Students respond differently to teaching practices, and teaching efficacy varies not only across disciplines, universities, and learning objectives, but also among student populations. Given student diversity, teaching is shifting from a one-size-fits-all model to more tailored teaching strategies. Research on tailoring teaching practices is starting to look beyond understanding student differences simply as a function of prior academic preparation, gender, and race. Various dimensions of student’s characteristics have been shown to have significant impacts on student learning. What has been lacking in the research are conceptual perspectives and methodological approaches to consider the combined impact of these personal dimensions. The construct of “learning dispositions” refers to habits of mind or tendencies toward the learning process. We conceptualized the student characters of motivation, self-efficacy beliefs, and epistemic beliefs as learning dispositions, examined their reciprocal relationships, and used cluster analyses to generate student learning disposition profiles that provide insights into the heterogeneity of students in our courses. Our sample included 503 students from 7 capstone courses in 4 STEM disciplines (biology, chemistry, economics, and neuroscience) across 4 institutions (Duke University, Morgan State University, UMN, and UNC), thus representing a diversity of student characteristics, course contexts, and institutional settings.
Results/Conclusions
We found pre- vs post-course increases in writing self-efficacy and science self-efficacy (p < 0.001 for both) with large effect sizes (1.13 and 1.26, respectively), and a positive change in mastery-driven motivation (p = 0.003), but with small effect size (0.15). Although these results indicate that these courses have a positive impact on student on average, looking at these dimensions independently only tells part of the story. The cluster analyses identified 5 meaningful constellations of student profiles across the learning disposition dimensions. Two clusters student profiles that were relatively flat across the dimensions. However, 42% of students fall into three interesting clusters. Cluster 3 students have the desirable traits of being motivated by a desire to achieve mastery and having sophisticated epistemic beliefs, yet have low self-efficacy (16% of sample). Students in cluster 4, in contrast, are not motivated by a desire to achieve mastery and have unsophisticated epistemic beliefs, and yet have high self-efficacy (11% of sample). Cluster 5 students are not motivated by a desire to achieve mastery, have neutral epistemic beliefs, and have low self-efficacy (15% of sample), and thus are at risk of leaving science. Teaching strategies should be tailored to the differential needs of each population.