Mochamad Nursalim, Wulan P. Saroinsong, Chinun Boonroungrut, Wagino, Augusto da Costa
The global health emergency, COVID-19, significantly influenced schooling in Indonesia. Students employed a variety of coping mechanisms to cope with unusual stress levels during confinement time. Hence, as students' COVID-19 resilience, investigation, and prevention were required for high and chronic stress connected with various disorders. This study aimed to design a predictive model of students' COVID-19 resilience based on artificial intelligence that included certain demographic variables, stress intensity, and mindfulness and to study the relationship between them. A total of 6580 Indonesian students were involved in this study (57.9% female and 70.3% aged between 13 and 15 years old). The prediction model was performed by the architecture of artificial neural networks. The results showed that the model's predictive capacity was over 63% in the testing phase, then reached almost 65% in the holdout phase. Students' COVID-19 resilience was mainly predicted by stress intensity and mindfulness with 100% and 40.9% normalized importance values, respectively. Receiver operating characteristic curve assessed and remarked the model as more superior than random. Our research gave some insight into the use of artificial intelligence in educational research to predict psychological variables. © 2023 The Authors. Psychology in the Schools Published by Wiley Periodicals LLC.
Department of Guidance and Counseling, Universitas Negeri Surabaya, Surabaya, Indonesia; Department of Early Childhood Education, Universitas Negeri Surabaya, Surabaya, Indonesia; Department of Psychology and Guidance, Faculty of Education, Silpakorn University, Bangkok, Thailand; Department of Special Education, Universitas Negeri Surabaya, Surabaya, Indonesia; Department of Guidance and Counseling, Instituto Superior Cristal, Dilli, Timor-Leste
