Deep Approach to Learning and Self-Regulated Learning among EFL University Students: A Descriptive Survey Study
DOI:
https://doi.org/10.70610/edujavare.2254Keywords:
Deep Approach To Learning; Self-Regulated Learning; EFL; University Students; Descriptive SurveyAbstract
This study describes how English as a Foreign Language (EFL) university students approach English learning and how they regulate their own learning. A descriptive quantitative survey design was used. Thirty-nine EFL university students completed a 25-item, five-point Likert questionnaire. Items 1–10 measured the deep approach to learning English, and items 11–25 measured self-regulated learning (SRL). Data were analyzed with means, standard deviations, response frequencies, Cronbach's alpha, and a Pearson correlation. Both scales were reliable (α = .817 for the deep approach; α = .834 for SRL). Students reported a high deep approach to learning (M = 4.17, SD = 0.47), with 92.3% of them in the high or very high category. Their SRL was also high, but lower (M = 3.86, SD = 0.49), with 84.6% in the high or very high category. The strongest deep approach items reached means of 4.59, while the weakest items ranged from 3.72 to 3.95. Within SRL, students were strongest in items 21, 19, and 22 (M = 4.21–4.41) and weakest in items 13 and 11 (M = 2.90 and 3.18), which were only moderate. The two constructs were strongly and positively correlated (r = .66, p < .001). The findings suggest that students value meaningful English learning but need more structured support to plan, monitor, and sustain it independently. Lecturers are encouraged to embed explicit SRL training, reflective tasks, and goal-setting routines into EFL courses.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 EDUJAVARE: International Journal of Educational Research

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
License: CC BY-SA 4.0 (Creative Commons Attribution-ShareAlike 4.0 International License)








