CHAT-ACTS: A pedagogical framework for personalized chatbot to enhance active learning and self-regulated learning

Abstract

The CHAT-ACTS pedagogical framework presented in this paper integrates personalized chatbots into active and self-regulated learning (SRL) to enhance student engagement, motivation, and learning outcomes. Employing three primary learning modes - Personalized Chatbot, Self-Regulated Learning, and Active Learning - the learner occupies the central position, symbolizing their active role in shaping their learning journey. Strategic actions such as Evaluation, Feedback, and Plan are crucial in the Personalized Chatbot mode, while the SRL mode emphasizes Goal Setting and Study Tactics. The Active Learning mode underscores Active-Based Learning and Teaching Strategies. Through these modes, bidirectional relationships are established, facilitating feedback, setting goals, and employing active learning techniques. By utilizing this framework, educators can maximize the impact of personalized chatbots in various educational settings.