EXAIT: A Symbiotic Explanation Learning System

Abstract

Explainable artificial intelligence has been gaining much attention as systems increasingly make high-stakes recommendation and decisions automatically in a wide range of fields, including education. Meanwhile, research into self-explanation by students as a beneficial intervention to promote metacognitive skills has a long history of research. In this paper, we propose a learning system that aims to bridge understanding between the cyber and physical world by facilitating symbiotic explanation between the EXAIT system and students using the system. A co-evolution cycle of AI recommendation and the self-explanation by students of answer processes is proposed to increase the motivation and awareness of students, and at the same time enhance the effectiveness of the system.