التكامل بين الذكاء الاصطناعي والبحث التربوي " تحليل أثر سوء استخدام مواقع التواصل الاجتماعي على الصحة النفسية والتحصيل الدراسي لدى طلاب كلية الآداب والتربية صبراتة

Abstract

In recent years there has been an unprecedented expansion in the use of social media among university students, raising serious questions about its effects on their mental health and academic performance. This study aimed to examine the relationship between patterns of excessive social media use and indicators of mental health—specifically anxiety and depression—as well as its effect on academic achievement among students at the Faculty of Arts and Education, Sabratha University. The study also sought to employ artificial intelligence algorithms to assess their ability to predict groups most at risk of academic decline. The research adopted a descriptive-analytical methodology. The sample comprised 82 students selected via stratified random sampling to ensure representation across different subgroups. Data were collected through an electronic questionnaire covering usage patterns, mental health indicators, and academic achievement levels.

Results indicated that social media has become an entrenched part of the daily routine for the majority of students; however, excessive use was significantly associated with elevated levels of anxiety and depression and a clear negative impact on academic achievement. Machine learning models, including logistic regression and random forest, demonstrated considerable ability to predict students at higher risk of academic underperformance, highlighting the potential utility of these tools in psychological and educational research. The findings confirm that social media misuse is not merely a transient behaviour but rather a factor that can threaten students’ mental health and academic stability. This calls for the development of awareness programs and AI-based early-warning systems capable of delivering more effective support and guidance.