Visual Analytics for the Additive Manufacturing
Certificate Program

BAM_Flowchart

Principal Investigator: Dr. Kylie Peppler

Creativity Labs Project lead: Joey Huang

The goal of this research is to understand how to design online professional engineering courses to be more efficient for learners and make inferences about what participants are actually learning. This work will be used to inform how future courses are designed for Boeing employees.

Researchers at Boeing and Indiana University desire to lay a foundation for the next generation of online education for professional engineers through: 1) studying design principles for three large online courses — Additive Manufacturing (i.e., 3D printing), Leadership for All, and the Boeing AerosPACE capstone — that would increase the efficiency of time spent on learning; 2) developing recommendations for the design principles of the Boeing AerosPACE capstone; 3) the development of machine learning and visually techniques to find meaningful patterns in learner’s use of course materials, including learner trajectory and learner proficiencies; 4) exploring what professional engineers are learning through these education efforts that actually translate to on-the-job work skills; 5) iteratively aligning course objectives to current research on the science of learning; and 6) creating new peer assessment techniques and rubrics. There is a need to design courses in a way that: inferences about learning can be made in a principled manner when machine learning/AI techniques are applied, the data is organized so that queries about learners can be readily obtained, and explorations on how professional education translate to on-the-job work for Boeing engineers.

A collaborative effort between the Cyberinfrastructure for Network Systems Center at Indiana University, the Creativity Labs, the Massachusetts Institute of Technology, and Boeing. In addition, this project is supported by the The Boeing Company (Grant #1712803).

Representative Publications