Design Implications for Next Generation Chatbots with Education 5.0

Prior research indicates that chatbots have the capacity to significantly enhance learning performance, student satisfaction, and engagement. Chatbots are employed in various educational contexts, serving as content delivery platforms, facilitating student interaction, fostering collaborative learning, and promoting question-and-answer practice, among other applications. Moreover, integrating chatbots into teaching practices empowers educators to analyze and assess students’ learning abilities and comprehension levels. However, much of the existing research on educational instruments, including chatbots, lacks both theoretical support from recent advancements in the learning sciences and an evidence-informed foundation for selecting appropriate data and information models. As a consequence, educational chatbots run the risk of yielding unintended negative consequences instead of delivering the intended benefits. This study seeks to address this gap by grounding the design of educational chatbots in the principles of learning sciences. We argue that effective communication through educational chatbots necessitates formulating information in the form of feedback dialogues to enhance learners’ comprehension. Additionally, we align the design of educational chatbots with learner-centric and mindful technology concepts, inline with Industry 5.0 digitization strategies.