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Do students learn from video lessons presented by pedagogical agents of different racial and gender types equivalently to those delivered by a real human instructor? How do the race and gender of these agents impact students’ learning experiences and outcomes? In this between-subject design study, college students were randomly assigned to view a six 9-minute video lesson on chemical bonds, presented by pedagogical agents varying in gender (male, female) and race (Asian, Black, White), or to view the original lesson with a real human instructor. In comparing learning with a human instructor versus with a pedagogical agent of various races and genres, ANOVAs revealed no significant differences in learning outcomes (retention and transfer scores) or learner emotions, but students reported a stronger social connection with the human instructor over pedagogical agents. Students reported stronger positive emotions and social connections with female agents over male agents. Additionally, there was limited evidence of a race-matching effect, with White students showing greater positive emotion while learning with pedagogical agents of the same race. These findings highlight the limitations of pedagogical agents compared to human instructors in video lessons, while partially reflecting gender stereotypes and intergroup bias in instructor evaluations. 

Abstract A substantial amount of media comparison research has been conducted in the last decade to investigate whether students learn Science, Technology, Engineering, and Mathematics (STEM) content better in immersive virtual reality (IVR) or more traditional learning environments. However, a thorough review of the design and implementation of conventional and IVR conditions in media comparison studies has not been conducted to examine the extent to which specific affordances of IVR can be pinpointed as the causal factor in enhancing learning. The present review filled this gap in the literature by examining the degree to which conventional and IVR conditions have been controlled on instructional methods and content within the K-12 and higher education STEM literature base. Thirty-eight published journal articles, conference proceedings, and dissertations related to IVR comparison studies in STEM education between the years 2013 and 2022 were coded according to 15 categories. These categories allowed for the extraction of information on the instructional methods and content characteristics of the conventional and IVR conditions to determine the degree of control within each experimental comparison. Results indicated only 26% of all comparisons examined between an IVR and conventional condition were fully controlled on five key control criteria. Moreover, 40% of the comparisons had at least one confound related to instructional method and content. When looking at the outcomes of the studies, it was difficult to gather a clear picture of the benefits or pitfalls of IVR when much of the literature was confounded and/or lacked sufficient information to determine if the conditions were controlled on key variables. Implications and recommendations for future IVR comparison research are discussed. 

This study examined how well people can recognize and relate to animated pedagogical agents of varying ethnicities/races and genders. For both Study 1 (realistic-style agents) and Study 2 (cartoon-style agents), participants viewed brief video clips of virtual agents of varying racial/ethnic categories and gender types and then identified their race/ethnicity and gender and rated how human-like and likable the agent appeared. Participants were highly accurate in identifying Black and White agents but were less accurate for Asian, Indian, and Hispanic agents. Participants were accurate in recognizing gender differences. Participants rated all types of agents as moderately human-like, except for White agents. Likability ratings were lowest for White and male agents. The same pattern of results was obtained across two independent studies with different participants and different onscreen agents, which indicates that the results are not solely due to one specific set of agents. Consistent with the Media Equation Hypothesis and the Alliance Hypothesis, this work shows that people are sensitive to the race/ethnicity and gender of onscreen agents and relate to them differently. These findings have implications for how to design animated pedagogical agents for improved multimedia learning environments in the future and serve as a crucial first step in highlighting the possibility and feasibility of incorporating diverse onscreen virtual agents into educational computer software.