Using virtual avatars to explore the impact of instructors' gender, race, and qualification on perceived learning in an online classroom

Lamba, Nishtha ORCID: https://orcid.org/0000-0003-2595-5076, Kishore, Sameer ORCID: https://orcid.org/0000-0003-2793-0075 and Khokhlova, Olga ORCID: https://orcid.org/0000-0002-7997-9949 (2022) Using virtual avatars to explore the impact of instructors' gender, race, and qualification on perceived learning in an online classroom. In: The 10th European Conference on Education, 14-17 July 2022, London, UK. . [Conference or Workshop Item] (Published online first)

Abstract

There is substantial evidence that students' perceptions and evaluations of instructors are influenced by their expectations and implicit biases, which further impacts their learning and motivation in higher education. Two ongoing studies with an experimental design examine the impact of A) gender (male, female) and race (South Asian, White) and B) gender and qualifications (MA, Ph.D.) on perceived learning and interest in further learning from the same lecturer. 220 and 325 UAE-based students, respectively, were shown a video of an avatar delivering a short online lecture. Virtual avatars' characteristics were manipulated one at a time while keeping content, tone, delivery, environment, and overall appearance consistent. In the first study, gender and race did not significantly facilitate learning. A non-significant trend suggested that participants showed greater interest in further learning from a male lecturer F (1, 220) = 3.12, p = 0.07, while race remained not significant. Gender and qualification, when race was fixed to South Asian, also did not significantly facilitate learning. However, a significant cross-over interaction F (1, 321) = 6.43, p = .01 showed that participants had a greater interest in further learning from a female lecturer with M.A. and a male lecturer with a Ph.D. In line with previous research, findings indicate gender disparity based on educational qualifications. Importantly race does not show discriminatory bias. Given there is limited information in the context of Middle East and South Asia, findings highlight differences specific to the region. Analysis with the full dataset will be presented at the conference.

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