Abstract
A number of methodologies (Big Five Factors and Five Factor Model, intelligence quotient tests, self-assessment) and strategies for web-based formative assessment are used in an effort to predict a student’s academic motivation, achievements and performance. These methodologies, biometric voice analysis technologies and 13 years of authors’ experience in distance learning were used in development of the Biometric and Intelligent Student Progress Assessment System for psychological assessment of student progress. Also the BISPA system was developed in consideration of worldwide research results involving the interrelation between a person’s knowledge, self-assessment and voice stress along with instances of available decision support, recommender and intelligent tutoring systems.
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Kaklauskas, A. et al. (2013). Biometric and Intelligent Student Progress Assessment System. In: Nguyen, N., Trawiński, B., Katarzyniak, R., Jo, GS. (eds) Advanced Methods for Computational Collective Intelligence. Studies in Computational Intelligence, vol 457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34300-1_6
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DOI: https://doi.org/10.1007/978-3-642-34300-1_6
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