evaluate online knowledge acquisition.
Original languageEnglish
Pages (from-to)455-465
Number of pages11
JournalEuropean Journal of Educational Research
Volume6
Issue number4
DOIs
Publication statusPublished - 23 Oct 2017

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measurement method
knowledge
semantics
student
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neural network
electronic learning
discrimination
learning

Cite this

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Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment. / Morales-Martinez, Guadalupe Elizabeth; Gonzalez, Claudia Jaquelina.

In: European Journal of Educational Research, Vol. 6, No. 4, 23.10.2017, p. 455-465.

Research output: Contribution to journalArticle

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