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Interface agents as social models: the impact of appearance on females' attitude toward engineering
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Source Conference on Human Factors in Computing Systems archive
CHI '06 extended abstracts on Human factors in computing systems table of contents
Montréal, Québec, Canada
SESSION: Work-in-progress table of contents
Pages: 526 - 531  
Year of Publication: 2006
ISBN:1-59593-298-4
Authors
Amy L. Baylor  Florida State University, Tallahassee, FL
Rinat B. Rosenberg-Kima  Florida State University, Tallahassee, FL
E. Ashby Plant  Florida State University, Tallahassee, FL
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 14,   Downloads (12 Months): 68,   Citation Count: 5
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ABSTRACT

This experimental study investigated the impact of interface agent appearance (age, gender, "coolness") on enhancing undergraduate females' attitudes toward engineering. Results revealed that participants reported more positive stereotypes of engineers after interacting with a female agent. In contrast, participants interacting with a male agent reported that engineering was more useful and engaging. An interaction of "coolness" and age indicated that agents who were young and "cool" (i.e., peer-like; similar to participants) and agents who were old and "uncool" (stereotypical engineers) were both most effective on enhancing self-efficacy toward engineering.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
American Association of University Women. (2000). Tech savvy: Educating girls in the new computer age. Washington, DC: American Association of University Women Educational Foundation.
 
2
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman and Company.
 
3
Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of Personality and Social Psychology, 41(3), 586--598.
 
4
Baylor, A. L. (2002). Expanding preservice teachers' metacognitive awareness of instructional planning through pedagogical agents. Educational Technology, Research & Development, 50, 5--22.
 
5
Baylor, A. L. (2005). The Impact of Pedagogical Agent Image on Affective Outcomes. Proceedings of Workshop "Affective Interactions: The Computer in the Affective Loop" at the International Conference on Intelligent User Interfaces, San Diego, CA.
 
6
Baylor, A. L., & Kim, Y. (2005). Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education, 15(1).
 
7
Baylor, A. L. & Plant, E.A. (2005). Pedagogical agents as social models for engineering: The influence of appearance on female choice. In C.K. Looi, G. McCalla, B. Bredeweg, & J. Breuker (Eds.), Artificial intelligence in education: Supporting Learning through intelligent and socially informed technology (Vol. 125, pp. 65--72). IOS Press.
 
8
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9
Goethals, G. R., & Nelson, R. E. (1973). Similarity in the influence process: The belief-value distinction. Journal of Personality and Social Psychology, 25(1), 117--122.
 
10
Kim, Y., & Baylor, A. L. (in press). A social-cognitive framework for pedagogical agents as learning companions. Educational Technology Research & Development.
 
11
Moreno, R., Mayer, R. E., Spires, H. A., & Lester, J. C. (2001). The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cognition and Instruction, 19(2), 177--213.
 
12
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13
Schunk, D. H. (1987). Peer models and children's behavioral change. Review of Educational Research. 57, 149--174.


Collaborative Colleagues:
Amy L. Baylor: colleagues
Rinat B. Rosenberg-Kima: colleagues
E. Ashby Plant: colleagues