The Effects of Artificial Intelligence Driven Corpus (AIDC) On ESP Learners' Learning and Retention of Lexical Bundles, Academic Emotions, And Engagement for Learning: A Case of Financial Engineering Students

Abstract

Artificial Intelligence Driven Corpus (AIDC) has gained prominence in language education due to its potential to enhance learners' proficiency in various linguistic aspects. This study explores the impact of AIDC on financial engineering students' learning and retention of lexical bundles and idiomatic expressions, engagement, and academic emotions. The research involved 60 Iranian learners of English for Specific Purposes (ESP). Quantitative data were gathered through pre- and posttests assessing participants' lexical bundles, engagement, and academic emotions. A pretest-posttest research design assessed the learners' lexical bundles, engagement, and academic emotions before and after the treatment. MANCOVA was used for analyzing the data. Results revealed significant improvement in the experimental group learners' lexical bundles, engagement, and academic emotions. These findings underscore the potential of AIDC to positively impact learners' usage of lexical bundles and idioms, engagement, and positive emotions. The treatment also reduced the students' negative emotions. These findings suggest that integrating AIDC into language instruction can lead to more effective vocabulary acquisition, increased learner engagement, and improved overall emotional well-being, particularly in specialized fields such as financial engineering.