Thornton 211 
Tue/Thu 10:30 AM - 11:50 AM 
Questions? From simulating the exponential spread of the COVID-19 virus to understanding biases in machine learning algorithms, explorable explanations are used in teaching about complex concepts and mechanisms. By combining visual metaphors, animations, storytelling, and interactivity, they offer a medium for "thinking the unthinkable." In this graduate-level course, you will learn how to design effective explorable explanations (and more broadly interactive simulations) for learning. You will incorporate key concepts from instructional design, cognitive psychology, and information visualization to create explorable explanations about complex ideas. You will examine different types of explorable explanations, such as interactive infographics, simulations, and games, and learn how to design these types of learning content using web-based tools. You will also develop the skills necessary to offer design feedback and critique and evaluate explorable explanations. The course is targeted toward students interested in designing computer-based interactive learning content as well as those interested in multimedia learning research. The material will be covered through lectures, readings, design critiques, design assignments, and a final project.
By the end of this course, you will be confident in producing explorable explanations for teaching complex concepts. Specifically, you will be able to:
- Understand the key design elements and design principles for creating explorable explanations.
- Apply concepts from visualization, instructional design, and cognitive psychology to represent learning content as interactive explanations.
- Create explorable explanations by following an iterative prototyping process.
- Evaluate the effectiveness of explorable explanations based on aesthetics, engagement, and learning goals.
Required:
- Wieman, C. E., Adams, W. K., & Perkins, K. K. (2008). PhET: Simulations that enhance learning. Science, 322(5902), 682-683. [science.org]
- Bumbacher, E., Salehi, S., Wieman, C., & Blikstein, P. (2018). Tools for science inquiry learning: Tool affordances, experimentation strategies, and conceptual understanding. Journal of Science Education and Technology, 27, 215-235.[Web]
- Population Growth Explorer: HTML
Required:
- De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179-201.[sagepub]
- Wenham, M. (1993). The nature and role of hypotheses in school science investigations. International Journal of Science Education, 15(3), 231-240. [pdf]
- Karagiorgi, Y., & Symeou, L. (2005). Translating constructivism into instructional design: Potential and limitations. Journal of Educational Technology & Society, 8(1), 17-27.[jstor]
Required:
- Paas, F., & Sweller, J. (2014). Implications of cognitive load theory for multimedia learning. The Cambridge handbook of multimedia learning, 27, 27-42.[pdf]
- Victor, B., 2011b. Up and Down the Ladder of Abstraction[web]
- Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive science, 7(2), 155-170.[Wiley]
- Maton, K. (2013). Making semantic waves: A key to cumulative knowledge-building. Linguistics and education, 24(1), 8-22.[sciencedirect]
Required:
- Plass, J. L., Homer, B. D., & Hayward, E. O. (2009). Design factors for educationally effective animations and simulations. Journal of Computing in Higher Education, 21(1), 31-61. [web]
- Segel, E., & Heer, J. (2010). Narrative visualization: Telling stories with data. [IEEE]
Optional:
Required:
- Cook, M. P. (2006). Visual representations in science education: The influence of prior knowledge and cognitive load theory on instructional design principles. Science education, 90(6), 1073-1091.[wiley]
- Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and instruction, 16(3), 183-198. [sciencedirect]
- Rieber, L. P. (1996). Seriously considering play: Designing interactive learning environments based on the blending of microworlds, simulations, and games. Educational technology research and development, 44(2), 43-58. [springer]
- Learning by Design: good video games as learning machines [pdf]
- Gameful Learning: Designing with Motivation in Mind [pdf]
Required:
- Smith, T. L., & Moore, E. B. (2020, April). Storytelling to sensemaking: A systematic framework for designing auditory description display for interactives. [acm]
- Smith, T. L., Lewis, C., & Moore, E. B. (2017). Description strategies to make an interactive science simulation accessible. Journal on Technology and Persons with Disabilities, 225-238. [pdf]