Fostering Learner Autonomy Through an AI-Integrated CALL Framework for Developing Undergraduate Listening, Speaking, Reading, and Writing Skills
DOI:
https://doi.org/10.17507/tpls.1605.01Keywords:
AI-Integrated CALL, learner autonomy, LSRW skills development, Mixed-Methods ResearchAbstract
Artificial intelligence has developed rapidly and started to interfere with English language teaching in India across regional universities, where traditionally undergraduate learners remain less engaged in listening, speaking, reading, and writing (LSRW) skills. Against this backdrop, the study has attempted to design, implement, and evaluate an AI-Integrated CALL framework to enhance LSRW skills and learner autonomy among undergraduates of a regional public university in Uttar Pradesh. A mixed methods sequential explanatory design has been adopted in this study, where, in a purposive sampling, 150 second-year undergraduate students (B.A., B.Com., B.Sc.) were divided equally into two groups: an experimental group and a control group. In terms of data compilation, the research involved pre-and post-tests of LSRW proficiencies using adapted CEFR descriptors, administration of a modified learner autonomy questionnaire, AI-usage logging, interviews and focus groups, and reflective journals. The quantitative analyses (t-test, ANOVA, regression, and Tukey HSD) established that the experimental group had a statistically significant improvement over all the domains of LSRW with autonomy and regular AI tool use being strong predictors of performance, whereas the qualitative findings showed enhancement in self-regulation, motivation, and perception of the role of learning, and discussed hazards such as digital access and digital literacy. AI-CALL has expedited the democratization of access to personalized language learning and functional communication and autonomy in resource challenged Indian higher education, subject to careful consideration of disciplinary and infrastructural contexts.
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