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All Journal International Journal of Evaluation and Research in Education (IJERE)
Soon Singh Bikar Singh
Universiti Malaysia Sabah
Education

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Academic stress and life satisfaction as social sustainability among university students Balan Rathakrishnan; Soon Singh Bikar Singh; Azizi Yahaya; Mohammad Rahim Kamaluddin; Fauziah Ibrahim; Zaizul Ab Rahman
International Journal of Evaluation and Research in Education (IJERE) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v11i4.22682

Abstract

This study was conducted to determine the relationship between academic stress and life satisfaction among university students in Sabah, Malaysia. A total of 400 students were selected as respondents and data were collected using questionnaires. Academic stress was measured using the Perception of Academic Stress Scale (PAS), which has four subscales: i) Performance stress; ii) Workload perception of workload and examinations; iii) Academic self-perception; and iv) Time constraints. Meanwhile, the Satisfaction with Life Scale was used to study student’s life satisfaction. The data obtained were analyzed using Pearson correlation and t-test. The results showed that performance stress is negatively associated with life satisfaction, while academic self-perception is positively associated with life satisfaction. The result also showed that perception of workload and examinations and time constraints not associated with life satisfaction. All in all, academic self-perception and performance stress have an association with life satisfaction.
Academic engagement and artificial intelligence platform behaviors in grammar achievement Wang Yadan; Soon Singh Bikar Singh; Connie Shin; Zheng Juncai; Zhang Qianqian
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i3.37822

Abstract

This study is among the first to use archival institutional records to test the incremental validity of artificial intelligence platform behaviors (AI_index) in predicting grammar achievement (GA). Using data from 405 non–English-major freshmen enrolled in a compulsory grammar course at a private Chinese university, we examined whether AI_index predicts end-of-semester grammar exam performance beyond course-embedded behavioral academic engagement (AE_index). AE_index was derived from grade-book quizzes and class interactions, whereas AI_index was constructed from institutional platform logs capturing coursework completion and assigned video viewing. Indices were scaled to a 0–100 range, and GA was measured by a unified final exam. Descriptive statistics, correlations, and hierarchical regression analyses showed that AE_index was a small but significant predictor of exam performance, whereas AI_index was weak and non-significant and added no incremental predictive value beyond AE_index. Together, the two indices explained a modest proportion of variance in GA. These findings suggest that completion-based platform metrics are unlikely to reflect effortful learning unless platform tasks align with summative assessment demands (e.g., translation and proofreading). The findings caution against using completion-based AI metrics as high-stakes indicators without demonstrated task–assessment alignment.
Co-Authors Azizi Yahaya Balan Rathakrishnan Connie Shin Fauziah Ibrahim Mohammad Rahim Kamaluddin Wang Yadan Zaizul Ab Rahman Zhang Qianqian Zheng Juncai