Self-regulated learning (SRL), learners' monitoring and control of cognitive, affective, metacognitive, and motivational processes, is essential for learning. However, cognitive and metacognitive SRL strategies are not typically used accurately leading to poor learning outcomes. Intelligent tutoring systems (ITSs) attempt to address this issue by…

Pedagogical agents have been designed to support the significant challenges that learners face when self-regulating in advanced learning environments. Evidence suggests differences in learners' prior skills and abilities, in conjunction with excessive didactic support, can cause overreliance on these external aids, which in turn prevents deeper…

The goal of this study was to use eye-tracking and log-file data to investigate the impact of prior knowledge on college students' (N = 194, with a subset of n = 30 for eye tracking and sequence mining analyses) fixations on (i.e., looking at) self-regulated learning-related areas of interest (i.e., specific locations on the interface) and on the…

Self-regulated learning conducted through metacognitive monitoring and scientific inquiry can be influenced by many factors, such as emotions and motivation, and are necessary skills needed to engage in efficient hypothesis testing during game-based learning. Although many studies have investigated metacognitive monitoring and scientific inquiry…

Metacognition and emotions play a critical role in learners' ability to monitor and regulate their learning about 21st-century skills related to science, technology, engineering, and mathematics (STEM) content while using advanced learning technologies (ALTs; e.g., intelligent tutoring systems, serious games, hypermedia, augmented reality). In…

In this paper, we investigate the relationship between students' learning gains and their compliance with prompts fostering self-regulated learning (SRL) during interaction with MetaTutor, a hypermedia-based intelligent tutoring systems (ITS). When possible, we evaluate compliance from student explicit answers on whether they want to follow the…

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…

This study examined the nature of cognitive, metacognitive, and affective processes among a medical team experiencing difficulty managing a challenging simulated medical emergency case by conducting in-depth analysis of process data. Medical residents participated in a simulation exercise designed to help trainees to develop medical expertise,…

We used a false-biofeedback methodology to manipulate physiological arousal in order to induce affective states that would influence learners' metacognitive judgments and learning performance. False-biofeedback is a method used to induce physiological arousal (and resultant affective states) by presenting learners with audio stimuli of false heart…

In this study, we examined the effect of two metacognitive scaffolds on the accuracy of confidence judgments made while diagnosing dermatopathology slides in SlideTutor. Thirty-one (N = 31) first- to fourth-year pathology and dermatology residents were randomly assigned to one of the two scaffolding conditions. The cases used in this study were…

This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…

Self-regulated learning (SRL) with hypermedia environments involves a complex cycle of temporally unfolding cognitive and metacognitive processes that impact students' learning. We present several methodological issues related to treating SRL as an event and strengths and challenges of using online trace methodologies to detect, trace, model, and…

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

A number of authors have presented data that challenge the validity of self-report of strategy use or choice of strategy. We created a multiple-choice measure of students' strategy use based on the work of Kozminsky, E., and Kozminsky, L. (2001), and tested it with three samples as part of a series of studies testing the fit of the DIME model of…

Previous studies in our laboratory have shown the benefits of immediate feedback on cognitive performance for pathology residents using an intelligent tutoring system (ITS) in pathology. In this study, we examined the effect of immediate feedback on metacognitive performance, and investigated whether other metacognitive scaffolds will support…