Ho, C., & Raubenheimer, D. (2011, June), Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities  Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. 10.18260/1-2--17647

\bibitem{asee_peer_17647}
  Ho, C., \& Raubenheimer, D. (2011, June), \emph{Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities}
  Paper presented at 2011 ASEE Annual Conference \& Exposition, Vancouver, BC.
  10.18260/1-2--17647

Chia-Lin Ho and Dianne Raubenheimer.  "Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities".  2011 ASEE Annual Conference & Exposition, Vancouver, BC, 2011, June.  ASEE Conferences, 2011.  https://peer.asee.org/17647 Internet.  24 Jul, 2024

\bibitem{asee_peer_17647}
  Chia-Lin Ho and Dianne Raubenheimer.
  "Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities".
  \emph{2011 ASEE Annual Conference \& Exposition, Vancouver, BC, 2011, June}.
  ASEE Conferences, 2011.
  https://peer.asee.org/17647 Internet.  24 Jul, 2024

@INPROCEEDINGS{asee_peer_17647
author = "Chia-Lin Ho and Dianne Raubenheimer"
title = "Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities"
booktitle = "2011 ASEE Annual Conference \& Exposition"
year = "2011"
month = "June"
address = "Vancouver, BC"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/17647}
number = {10.18260/1-2--17647}
}

TY  - CPAPER
AB  -     Computing-related Self-efficacy: The Roles of Gender, Academic Performance, and                               Computational CapabilitiesAbstractResearch has documented that self-efficacy is a great predictor of individuals’ behaviors andmotives. In engineering education, self-efficacy has received a significant amount of attention indealing with the issues regarding retention of female engineering students. As an effort tounderstand the role of self-efficacy in engineering education, this study focuses on self-efficacytowards computing and engineering and examines their relations to gender, GPAs, andcomputational capabilities.This study is part of a larger project, supported by a National Science Foundation CISEPathways to Revitalized Undergraduate Computing Education (CPATH), designed to preparestudents for pervasive, advanced computing in the workplace. These data included participants(N = 418) enrolled in undergraduate engineering courses in several programs in 2009 and 2010.These participants completed measures of computer self-efficacy and self-efficacy towardsengineering, self-ratings of six computational capabilities (i.e., database fundamentals, processmodeling and design, basic knowledge of programming, data analysis skills, communicationtools/organization, and web search) indicated as important to industry representatives, anddemographic information.Two multiple regression analyses were conducted, each for computer self-efficacy and self-efficacy towards engineering/computer science. Gender, GPAs, and six computationalcapabilities were regressed on each measure of self-efficacy. The analysis results revealedsignificant gender differences in computer self-efficacy and self-efficacy towardsengineering/computer science, providing support for the continuing existence of genderdifferences in computing-related self-efficacy. Individuals with higher GPAs reported higherlevels of self-efficacy towards engineering/computer science. Ratings on computationalcapabilities also showed different relations to computer self-efficacy and self-efficacy towardsengineering/computer science. Specifically, controlling gender and GPAs, self-efficacy towardsengineering was predicted by reported skill level on database fundamentals, basic knowledge ofprogramming, and data analysis. Computer self-efficacy was predicted by capabilities on basicknowledge of programming, communication tools/organization, and web search above andbeyond gender and GPAs.The study results provide support for the relations of computing-related self-efficacy, gender,GPAs, and skill level of specific computational capabilities. Given the importance of self-efficacy in learning, these findings have implications for engineering education. Besidescontinuing to acknowledge gender differences in computing-related self-efficacy, traininginterventions to enhancing computational capabilities should be implemented to increasestudents’ computer self-efficacy and self-efficacy towards engineering/computer science and, inturn, lead to more learning involvement and higher learning motivation.Analysis results for “self-efficacy towards engineering”Analysis results for “computer self-efficacy”
AU  - Chia-Lin Ho
AU  - Dianne Raubenheimer
CY  - Vancouver, BC
DA  - 2011/06/26
PB  - ASEE Conferences
TI  - Computing-Related Self-Efficacy: The Roles of Gender, Academic Performance, and Computational Capabilities
UR  - https://peer.asee.org/17647
DO  - 10.18260/1-2--17647
ER  -