Artificial Intelligence for Writing Enhancement: Exploring Learners’ Motivation and Perceptions of AI Generated Feedback through Cambridge Write & Improve

Abstract

The incorporation of Artificial Intelligence (AI) into language instruction has offered possibilities for enhancing English as A Second Language (ESL) learners’ writing proficiency and motivation. This study investigates the impact of AI-generated feedback on learners’ motivation in English writing using the Cambridge Write & Improve platform. This study was designed to explore the extent to which AI-generated feedback can improve learners’ motivation in four constructs: self-efficacy, persistence, engagement and autonomy. A mixed-method design was employed in this study with 30 Year 5 ESL learners with mixed abilities in English writing from an urban Chinese vernacular primary school in Johor, Malaysia. A writing pre-test and post-test, a 5-point Likert Scale motivation questionnaire and semi-structured interviews were used to collect the data. The data from pre-test, post-test and questionnaire were analyzed using SPSS and subsequently triangulated with data from semi-structured interviews. Findings revealed a measurable improvement in writing performance with learners achieving higher grades in post-intervention writing test. Learners also reported to develop greater writing motivation with increased self-efficacy, sustained engagement, greater persistence in writing tasks and enhanced learner autonomy in revising written essays. The study demonstrated that AI feedback indeed supported writing skill development and strengthened motivational drives among ESL learners. These findings also address a significant gap in literature pertaining to learner motivation in relation to AI-supported tools to improve writing coherence. Further research can be conducted across different AI writing tools and explore cross-contextual implementations to determine the impact of AI-generated feedback on learners’ writing motivation and writing proficiency.