PhD Thesis Proposal, "The Influence of Cuturally-Aligned Educational Technology on Student Performance and Social Behavior"

 

Justine Cassell (chair) (Language Technologies Institute, CMU)

Amy Ogan (Human-Computer Interaction Institute, CMU)

Marti Louw (Human-Computer Interaction Institute, Learning Media and Design Center at CMU)

Sandra Calvert, (Children's Digital Media Center, Georgetown University)

 

Though one of the main benefits of educational technologies is the opportunity for personalization, when it comes to culture, most media is ‘one size fits all.’ There is much debate about if and how to integrate students' native cultural behaviors into the classroom, particularly regarding the use of non-Standard English dialects that are heavily stigmatized within contemporary society. Over the past five years, we have examined the impact of using students’ native dialects of English within the design of a social educational technology called a Virtual Peer (VP). We have found that African American students who speak a dialect of English called African American Vernacular English (AAVE) perform better science after speaking with a VP that uses both AAVE and Standard English, rather than one that uses Standard English exclusively. Furthermore, those students who worked with a bidialectal VP were less likely to demonstrate agent abuse - a factor which was negatively correlated to students' science performance.

 

In the proposed research, we will augment our current understanding of this phenomenon by collecting data on students' perceived social relationships with the VP. We hypothesize that AAVE-speaking students who work with a bidialectal VP will report higher rapport with the agent. We additionally hypothesize that this social relationship score will be a significant predictor of students' science performance. The primary contribution of this work is (1) to demonstrate the impact of one particular culturally-based design choice, dialect, within an educational technology on students' resulting science performance and social behavior, and (2) explore the role of social relationship as a mediating factor between agent dialect and student performance. This work will provide evidence toward a long-standing debate within the field of educational about the role of dialect in students' learning. We believe that this work has implications not just for the future design of educational technologies, but also the design of even non-technological learning materials more broadly.