Measuring transformative learning in STEM: validating the transformative learning scale for the innovation mindset (TLSIM) in experiential programs

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Abstract

The transformative learning scale for the innovation mindset (TLSIM) is an instrument that effectively assesses both process-related experiences and outcome-oriented shifts in students’ self-awareness, open-mindedness, and innovation capabilities resulting from participation in innovation competitions and programs (ICPs), namely, experiential learning opportunities. It was developed using transformative learning theory (TLT) and the Kern Entrepreneurial Engineering Network’s (KEEN) 3Cs framework (Curiosity, Connections, and Creating Value). The study involved developing scale items, validating content and face validity through expert reviews and student focus groups, as well as conducting psychometric analysis using confirmatory factor analysis (CFA) on data collected from 291 STEM students (70.2% from engineering) who participated in ICPs. The CFA results showed strong factor loadings across most constructs, with Root Mean Square Error of Approximation (RMSEA) values within acceptable limits, confirming the robustness of the TLSIM for measuring both process-oriented (RMSEA = 0.047, CFI = 0.929) and outcome-oriented constructs (RMSEA = 0.052, CFI = 0.901) in the development of an innovation mindset. The analysis showed that TLSIM is a reliable and valid instrument with strong psychometric properties for measuring key constructs related to the innovation mindset. TLSIM can capture significant changes in students’ beliefs, attitudes, and self-perceptions regarding innovation. Future research should refine TLSIM across various disciplines.

Original languageEnglish (US)
Pages (from-to)431-460
Number of pages30
JournalEntrepreneurship Education
Volume8
Issue number3
DOIs
StatePublished - Sep 2025

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Education
  • Social Sciences (miscellaneous)
  • Economics, Econometrics and Finance (miscellaneous)

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