Unlocking the impact of ICALL across proficiency levels: EFL learners’ language achievement and multidimensional engagement

Abstract

This quantitative quasi-experimental study examined whether Intelligent Computer-Assisted Language Learning (ICALL)-based instruction improved Chinese English as a Foreign Language (EFL) learners’ language achievement and multidimensional engagement across elementary, intermediate, and advanced proficiency levels. Learners were placed in ICALL-based and traditional instructional conditions according to their proficiency level. The ICALL groups received adaptive grammar, reading, and vocabulary instruction supported by automated feedback, learner monitoring, and proficiency-sensitive task sequencing, whereas the traditional groups received teacher-centered instruction through printed materials and non-adaptive classroom feedback. Data were collected through proficiency-specific General English Tests and a behavioral, cognitive, and emotional engagement questionnaire before and after the intervention. Multivariate analysis of variance and follow-up analyzes of variance indicated that the ICALL groups outperformed the traditional groups in language achievement and demonstrated higher behavioral, cognitive, and emotional engagement. The pattern of improvement varied across proficiency levels, indicating that adaptive feedback and task calibration may support learners differently depending on their instructional readiness. Overall, the findings provide empirical support for integrating ICALL into EFL instruction when intelligent feedback, learner-specific sequencing, and engagement-oriented task design are aligned with proficiency level.