Adam R. Carberry is a doctoral candidate in Engineering Education in the Tufts University Math, Science, Technology, and Engineering Education program. He holds an M.S. in Chemistry from Tufts University and a B.S. in Material Science Engineering with a minor in Chemistry from Alfred University. He is currently working at the Tufts University Center for Engineering Education and Outreach as a research assistant and manager of the Student Teacher Outreach Mentorship Program (STOMP).
Measuring Engineering Design Self-Efficacy
Article first published online: 2 JAN 2013
2010 American Society for Engineering Education
Journal of Engineering Education
Volume 99, Issue 1, pages 71–79, January 2010
How to Cite
Carberry, A. R., Lee, H.-S. and Ohland, M. W. (2010), Measuring Engineering Design Self-Efficacy. Journal of Engineering Education, 99: 71–79. doi: 10.1002/j.2168-9830.2010.tb01043.x
- Issue published online: 2 JAN 2013
- Article first published online: 2 JAN 2013
- engineering design;
Self-concept can influence how an individual learns, but is often overlooked when assessing student learning in engineering.
To validate an instrument designed to measure individuals' self-concepts toward engineering design tasks, three research questions were investigated: (a) how well the items in the instrument represent the engineering design process in eliciting the task-specific self-concepts of self-efficacy, motivation, outcome expectancy, and anxiety, (b) how well the instrument predicts differences in the self-efficacy held by individuals with a range of engineering experiences, and (c) how well the responses to the instrument align with the relationships conceptualized in self-efficacy theory.
A 36-item online instrument was developed and administered to 202 respondents. Three types of validity evidence were obtained for (a) representativeness of multi-step engineering design processes in eliciting self-efficacy, (b) the instrument's ability to differentiate groups of individuals with different levels of engineering experience, and (c) relationships between self-efficacy, motivation, outcome expectancy, and anxiety as predicted by self-efficacy theory.
Results indicate that the instrument can reliably identify individuals' engineering design self-efficacy (α = 0.967), motivation (α = 0.955), outcome expectancy (α = 0.967), and anxiety (α = 0.940). One-way ANOVA identified statistical differences in self-efficacy between high, intermediate, and low experience groups at the ρ < 0.05 level. Self-efficacy was also shown to be correlated to motivation (0.779), outcome expectancy (0.919), and anxiety (—0.593) at the ρ < 0.01 level.
The study showed that the instrument was capable of identifying individuals' self-concepts specific to the engineering design tasks.