Jeff Bean

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Fake data, analysis, statistics, data fluency, pedagogy, reverse engineering


Second Annual University of Arkansas Teaching and Learning Symposium: Sharing Teaching Ideas While not a formal discipline, “reverse engineering” can yield opportunities for students to experience a compressed end-to-end (e2e) life cycle of projects that leverage human factors such as perception, cognition, and macro-factors such as organizational culture or situational context to improve operations performance, safety, or other organizational outcomes.

As the process of project proposal, approval, and execution can often take months (or longer!), we simply do not have the time or resources to conduct “real” experiments. To give the benefit of e2e projects, students are asked to create hypothetical-yet-realistic problem statements in Week 3 of the course in which they leverage course content and their often-substantial work experience. Following feedback and the opportunity to iterate, students are placed in small groups (Week 4) in which they discuss and settle upon a single potential “opportunity” for which they propose an intervention and which includes a hypothesized impact statement in terms that organizations understand (financial) (Week 6). In the final weeks of the course, student teams generate “fake data” to resemble the actual data collection if there were time and resources. In so doing, this employs both a “bottoms up” (i.e., here is the data, analyze it) and a “top down” (i.e., here is the analysis, what does it mean?) approach to understanding course content as well as statistical process and presentation.

In summary, the opportunity to reverse engineer findings can teach a great deal about the process of data collection, analysis, as well as limited resource allocation.