The Challenge of Measuring Processes and Outcomes While Learning from Multiple Representations with Advanced Learning Technologies

This chapter focuses on the challenges of measuring self-regulatory processes and learning outcomes while learning from multiple representations with advanced learning technologies (ALTs). More specifically, we present challenges associated with measuring learners' processes and outcomes while using multiple representations with ALTs. ALTs are technology-based learning and training systems designed to teach learners of all ages to learn, reason, problem solve, and understand different topics and domains such as physics, math, history, biology, medicine and can include different systems such as multimedia, hypermedia, serious games, simulations, intelligent tutoring systems, immersive virtual environments and so forth. The structure of our chapter is as follows: (1) a brief overview of the major issues related to using multiple representations for learning with ALTs; (2) a description of the analytical techniques for understanding multiple representations and their goals for successful learning with ALTs; (3) a discussion of the issues associated with using multiple representations to measure and assess learning outcomes and how we can use ALTs as research tools to capture self-regulated learning; and (4) a presentation of challenges and future directions that need to be addressed by researchers.