Does culture-based learning matter? Learning engagement, computational thinking and scientific attitude among biology students
Muhiddin Palennari, Asham Bin Jamaluddin, Abd Muis, Hamzah UpuPurpose
This study examines the relationships among learning engagement, culture-based learning, computational thinking, and scientific attitude among biology students and evaluates whether culture-based learning provides additional explanatory value.
Design/methodology/approach
A quantitative cross-sectional survey was conducted with 590 undergraduate students from the biology and b iology education study programs at Universitas Negeri Makassar. Data were collected using a four-point Likert questionnaire and analyzed through partial least squares structural equation modeling (PLS-SEM). Computational Thinking was modeled as a reflective-reflective higher-order construct reflected by decomposition, pattern recognition, abstraction and algorithmic thinking. Two competing models were compared: Model I included Culture-based Learning as an explanatory construct, whereas Model II excluded culture-based learning and examined the relationships among learning engagement, computational thinking and scientific attitude.
Findings
All hypothesized associations in Model I were positive and statistically significant. Learning engagement was positively associated with culture-based learning, computational thinking and scientific attitude. Culture-based learning showed strong positive relationships with both computational thinking and scientific attitude, while computational thinking was also positively associated with scientific attitude. The hypothesized indirect associations were also positive and statistically significant. Model I showed stronger explanatory power and predictive relevance than Model II.
Originality/value
This study integrates learning engagement, culture-based learning, computational thinking and scientific attitude within a single framework. It shows that the model including culture-based learning provides greater explanatory and predictive value than the model without it and supports the appropriateness of modeling computational thinking as a higher-order construct in biology education.