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The Influence of Computer‐based Model's Race and Gender on Female Students' Attitudes and Beliefs Towards Engineering
Author(s) -
RosenbergKima Rinat B.,
Plant E. Ashby,
Doerr Celeste E.,
Baylor Amy L.
Publication year - 2010
Publication title -
journal of engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.896
H-Index - 108
eISSN - 2168-9830
pISSN - 1069-4730
DOI - 10.1002/j.2168-9830.2010.tb01040.x
Subject(s) - narrative , white (mutation) , race (biology) , black male , black female , psychology , population , interface (matter) , social psychology , gender studies , engineering , sociology , demography , philosophy , biochemistry , linguistics , chemistry , gibbs isotherm , chemical engineering , gene , pulmonary surfactant
B ackground This study explored the use of interface agents, anthropomorphic, 3D‐animated computer characters that provide teaching or mentoring within a computer‐based learning environment, to encourage young Black and White women to pursue careers in engineering. P urpose (H ypothesis ) We hypothesized that computer‐based models that matched young women in terms of their race and gender would be the most effective in positively influencing their interest, self‐efficacy, and stereotypes about engineering. D esign/ M ethod Eighty African American undergraduate female students in Experiment 1, and 39 White undergraduate female students in Experiment 2 interacted with a computer‐based agent that provided a narrative designed to encourage them to pursue engineering careers. The study employed a 2 × 2 between subjects factorial design (agent gender: male vs. female and agent race: Black vs. White). R esults Across both studies we found that race and gender influenced the effectiveness of the agent for several key outcome measures. Computer‐based agents who matched the participants with respect to race and gender tended to be the most effective in improving the women's responses to engineering‐related fields. Nevertheless, the White male agent was actually significantly more influential than the White female agent for female Black participants. C onclusions Personalizing interface agent characteristics to match the target population can increase the effectiveness of a persuasive message to encourage young women to pursue engineering. Such an approach may contribute to the growth and inclusiveness of fields such as engineering.