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Seeing Experience from Many Angles: Educational Game Design as a Data-Informed Craft

Speaker Name: 
Erik Harpstead
Speaker Title: 
Systems Scientist
Speaker Organization: 
HCI Institute, Carnegie Mellon University
Start Time: 
Thursday, February 21, 2019 - 11:15am
End Time: 
Thursday, February 21, 2019 - 12:15pm
Eddie Melcer


The goal of educational game design is to create an experience that impacts players to change in some way. Game designers, however, cannot create these experiences directly; they can only create the systems and mechanics that give rise to experiences. This fundamental tension makes it difficult for designers to anticipate the implications of their design choices and understand whether their designs are aligned to their goals. Computational methods can be brought to bear on this problem. In my work, I develop novel tools and processes to provide designers with different perspective on player experience by building models of players that can be compared to real player behavior and provide data to decide whether a game is playing according to its intention. In this talk I will describe three projects that support this goal: (1) Clustering player solutions to a puzzle game to reason about its solution space, (2) Fitting skill models to player performance to assess player learning against expectations, and (3) Using in-game replays to virtually playtest redesigns of an educational game without human players. Finally, I will lay out how each of these projects contributes to my vision for educational game design as a data-informed craft.


Erik Harpstead is a Systems Scientist in the HCI Institute at Carnegie Mellon University. His work employs quantitative data science methods and qualitative user research techniques to develop smarter tools and processes for designers of educational technologies and games to interrogate their products and reflect on how well they manifest designers’ intentions. Erik received his PhD in Human-Computer Interaction from Carnegie Mellon University in 2017 where he worked on a novel game analytics technique using in-game replays to evaluate the instructional alignment of educational games and explore potential future designs with automated playtesting. During his PhD he was also a fellow in Carnegie Mellon’s Program for Interdisciplinary Education Research. He has published extensively on game user research and educational data mining.