Persuasive Teachable Agent for Intergenerational Learning

Abstract

Teachable agents are computer agents based on the pedagogical concept of learning-by-teaching. During the tutoring process, where students take on the role of the tutor to teach a computer agent tutee, learners have been observed to gain deeper understanding of the subject matter. Teachable agents are commonly used in the areas of science and mathematics learning where learners are able to learn complex concepts and deep reasoning by teaching the teachable agent through graphic representation such as concept maps. Literature review on teachable agents as well as observations during field studies conducted by the researcher, have shown that many current teachable agents lack the interaction abilities required to keep learners engage in learning tasks. The result of this is learners deviating from the teaching process, and thus the learners are unable to benefit fully from learning with the teachable agent. The applications of teachable agents are restricted to the learning of academic subjects such as mathematics and science. In this book, we have proposed the Persuasive Teachable Agent (PTA), a teachable agent based on the theoretical framework of persuasion, computational and goal-oriented agent modelling. We argue that the PTA, an autonomous agent, capable of encouraging attitude and behavioural change can offer a more meaningful and engaging learning experiences for learners from different age groups. Based on the findings from our research we argue that persuasive feedback actions generated by the PTA provide significant influence over learner's decision to participate in intergenerational learning. The PTA plays a crucial role in the development of future persuasive technologies in artificially intelligent agents.