Doctoral Thesis: Researching and Developing the Impacts of Virtual Identity on Computational Learning Environments


Event Speaker: 

Dominic Kao

Event Location: 


Event Date/Time: 

Tuesday, January 9, 2018 - 1:00pm

Over two years, I led an initiative in MIT's Imagination, Computation, and Expression (ICE) Laboratory conducting experiments involving > 10,000 participants to understand the impacts of virtual identities on users in virtual environments. Using a computer science learning platform and game of our own creation as an experimental setting, we have been studying the impacts of avatar use on users' performance and engagement in computer science learning environments. This is a topic of increasing importance in human-computer interaction with the current proliferation of educational games, MOOCs, and with the pervasive use of virtual identities such as avatars in systems ranging from online forums to virtual reality simulations. While a great deal of work focuses on performance of procedural thinking activities such as problem solving and structuring information, attending to learners' development of identities as, and affective engagement with, computer science have been argued as being of great importance as well. We systematically explored the impacts of different avatar types on users, beginning with distinctions between anthropomorphic vs. non-anthropomorphic avatars, user likeness vs. non-likeness avatars, and other conditions informed by insights from the learning sciences and sociology. Our studies have revealed that avatars can support, or harm, performance and engagement. Several notable trends are: 1) simple `abstract' avatars (such as geometric shapes) are especially effective when the player is experiencing failure, e.g., while `debugging,' 2) `likeness' avatars (avatars in a user's likeness) are not always effective, 3) `role model' avatars (in particular scientist avatars) are often effective, and 4) `successful likeness' avatars that are a user's likeness when doing well and otherwise abstract are effective. We outline supporting evidence, and end by describing our findings from a follow-up study incorporating some of these trends.
Thesis Supervisor, Prof. D. Fox Harrell