Assessing the Role of Artificial Intelligence in the Teaching-learning Process

Background: Artificial Intelligence (AI) is rapidly emerging as a transformative force in education, holding the potential to revolutionise the traditional teaching-learning process. Far from merely automating existing tasks, AI promises to usher in an era of personalised learning, enhanced efficiency for educators, and enriched engagement for students. While challenges and ethical considerations remain, the trajectory of AI's integration into education points towards a future where learning is more accessible, effective, and tailored to individual needs than ever before. One of the most significant contributions of AI to education lies in its capacity for personalised learning. Traditional classrooms often struggle to cater to the diverse learning paces, styles, and needs of individual students. AI-powered adaptive learning platforms and intelligent tutoring systems (ITS) bridge this gap by analysing student performance data in real-time. They can identify a student's strengths and weaknesses, adapt content difficulty, provide immediate and targeted feedback, and suggest additional resources or alternative explanations. Aims: The aim of this study is to investigate the role of AI in enhancing the teaching-learning process, focusing on Personalised Learning, Administrative Efficiency for Educators, and Student Engagement. Methodology: This study used a mixed-methods approach, combining qualitative and quantitative research designs. A purposive sample of 100 respondents was selected, and data were collected using Google Forms. Regression analysis was used for quantitative data, while qualitative analysis provided in-depth insights into AI's role in personalised learning, administrative efficiency, and student engagement. Findings: The result showed that out of 100 respondents, there were 63 per cent male educators and 37 per cent female educators those were used Artificial Intelligence as a tool in the teaching-learning process. The personalised learning, Learning efficiency and Student engagement variables explain 44.2 per cent (boys) and 43.1 per cent (girls) variance of AI in education. This individualised approach ensures that struggling students receive the necessary support, while advanced learners are challenged with more complex material, fostering deeper understanding and improved academic outcomes. Tools like Khanmigo and Duolingo exemplify how AI can act as a tireless, patient tutor, offering round-the-clock assistance and tailored learning paths. Beyond personalisation, AI significantly enhances administrative efficiency for educators. Teachers often spend a substantial portion of their time on repetitive, time-consuming tasks such as grading assignments, tracking attendance, and generating reports. AI can automate these processes, freeing up valuable time that teachers can then redirect towards direct instruction, mentorship, and fostering stronger student relationships. Conclusion: AI-powered grading systems can provide instant feedback, allowing students to understand their mistakes and make immediate corrections. Furthermore, AI can assist in lesson planning, content creation, and even generating diverse assessment questions, enabling teachers to focus on the human-centric aspects of their profession. The impact of AI extends to improving student engagement. AI-driven tools can create more interactive and dynamic learning experiences. Gamified learning platforms, virtual reality (VR) and augmented reality (AR) simulations, and AI chatbots can make lessons more immersive and enjoyable.