Article citationsMore>>

Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Lowe, R., et al. (2022) Training Language Models to Follow Instructions with Human Feedback. Advances in Neural Information Processing Systems, 35, 27730-27744.‏

has been cited by the following article:

• TITLE: Large Language Model (LLM-ChatGPT) and Learner Autonomy: Teaching Present Simple Tense as a Model

  AUTHORS: Hasan Mohammed Saleh Jaashan

  KEYWORDS: Learner Autonomy, LLM-ChatGPT, Sage on the Stage Approach, EFL Learners, E-Learning, Student-Centered Approach

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.15 No.2, February 25, 2025

  ABSTRACT: Learner autonomy stands on the top priorities of scholars due to its pivotal role in fostering student-centered learning methods. It empowers the learners to be in charge of their learning process and be the center of attention in language learning education. For this purpose, different AI tools were used and implemented in pedagogy to narrow the divide in promoting learning/teaching approaches. This study aims to gauge the impact of using LLM-ChatGPT to teach EFL learners the present simple tense autonomously via providing automated feedback, and chances for regular drillings without over reliance on teacher. It also aims to investigate the EFL learners’ perception of using LLM-ChatGPT as a reinforcement approach to learner autonomy. A cohort comprising 50 EFL learners would participate in the study and a between subject design method using control and experimental groups would be implemented. The findings of the study indicated that learners who were taught present simple tense’s rule through using LLM-ChatGPT application, with less teacher’s dominance, scored grades similar to those who were taught the same tense’s rule by the teacher (sage on the stage approach). This substantiates the idea that LLM-Chat GPT acts a role akin to teachers in teaching grammatical rules. Moreover, the learners felt that LLM-ChatGPT application had a positive impact on fostering autonomous learning.