Content area

Abstract

Computer science (CS) education is foundational for 21st century learning. Equipping students for the future begins with becoming active problem-solvers and confident critical thinkers in elementary school. Early CS learning increases self-efficacy, the ability to reject beliefs in gender stereotypes, and the likelihood of future CS participation. However, self-efficacy does not necessarily lead to high career self-efficacy. Specifically, it is essential for female students, who are underrepresented in the computing field, to experience direct instruction of CS careers at an early age. This mixed-methods study focused on understanding how interactions with diverse and non-stereotypical CS role models impacted fifth- and sixth-grade students’ attitudes toward CS careers by highlighting interpersonal skills and collaborative work. Research questions examined the effects of these role model experiences and their influence on both male and female students. Findings provided evidence of increased career self-efficacy and outcome expectancy post-intervention in both genders (n=22) due to broadened understanding and newfound awareness of CS careers. Female students reported they began to see themselves in CS careers after learning that CS jobs required teamwork and empathy. This study concluded that special consideration must be given to developing student attitudes (self-efficacy and outcome expectancy) toward careers. Recommendations are included for how to scale the intervention and continue collaboration with industry partners.

Details

1010268
Title
Debugging Destiny: Building Computer Science Career Self-Efficacy and Outcome Expectancy Through Role Model Interactions in an Elementary Class
Number of pages
208
Publication year
2025
Degree date
2025
School code
0111
Source
DAI-A 86/12(E), Dissertation Abstracts International
ISBN
9798280724198
Committee member
Goldsworthy, William; Abrams, Eleanor; Uy, Phitsamay
University/institution
University of Massachusetts Lowell
Department
Leadership in Schooling
University location
United States -- Massachusetts
Degree
Ed.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
31847271
ProQuest document ID
3217029275
Document URL
https://www.proquest.com/dissertations-theses/debugging-destiny-building-computer-science/docview/3217029275/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic