Exploring the Potential of Computational Self- Representations for Enabling Learning: Examining At-risk Youths' Development of Mathematical/Computational Agency
This paper reports on a study conducted within an alternative high school for students evicted from the mainstream and that utilized the virtual world (Teen Second Life or TSL). The use of selfrepresentations in virtual worlds to enable and facilitate Science, Technology, Engineering, and Mathematics (STEM) learning is a promising endeavor. At the same time, it is not clear how the ability to construct imaginative self-representations can impact students’ abilities to view themselves as STEM learners and doers. Furthermore, questions over whether students should view avatars instrumentally to accomplish virtual tasks, as virtual selves for playful identity construction and performance, or to what degree the avatars should accommodate representing aspects of students’ real selves vs. extraordinary fantastic characters. This paper provides pilot evidence, elicited using grounded theory techniques on data collected in a three-year design-based research study into fostering at-risk students STEM learning. We propose a three-axis model of students’ stances in relationship to their avatars. Using insights from the cognitive science theory of conceptual blending in order to characterize students’ perspectives of their avatars as imaginative integrations of their real and virtual selves, we present a set of case studies illustrating students’ stances in terms of our three axes. The upshot is that students in the study tended to fall into three one of three categories: (1) viewing their avatars as necessarily reflections of their real world identities, (2) viewing their avatars as mere proxies for building artifacts in the world, and (3) viewing avatars as characters external to themselves for engaging in a play of identity performance and presentation. Group (1) found the affordances of TSL to be inadequate, hence serving the needs of this group may require alternative design solutions in light of real world behavior.