The Effects of Deep Learning-Based Teaching and Reading Interest on EFL Reading Comprehension: A 2 × 2 Factorial Study

Reading comprehension remains a persistent concern in Indonesian EFL classrooms, particularly when learners are expected to interpret, integrate, and evaluate information from texts. This study investigated the main effects of Deep Learning-Based Teaching (DLBT) and students' reading interest, as well as their interaction, on EFL reading comprehension. The study employed a quantitative experimental design with a 2 × 2 factorial structure involving teaching method (DLBT and conventional instruction) and reading interest (high and low). Sixty eighth-grade students at SMP Negeri 2 Banyuasin I participated in the study. Data were collected through a 20-item reading interest questionnaire and a 25-item reading comprehension test administered before and after the instructional intervention. Post-test data were analysed using descriptive statistics, planned independent-samples t-tests, and two-way ANOVA after the assumptions of normality and homogeneity had been examined. The results showed significant differences between DLBT and conventional instruction among high-interest students, t(18.113) = 10.068, p < .001, and low-interest students, t(28) = 3.635, p = .001. The two-way ANOVA showed significant main effects of teaching method, F(1, 56) = 85.984, p < .001, and reading interest, F(1, 56) = 57.110, p < .001. The teaching method × reading interest interaction was also significant, F(1, 56) = 13.818, p < .001, indicating that the magnitude of the instructional difference varied across reading-interest levels. The findings suggest that meaningful, learner-centred reading instruction should be considered together with students' motivational characteristics when designing EFL reading instruction.