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

Guadalupe Elizabeth Morales-Martinez, Ernesto Octavio Lopez-Ramirez, Claudia Castro-Campos, Maria Guadalupe Villarreal-Treviño, Claudia Jaquelina Gonzales-Trujillo

APA 6th edition
Morales-Martinez, G.E., Lopez-Ramirez, E.O., Castro-Campos, C., Villarreal-Treviño, M.G., & Gonzales-Trujillo, C.J. (2017). Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment. European Journal of Educational Research, 6(4), 455-465. doi:10.12973/eu-jer.6.4.455

Morales-Martinez G.E., Lopez-Ramirez E.O., Castro-Campos C., Villarreal-Treviño M.G., and Gonzales-Trujillo C.J. 2017 'Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment', European Journal of Educational Research , vol. 6, no. 4, pp. 455-465. Available from:

Chicago 16th edition
Morales-Martinez, Guadalupe Elizabeth , Lopez-Ramirez, Ernesto Octavio , Castro-Campos, Claudia , Villarreal-Treviño, Maria Guadalupe and Gonzales-Trujillo, Claudia Jaquelina . "Cognitive Analysis of Meaning and Acquired Mental Representations as an Alternative Measurement Method Technique to Innovate E-Assessment". (2017)European Journal of Educational Research 6, no. 4(2017): 455-465. doi:10.12973/eu-jer.6.4.455


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.

Keywords: E-assessment, learning, knowledge representation, connectionism, educational technology, innovation, neural nets.


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