Successful performance during multimedia learning requiresaccurate metacognitive judgments. However, little researchhas investigated the influence of accurate metacognitivejudgments for different representations of information (e.g.,text and diagram) on performance during multimedialearning. As such, we investigated if participants’metacognitive judgments for text and diagrams (i.e., contentevaluations; CEs) were significantly related to increasedperformance and higher confidence during multimedialearning. Metacognitive judgments and performance measureswere collected from 48 undergraduate participants during 18randomized trials. Results using multilevel modelingindicated that participants’ CEs for text-based content weresignificantly predictive of performance. Results also showedthat accurate CEs for diagrams interacted with accuratemultiple-choice responses to predict higher retrospectiveconfidence judgments (i.e., higher confidence). Identifyingmetacognitive judgments predictive of increased performanceduring multimedia learning has important theoretical,conceptual, and analytical implications.

Self-regulated learning (SRL) can be measured in different ways (e.g., eye-tracking) and can be impacted by individual differences (e.g., prior knowledge) as college students learn with MetaTutor, an intelligent hypermedia system. In this study (N = 30), we examined fixation and duration data on interface-related areas of interest (AOI)-pairs as indicators of cognitive and metacognitive SRL strategies, and whether the frequencies of fixations and proportion of time spent on these AOI-pairs differed between prior knowledge groups. Results indicated that high prior knowledge learners selected significantly more cognitive (e.g., summarize) SRL strategies than learners with low prior knowledge. Additionally, learners with low prior knowledge spent a significantly higher proportion of time engaging in help seeking behavior, compared to high prior knowledge learners. These results have implications for designing advanced learning technologies capable of detecting real-time eye-tracking data used to adapt to fluctuations in learners’ SRL processes and foster effective learning.

The current study examined the impact of agency on college students’ emotions and learning during gameplay with CRYSTAL ISLAND, a game-based learning environment designed to foster microbiology learning. 96 undergraduate students (59% female) from a large North American university participated in the study. Participants were randomly assigned to one of three experimental conditions (i.e., full agency, partial agency, no agency), based on the level of control granted during gameplay, and were asked to uncover the source, identity, and best treatment for a mysterious illness. Results revealed participants in the partial agency condition achieved the highest (pre- to post-test) proportional learning gain (PLG), even when controlling for session duration. Additionally, there was a positive correlation between evidence scores of four emotions (anger, fear, confusion, and frustration) and PLG within the partial agency condition—meaning the higher the evidence of the above emotions, the higher the PLG. Further, a stepwise multiple regression showed anger as the sole predictor of PLG. Results from this study have important implications for understanding the role of autonomy and emotions during learning and problem solving with GBLEs designed to foster scientific thinking in STEM. The current study suggests that although GBLEs offer significant learning benefits, they also induce several emotions that can facilitate or inhibit learning gains, requiring further examination.