The effects of artificial intelligence-based interactive scaffolding on secondary students’ speaking performance, goal setting, self-evaluation, and motivation in informal digital learning of English

Abstract

Artificial intelligence-based interactive scaffolding (AIIS), which is the interactive process that learners communicate with AI to learn by implementing learning activities with AI’s gradual assistance, has recently been reported to provide potential benefits to teachers and learners in informal digital learning of English (IDLE). While much previous research has focused on the combined effects of AIIS in facilitating interactions with teachers, learner peers, and content in higher education, this study specifically examined the discrete effects of AIIS on secondary students’ speaking performance, goal setting, self-evaluation, and motivation, and the developmental trend of goal setting, self-evaluation, and motivation in IDLE. Sixty secondary students were assigned into the treatment group of interacting with AIIS and the control group of observing fixed scaffolding over ten sessions in IDLE. Results indicated that the treatment group showed more learning gains in vocabulary, goal setting, self-evaluation, and motivation than the control group. Moreover, despite the similar decline and rise developmental trajectories of goal setting, self-evaluation, and motivation, the treatment group dropped less in the middle of the sessions. This study adds to the scarce evidence that AIIS facilitates secondary students’ speaking learning in IDLE and provides theoretical, pedagogical, and research implications for AI-supported interactive learning environments.