Personalising and Revolutionising Language Learning Through Artificial Intelligent-Powered Applications among English Education students of Federal University Otuoke.

Abstract This study investigated the use of Artificial Intelligent-Powered Applications in Personalising and Revolutionising Language Learning Among English Education Students of Federal University Otuoke, Bayelsa State. four research questions were answered and four hypotheses were tested at 0.05 level of significance. A descriptive survey design was adopted for the study. The population of the study consisted of 138 all year one and year two English Education Students at Federal University Otuoke, Bayelsa State. Purposive sampling technique was used to select the year one and two students while convenient sampling technique was used to select 58 English Education Students for data collection. The instrument used was researcher developed Checklist. The instrument was validated by three experts in measurements and evaluation. The reliability of the instrument was determined using Cronbach Alpha and coefficient indices of 0.88 was obtained. Data collected were analysed using descriptive statistics of mean and standard deviation to answer the research questions, while t-test was used to test the hypotheses at 0.05 level of significance. The study reveals that AI tools are essential in language teaching and learning because they enhance learners’ engagement, provide personalised learning experiences, and improve language proficiency, particularly in speaking and writing. However, there are some limitations associated with their implementation, and their potential implications for the future of language learning, such as accessibility barriers, concerns about accuracy, cultural relevance, and bias in language instruction and ethical concerns around data privacy, security risks. Therefore, the review of findings aims at supporting educators, developers, and policymakers in fostering an AI-enriched learning environment that aligns with educational goals while addressing existing limitations.