The role of engineering-related attitude and learning interest on mechanical reasoning: A structural equation modeling study
DOI:
https://doi.org/10.12928/ijei.v7i1.15300Keywords:
engineering-related attitude, interest in learning, mechanical reasoning, structural equation modelingAbstract
The results of previous research have not revealed the factors that influence mechanical reasoning, as a preparatory step to improve the mechanical reasoning abilities of engineering students. Based on this, the purpose of this study is to determine a factor model of engineering-related attitude and interest in learning in influencing mechanical reasoning. This study used a cross-sectional study design. The sampling technique used was purposive sampling, involving 30 mechanical engineering students and 72 civil engineering students from the Faculty of Engineering at Universitas Islam Ogan Komering Ilir Kayuagung. The study was conducted using a questionnaire with four Likert-type scale options. The questionnaire consisting of 13 items on mechanical reasoning, 8 items on engineering-related attitudes, and 8 items on interest in learning. The research data were analyzed using Structural Equation Modeling (SEM) using the SmartPLS4 application. SEM analysis involves two stages: measurement model testing and structural model evaluation. Overall, the results of the PLS-SEM model evaluation show that all indicators have met convergent validity and reliability, the independent variables do not experience multicollinearity, 42.1% of the variation in the mechanical reasoning variable can be explained by the relationship between the indicators that form the construct, and both engineering-related attitudes and learning interests are important and significant factors in influencing mechanical reasoning ability. This study contributes to the existing literature in mechanical reasoning by providing an empirically validated structural model that clarifies the significant roles of engineering-related attitudes and learning interest in explaining variations in students’ mechanical reasoning ability.
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