Improving Student’s Cognitive Performance during the Pandemic through a Machine Learning-Based Virtual Museum

Abstract

This study presents the investigation of the innovative virtual application developed for cultural education through museum collections. It’s designed as an innovative virtual museum model for learning media containing various contents. Furthermore, it integrates machine learning to predict student interests which are expected to be effective in improving cognitive performance. The conceptual model design is continued with the development of an innovative virtual museum application tested on students, and the effectiveness was evaluated by taking a sample of N1 = N2= 32 participants in experimental and control group. Meanwhile, the pre-test and post-test were conducted to measure the user’s cognitive performance before and after using the innovative virtual museum application. The experimental group results show that the proposed application strongly affects students’ cognitive performance improvement in cultural education. The effect size value is 1.396, where the average score of post-test = 57.946 and the standard deviation = 21.421. Therefore, the proposed application strongly affects museum learning, while the t-test results show a significant difference between the experimental and control groups.

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