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Prior Literature has evidence that students’ engagement plays a vital role in developing their interest in STEM (Science, Technology, Education, and Mathematics) courses, their performance, and their selection of college majors and careers. One way of achieving this engagement is through the active involvement of students in science courses at an early age and school life. Literature shows that students’ engagement and learning can be improved by introducing meaningful and conceptually driven curriculum. Considering the role of active engagement in science classes as a critical factor to students’ performance, we designed a life sciences curriculum unit, and associated assessment for 6th-grade students. We developed curriculum materials, which integrated engineering design principles in an existing unit of the life sciences curriculum. We introduced the curriculum unit through 11 teachers in eight middle schools across the Midwest. We collected the data of students’ pre-engagement (before the implementation of the curriculum unit) and performance in the curriculum unit (based on an associated assessment) from 915 6th grade students. To collect students’ engagement, we used the modified multidimensional engagement instrument, “The Math and Science Engagement Scales” [1]. The instrument has four dimensions, which are behavioral, emotional, cognitive, and social. The assessment of the curriculum unit was done in a pre and post manner. In this study, we specifically studied the role of students’ pre-engagement in predicting students' performance in the curriculum unit while accounting for students’ prior performance. We used multiple regression analysis to explore the relationship between each dimension of students’ engagement and performance. The results indicated that students’ pre-assessment, behavioral engagement, and social engagement are the significant predictors of their performance in the post-assessment. The full paper will discuss these results in light of the integrated STEM approach and previous literature evidence. Further, we will discuss the limitations and implications of the study and will provide future directions for research. References [1] M.-T. Wang, J. A. Fredricks, F. Ye, T. L. Hofkens, and J. S. Linn, “The Math and Science Engagement Scales: Scale development, validation, and psychometric properties,” Learn. Instr., vol. 43, pp. 16–26, 2016.
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Anwar et al. (2020) studied this question.
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