Board 333: Lessons Learned Doing Secondary Data Analysis in EER Conference

Case, JM, Matusovich, HM, Paretti, MC et al. (2023). Board 333: Lessons Learned Doing Secondary Data Analysis in EER .

cited authors

  • Case, JM; Matusovich, HM; Paretti, MC; Benson, L; Delaine, DA; Jordan, SS; Kajfez, RL; Lord, SM; Papp, R; Young, ET; Zastavker, YV



  • This paper reports on a project funded through the Engineering Education and Centers (EEC) Division of the National Science Foundation. The project is aimed towards building understanding in the engineering education research (EER) community about the potential value of secondary data analysis (SDA) as well as developing guidelines for using this research approach. Changing the paradigm of single-use data collection will require actionable, proven practices for effective, ethical data sharing, coupled with sufficient incentives to both share and use existing data. To that end, this project drew together a team of experts and emerging researchers to develop a shared understanding of SDA, and to conduct two intentional projects using this approach. Significant insights from this work included (i.) deeper insights about the ethical implications of SDA as well specific approaches to address these; (ii.) the need for collaborative relationships between those who collected the data and those who are conducting the SDA; and (iii) the value of ongoing reflective practice by the entire team. We also solicited views from a larger workshop group at the NSF EEC Grantees conference in 2022 which surfaced ongoing concerns expressed by those who are new to this approach and confirmed the need for the engagements with the broader community that have been central to this project.

publication date

  • June 25, 2023