Research Results
We surveyed students before and after deploying our data science modules.
As part of the DIFUSE project we developed an instrument to measure attitudes towards data science with which we probe four central constructs: interest in data science, beliefs about data science, interest in a data science career, and data science self-efficacy.
Upon validation of the instrument, we have deployed it in courses that have adopted data science modules at two time points, at the beginning of the course as well as at the end. This pre/post survey structure allows us to assess changes in student attitudes towards data science over time. Interestingly all of the deployments showed a statistically meaningful (as measured by a t-test with standard significance cutoffs) change in the means across the self-efficacy construct from the pre-module survey to the post. We see this as a powerful result as students’ perception of self-efficacy for data science skills is a central and necessary component of successful independent work.
Results of the pre/post-module survey deployment in six courses with data science modules reported across the four constructs of interest, career, beliefs, and self-efficacy. For each construct, we report the number of students with significant increases in mean as well as the number with significant decreases. The constructs colored yellow (all the self-efficacy constructs and career constructs for ENVS 3 and PSYC 1 21F) have overall significant increases in mean as measured by standard t-tests. The orange construct (beliefs for PSYC 1 21 S) indicated an overall significant decrease
