Scaffolding Metacognitive Processes Using Pedagogical Agents During Complex Learning With MetaTutor

• In Event: 63.033 - Scaffolding Metacognition

Abstract

Objectives: Pedagogical agents (PAs) have the potential to scaffold students’ challenges in regulating their own learning about complex science topics while using advanced learning technologies (Azevedo & Aleven, 2013; Azevedo et al., 2012; Biswas et al., 2010; Lester et al., 2013). We converged product data (pretest and posttest scores) with several on-line measures of cognitive, metacognitive, and affective processes (e.g., log-files, metacognitive judgments, use of SRL palette, and facial expressions of emotions) to examine the effectiveness of self- and externally-regulated learning with (i.e., the adaptive version of MetaTutor) or without the agents (i.e., the non-adaptive version of MetaTutor) (Azevedo et al., 2013). In this study, we focus on (1) briefly describing the theoretical basis for designing our PAs and (2) presenting empirical evidence, based on process and product data, regarding the effectiveness of MetaTutor’s four PAs’ metacognitive scaffolding of students learning about a complex biological topic.

Methods and Results: 100 college students took part in a 2-day experiment with MetaTutor (Azevedo et al., 2010) to learn about the human circulatory system. They were instructed to use several key SRL processes during their learning session (e.g., activating relevant prior knowledge and setting-relevant learning goals, assessing metacognitive processes [e.g., FOK, JOL], effective learning strategies). Participants were randomly assigned either to the adaptive or non-adaptive condition. The effectiveness of PAs’ metacognitive scaffolding was assessed based on analyses of participants’ 2-hour session with MetaTutor where we collected the following data from each participant: eye-tracking, video recording of the face (for affect detection and classification), log-files (e.g., quiz results, summaries and metacognitive judgments, learner-agent dialogue), notes and drawings, and physiological data. We also collected pretest and posttest data and several self-report measures on agent likeability and metacognitive knowledge about specific SRL processes. Results indicated statistically significant differences between MetaTutor conditions, such that learners in the adaptive scaffolding condition had higher learning gains, sub-goal quiz scores, spent more time engaging in each learning sub-goal, engaged in more help-seeking behavior, inspected more relevant and less irrelevant multimedia materials during learning, deployed more sophisticated learning strategies, and made higher metacognitive judgments, compared to participants in the non-adaptive condition. These results suggest the importance of metacognitive scaffolding in learning about complex topics and promoting the effective use of SRL strategies while interacting with intelligent, agent-based hypermedia-learning environments.

Significance: Understanding the effectiveness of PAs’ scaffolding on SRL is the key to enhancing complex science, technology, engineering, and mathematics (STEM) learning and performance. The data sources will provide evidence that has the potential to advance current conceptual, theoretical, methodological, and analytical frameworks related to scaffolding and SRL, based on self- and external-regulation (see Molenaar & Järvelä, in press). These advances will in turn allow researchers to design more effective PAs and multi-agent learning environments that are sensitive and responsive to students’ CAM processes during learning.

Authors

• Roger Azevedo, North Carolina State University

• Nicholas Vincent Mudrick, North Carolina State University

• Michelle Taub