About
Multimedia Learning Project
Multimedia learning environments contain instruction that is presented in different representational formats (words and pictures) and processed in different sensory channels (auditory and visual) by the learner. Current consensus among educational researchers is that the design of multimedia learning materials should align with the learner’s cognitive processing resources in a way to prevent unnecessary processing and support effective higher-level cognitive processes. Over the past two decades, Cognitive Load Theory (Sweller, 1994; Sweller, van Merriënboer & Paas, 1998) and Cognitive Theory of Multimedia Learning (Mayer, 2005) have provided a framework for research on cognitive processes that has led to the development of instructional design guidelines (Paas, Renkl, & Sweller, 2003) and to effective learning environments (Ayres & van Gog, 2009).
To extend this research and further refine multimedia instructional guidelines, our lab-Learning Science Research Lab at Arizona State University-investigated the role of social aspects of multimedia learning that may impact how much effort a learner is willing to exert during learning and ultimately enhance the amount or type of learning that occurs. Specifically, we conducted a series of experiments to examine the conditions under which pedagogical agents enhance learning.
Animated pedagogical agents are life-like characters that incorporate some or all of the following features: locomotion, goal-directed gestures, facial expression gaze, a human voice, personalized speech, and interactive behavior by reacting to a learner’s actions (e.g., providing feedback). According to social agency theory (Atkinson, Mayer & Merrill, 2005), an agent is capable of priming learners’ social-interaction schema and motivating learners to engage in learning activities. As a result, agents enhance human-computer interaction by promoting motivation and learning. The experiments we have conducted revealed that: (a) an agent with human voice promoted learning compared to a computer-generated voice; (b) learners presented with an animated agent gained more knowledge than their peers who were presented with a static agent; (c) there was an interaction effect between the presence of agent (with/without) and the type of feedback (simple feedback vs. elaborate feedback); and (d) visual cueing was effective to promote learning. We will continue conducting experiments to investigate research questions related to testing and refining multimedia learning guidelines.