SIGCSE TS 2026 (series) / Journal First / Development and Analysis of Pre-service Teachers’ Self-efficacy in Integrating Computer Science Survey Instrument Using Confirmatory Factor Analysis
Development and Analysis of Pre-service Teachers’ Self-efficacy in Integrating Computer Science Survey Instrument Using Confirmatory Factor AnalysisK12
Thu 19 Feb 2026 11:33 - 12:00 at Meeting Room 241-242 - ACM TOCE: Youth, identity, and teachers
Computer science (CS) in K-12 education is growing rapidly in response to national educational policy. As a result, teacher education programs are increasingly integrating CS within their courses. As pre-service teachers (PSTs) develop knowledge about learning and teaching CS, it is imperative to help PSTs build self-efficacy in CS and associated technology integration. Few instruments have been validated for PSTs’ self-efficacy for future integration of CS. This study presents an analysis of a survey for CS self-efficacy of PSTs. Confirmatory factor analysis (CFA) indicated the items align with the construct, and results demonstrate the validity of the instrument to assess PSTs’ self-efficacy to integrate CS.
Thu 19 FebDisplayed time zone: Central Time (US & Canada) change
Thu 19 Feb
Displayed time zone: Central Time (US & Canada) change
10:40 - 12:00 | |||
10:40 26mTalk | ‘If you can’t dance your program, you can’t write it’: Challenges and Implications for AI in EducationGlobal Journal First Ronnie Videla Universidad Santo Tomás, Chile, Simon Penny University of California, Irvine, Wendy Ross London Metropolitan University DOI | ||
11:06 26mTalk | Design Principles for Authentically Embedding Computer Science in Sports Journal First Herminio Bodon Northwestern University, Vishesh Kumar Vanderbilt University, Marcelo Worsley Northwestern University DOI | ||
11:33 26mTalk | Development and Analysis of Pre-service Teachers’ Self-efficacy in Integrating Computer Science Survey Instrument Using Confirmatory Factor AnalysisK12 Journal First Eric Bredder University of Virginia, Sarah Lilly University of Virginia, Jennifer Chiu University of Virgina DOI | ||