Note-taking within MetaTutor: interactions between an intelligent tutoring system and prior knowledge on note-taking and learning

Abstract

Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE—MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and metacognitive self-regulated learning (SRL) processes—interacts with learner’s prior domain knowledge to affect their note-taking activities and subsequent learning outcomes. Sixty (N = 60) college students studied with MetaTutor for 120 min and took notes on hypermedia content of the human circulatory system. Log-files and screen recordings of learner-system interactions were used to analyze notes for several quantitative and qualitative variables. Results show that most note-taking was a verbatim copy of instructional content, which negatively related to the post-test measure of learning. There was an interaction between prior knowledge and pedagogical agent scaffolding, such that low prior knowledge students took a greater quantity of notes compared to their high prior knowledge counterparts, but only in the absence of MetaTutor SRL scaffolding; when agent SRL scaffolding was present, the note-taking activities of low prior knowledge students were statistically equivalent to the number of notes taken by their high prior knowledge counterparts. Theoretical and instructional design implications are discussed.