Study Habits, Self-Regulation, and AI-Assisted Learning Among Faculty of Languages Students at Benghazi University: A Descriptive Survey Analysis

Abstract

This study examines how undergraduate students in the Faculty of Languages at Benghazi University structure their independent study time, regulate their own learning, and incorporate artificial intelligence (AI) tools into that process. A total of 116 students completed a descriptive, cross-sectional survey between January 13 and January 20, 2026, covering demographic background, academic major, self-reported grade point average (GPA), preferred study environment, timing and duration of study sessions, pacing across the semester, reliance on lecturer-provided material, background music use, AI-assisted studying, and satisfaction with personal study habits. The typical respondent studies alone (76.7%), in blocks of two to four hours (66.4%), without background music (92.2%), and during the early morning or evening (72.4% combined). Once both AI-related items are counted together, 95.7% of respondents reported some form of AI-assisted studying — a figure that positions AI use as close to a default feature of studying in this group rather than an occasional supplement. Six chi-square tests of independence tested whether self-reported GPA was associated with six study-habit variables. Only one reached significance: GPA and semester-long pacing pattern, χ²(12) = 22.52, p = .032, Cramér's V = .254, though the underlying contingency table fell short of the minimum expected cell-count assumption, so this result carries a caveat. The remaining five relationships were not significant. Several habits often assumed to underpin academic success show little connection to self-reported GPA in this sample, while pacing steadily through the semester carries a small but measurable association with stronger grades. The paper closes with implications for academic advising and suggested directions for future research.