Academic Stress of Students in Higher Education using Machine Learning: A Systematic Literature Review

Academic stress results from greater academic demands and non-academic factors, resulting in students’ performance decline and their ability to cope with academic activities. For past years, academic stress studies have been expanding to provide a greater understanding of the factors contributing to stress, interventions, and support to reduce the chance of impacting students’ learning. At this point, this paper presents a systematic literature review of the academic stress of students in higher education based on machine learning techniques. As such, this paper presents the factors, data preparation, model development, performance, and general description of academic stress based on machine learning techniques. Thus, this paper expands the current understanding of academic stress and recommendations for future work.