AI Chatbots in LMS: A Pedagogical Review of Cognitive, Constructivist, and Adaptive Principles
Brian Kamau Mungai, Professor Kelvin Kabeti Omieno, Mathew Egessa, Peninah Njeri Manyara, Independent Researcher, Eldoret, Kenya
Abstract
The sudden growth of technology has profoundly shifted various sectors, notably education, where Artificial Intelligence (AI) chatbots are revolutionizing Learning Management Systems (LMS). LMSs are pivotal in the management of educational materials and engagements between educators and students. Traditional LMSs often encounter obstacles like limited interactivity and static content, which impact student engagement and overall effectiveness. AI chatbots can tackle these challenges by providing real-time, adaptable support, thereby enriching the educational process. This study explores the integration of these chatbots in LMS through the lens of three pedagogical principles: Cognitive Load Theory (CLT), Constructivist Learning Theory, and Adaptive Learning Theory. CLT strives to regulate cognitive load to enhance learning efficiency, with chatbots simplifying content and offering instant feedback. Constructivist Learning Theory advocates for active, contextual learning through interaction, a principle supported by AI chatbots engaging learners in conversations and problem-solving activities. Adaptive Learning Theory emphasizes the personalization of educational experiences, a goal achieved by AI chatbots tailoring content and adjusting to student performance in real time. This study presents AI chatbots' alignment with pedagogical principles, revealing their potential to enhance LMS environments and improve student engagement, comprehension, and achievements.