Pixel-Bit (Dec 2024)

Assessing Attitudes Toward Science, Technology, Engineering, and Mathematics (STEM) for Enhancing Creativity in Secondary Education [Evaluación de actitudes hacia la ciencia, tecnología, ingeniería y matemáticas (STEM) para fomentar la creatividad en la educación secundaria]

  • Mujib,
  • Mardiyah Mardiyah

DOI
https://doi.org/10.12795/pixelbit.109760

Abstract

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Students' attitudes towards subjects such as science, technology, engineering, and mathematics (STEM) play a crucial role in the 21st-century learning process. Increasing the number of students pursuing careers in STEM has been widely recognized as important. Consequently, enhancing students' learning and engagement in STEM subjects, as well as fostering positive attitudes toward STEM, has become a primary objective for K-12 STEM education. However, measuring such attitudes in a learning context remains a significant challenge. This research aimed to develop a comprehensive and valid assessment tool to evaluate students' attitudes toward STEM in a learning context for enhancing students creativity. The sample for this research consisted of 311 secondary school students aged 12.83 ± 1.04 years. The validity of the four-factor structure of the model was evaluated using confirmatory factor analysis. Reliability values for the four factors ranged between .73 and .94 with Cronbach Alpha, while those for composite reliability ranged between .97 and .97. The relationship between variables in attitudes toward the STEM instrument identified various path coefficients and effect sizes, indicating strong correlations between the STEM attitude variables. The analysis revealed significant differences according to grade level, with grade 9 students showing better or at least competitive performance in most disciplines. This questionnaire was found to be a feasible instrument to assess secondary school students' STEM attitudes. These findings have important implications for STEM education strategies, emphasizing the need for sustained and focused approaches to deep learning experiences for all students, regardless of gender.

Keywords