Validation of scale to measure motivation to use Python in Probability and Statistics in Higher Education
DOI:
https://doi.org/10.51247/pdlc.v6i4.653Keywords:
Higher education, Academic Motivation Scale, Probability and Statistics, PythonAbstract
or related fields is essential for training citizens capable of making data-driven decisions. Furthermore, the use of Python allows students to directly apply theoretical concepts to real-world data. The research aimed to validate an instrument based on the Academic Motivation Scale to measure the types of motivation associated with the use of Python in learning probability and statistics among university students. The research was conducted using a quantitative, non-experimental, cross-sectional approach with an instrumental design. Expert judgment was used for content validation. Seventy-six students participated in the pilot test. Internal reliability was acceptable across all three dimensions: intrinsic motivation (α = 0.794), amotivation (α = 0.872), and extrinsic motivation (α = 0.683), although the overall alpha (α = 0.646) suggests room for improvement. The instrument demonstrated adequate psychometric properties: exploratory factor analysis identified three factors consistent with the theoretical model, explaining 74.74% of the total variance. Confirmatory analysis supported this structure with satisfactory fit indices (CFI = 0.955, TLI = 0.942, RMSEA = 0.064). These findings support the instrument's use in university settings, especially in courses that integrate technological tools.
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