Education Theories and AI Affordances: Design and Implementation of an Intelligent Computer Assisted Language Learning System

Xiaobin Chen, Elizabeth Bear, Bronson Hui, Haemanth Santhi Ponnusamy, Detmar Meurers

Abstract: Skepticism towards AI-powered education products is widespread among educators. One reason for this skepticism is a perceived gap between what educators consider effective teaching and what AIED systems offer. This paper tries to address the issue by arguing for an architectural design that is oriented towards education theories and empirical findings instead of solely towards AI affordances, the benefits of which include more robust AIED systems and higher educator acceptance because of the increased match between the expectations of educators and the systems’ offerings. We illustrate this design principle with an on-going intelligent computer assisted language learning project’s architectural design by referring to the Interaction Theory of second language learning and state-of-the-art AI technology to implement the theoretical requirements.

External IDs:dblp:conf/aied/ChenBHPM22