Correlations between modes of student cognitive engagement and instructional practices in undergraduate STEM courses

• Published in: International journal of STEM education Vol. 7; no. 1; pp. 1 - 15
• Main Authors: Barlow, Allyson, Brown, Shane
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 24-04-2020; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Classroom Environment; Classrooms; Cognitive ability; Cognitive Processes; Cooperative Learning; Correlation; Correlation analysis; Education; Educational Practices; Educational Technology; Instructional practices; Learner Engagement; Learning; Learning Processes; Mathematics Education; Measures (Individuals); Partial correlation analysis; Science Education; Self report; Self-report measurement; Statistical Analysis; STEM Education; Student Attitudes; Student cognitive engagement; Student Evaluation; Student participation; Students; Teachers; Teaching; Teaching Methods; Technical education; Undergraduate Students; Variance analysis; Instructional practices; Student cognitive engagement; Self-report measurement; Partial correlation analysis
• DOI: 10.1186/s40594-020-00214-7
• EISSN: 2196-7822

Background
Within STEM education, research on instructional practices has focused on ways to increase student engagement and thereby reap the associated benefits of increased learning, persistence, and academic success. These meaningful-learning goals have been tied most specifically to cognitive engagement, a construct that is often difficult for instructors to assess on their own. While it has been shown that certain instructional practices are tied to higher cognitive engagement in students, tools to measure instructional practices and student engagement have remained largely isolated in their development and use.
Results
This research uses previously developed instruments to simultaneously assess modes of cognitive engagement in students (Student Course Cognitive Engagement Instrument [SCCEI]) and instructional practices (Postsecondary Instructional Practices Survey [PIPS]) within a course. A sample of 19 STEM courses was recruited to participate in this study, with instructors and students each self-reporting data. Results from the instructor and students in each course were scored, and ANOVA and partial correlation analysis were conducted on the sample. ANOVA indicated the significance of and classroom structure on student engagement. From the correlation analysis, a significant relationship was found between four student-reported modes of cognitive engagement and instructor-reported teaching practices.
Conclusions
With an understanding of student engagement response to classroom structure, instructors may consider their teaching environment when implementing instructional practices. Moreover, Interactivity with Peers, the deepest mode of cognitive engagement suggested by previous research, was correlated with instructional practices in our study, suggesting that instructors may be able to shape their students’ learning by encouraging collaboration in the classroom. We also found that assessment played a role in students’ cognitive engagement; this indicates that instructors may wish to thoughtfully consider their methods of assessment to facilitate modes of cognitive engagement associated with deeper learning of course material. By understanding factor correlations, the PIPS and SCCEI can be used in tandem to understand impacts of instructional practices on student cognitive engagement within a course. We conclude that there is a need for ongoing research to study the interplay of instructional practices and student cognitive engagement as instruments are developed to measure such phenomena.