Project’s NSF Page

Investigators

John Morelock, Ph.D. - EETI Associate Director for Educational Innovation and Impact
Joachim Walther, Ph.D. - EETI Founding Director, Professor of Engineering Education
Nicola Sochacka, Ph.D. - Adjunct Faculty, College of Engineering

Grant Details

Funder: National Science Foundation – Engineering Education Research and Centers (EEC)
Amount: $47,350.00
Award number: 2039871
Start and End date: March 2021 – September 2024

Abstract

To help develop the nation’s engineering workforce, the National Science Foundation has invested substantial public funding in engineering education research over the past twenty years. This investment has helped markedly improve courses and programs at many universities by testing and sharing research-based practices that promote active learning, increase student motivation and engagement, diversify the field, and better prepare students for work. At the same time, the investment has typically focused on researchers collecting new data, resulting in hundreds of data sets that remain underexplored. These existing data sets have significant potential to be analyzed and even combined in new ways to further support large-scale changes in how we recruit, teach, and prepare engineering students for the demands and challenges of the 21st century. Currently, however, engineering education researchers do not have productive and effective ways for sharing and analyzing data beyond the original project. Thus the full potential of these data sets remains untapped. This project will address that gap by developing and promoting a viable approach that will enable researchers to leverage the rich data currently available. In doing so, it will simultaneously improve engineering education nationally and increase the return on investment of public funds. The project will bring experienced researchers together with those just beginning their careers to identify the major roadblocks to sharing and re-using data, develop strategies and practices for overcoming those roadblocks, and conduct a series of test cases that demonstrate how to put those strategies and practices into action. The results will help create a paradigm shift that can move both the study and the practice of engineering education in the U.S. to a new level and spur the kind of sea changes needed to keep the nation’s engineering workforce at the forefront of the global marketplace. Changing the paradigm of single-use data collection is a high-risk proposition that requires actionable, proven practices for effective, ethical data sharing, coupled with sufficient incentives to both share and use existing data. To that end, this proposal draws together a team of experts to overcome substantial obstacles in data sharing and build a framework to guide secondary analysis in engineering education research. In particular, we will bring together established and emerging scholars to deliver a tested framework that outlines methodological best practices for formally and informally sharing data, making data sets public, combining data from different studies, performing secondary analyses of both qualitative and quantitative data, publishing and sharing the results, securing the needed funding, and ensuring that the work is valued in the field. To create this framework, the research team will hold a series of six workshops over two years. In the first year, we will bring highly respected, experienced researchers from institutions across the country together with newer researchers to create the initial framework for data sharing and data re-use. In the second year, we will test and refine that framework on two existing data sets. We will solicit data sets from the wider community, and invite teams of scholars to conduct secondary analysis on those data sets, in conversation with the original researchers. Importantly, in selecting both the data sets and the approaches to secondary analysis, we will emphasize methodological diversity to ensure that the framework is widely applicable. The outcome will be a framework document that will comprise a set of tested guidelines for data sharing and secondary analysis in engineering education research, distributed through both journals and workshops to promote widespread adoption. This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.