Examining the Relationship Between the WTCAi System and Student Background Data in Modern Educational Assessment
DOI:
https://doi.org/10.24368/jates389Keywords:
pedagogical monitoring, evaluation, individual learning paths, validity, learner-centred knowledge transfer, development of monitoring and evaluation systems, WTCAi, item, generation gap, artificial intelligence, machine learningAbstract
The study presents the latest development results of the WTCAi (When The Child Asks with AI) system, focusing on the correlations between student background data and academic performance. Students' family background, learning habits, and performance during the research were analysed using machine learning methods. The results show that the artificial intelligence-based approach can significantly improve the efficiency and personalisation of educational assessment. The study discusses the results of the developed prediction models and their practical application possibilities.
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