Dr. Jang's work with the Learning Environments Across Disciplines group is a collaboration across themes to explore different methodologies for best assessing, tracking, and supporting learners in major technology-rich environments (TREs). This work has allowed us to identify - either explicit through self-reports or implicit through data mining - key learner variables from multimodal data such as: cognitive knowledge and skills, self-regulated learning (SRL) strategies, affective variables, and students’ goal orientations, and task variables such as: task complexity, task condition, task difficulty, and task motivation. This helped further establish the relationship between learner traits, digital mechanisms, and the features of TREs. Methodological and investigator triangulations have led us to examine learning progressions in terms of cognitive, metacognitive, affective, and self-regulatory growths afforded by technology. Specifically, the this work has examined the extent to which self-regulation underlies several key cognitive, affective, metacognitive, and motivational (CAMM) processes. We continue to collaborate on ways to incorporate learner dashboards that mediate learning through visualizing progressions tailored to individual profiles.
Lab members working on LEADS: