Business curricula are increasingly offering data analytics courses. However, training business students in data-analytic thinking and exposing them to new software requires balancing technical skills with domain-specific knowledge in ways that keep students motivated. In-class observations, student evaluations, and student reflections were used to develop and iteratively improve a data analytics course that overcomes these challenges. A survey and retrospective interviews supplemented these to formulate the lessons learned presented in this paper. These include using the software R as a Blackbox application and creating an atmosphere of collaborative learning. The use of relevant datasets and examples also appealed to students’ intrinsic motivation for their subject.
Kokkinou et al. (Fri,) studied this question.