USE OF ARTIFICIAL INTELLIGENCE AS AN ONLINE PLATFORM FOR ENGLISH LANGUAGE TEACHING AT TERTIARY LEVEL

Abstract

The use of artificial intelligence in the classroom widely known as artificial intelligence education (AIEd) based on many AI-driven applications are now in use in educational institutions. By integrating an AI module with knowledge suggestion into the system, this study builds an online English teaching system use as a platform for self learning English language. The integration of Artificial Intelligence (AI) in language education has transformed traditional pedagogical approaches, offering innovative, adaptive, and interactive learning experiences. This quantitative study investigates the effectiveness of AI-based online platforms for English language teaching at the tertiary level. A structured survey was administered to 200 undergraduate students enrolled in a BS English program at University of Larkano to assess their perceptions of AI-driven learning tools. The collected data were analyzed using SPSS, employing descriptive statistics and hypothesis testing to evaluate engagement, effectiveness, and perceptions. The findings reveal that AI-based platforms significantly enhance English language learning by providing personalized learning experiences, real-time feedback, and increased student engagement. Students with prior experience in AI-assisted learning reported higher satisfaction and perceived effectiveness compared to those without prior exposure. The study also found that AI tools improve various language skills, particularly vocabulary acquisition, pronunciation, and reading comprehension, while their effectiveness in grammar learning remained inconclusive. Furthermore, statistical tests confirmed significant differences in engagement levels across academic years, highlighting the progressive adaptation to AI-based learning over time. The study underscores the potential of AI as a transformative tool in tertiary-level English language education, enhancing both teaching methodologies and student learning outcomes. However, the findings suggest that AI should complement, rather than replace, traditional instructional methods, particularly in areas requiring in-depth linguistic explanations. Future research should explore hybrid AI-human instructional models to optimize learning effectiveness and address existing challenges in AI-driven language education.