Machine Learning’s Growing Role in Research

Methodology and Acknowledgments

Methodology

Interviews were conducted with 20 participants including faculty researchers, graduate students, and IT managers from of the following higher education institutions: Carnegie Melon University, Stanford University, Jackson State University, Massachusetts Institute of Technology, Northeast Wisconsin Technical College, Red Rocks Community College, Rice University, University of California, Berkeley, and University of California, San Diego. For researchers, interview questions focused on needs, challenges, technologies, research process, and machine learning trends. For IT managers, interview questions focused on priorities, budgets, technology, processes, services, and interactions with researchers. Interviews were conducted virtually and lasted between 30 minutes and an hour.

Acknowledgments

I would first like to offer special thanks to HP, especially Jeff Chen and Dana Castro, for making this research possible and for providing helpful insight and assistance throughout the project. I would also like to thank all of the researchers and IT professionals who spent their very valuable time in interviews providing insights based on their hard work and experience. I would also like to thank the EDUCAUSE staff members—Jim Burnett, Carolyn Colman, Kate Roesch, Mark McCormack, and Jamie Reeves—who all played an important role in the creation and publication of this research project. Gregory Dobbin and the publication team provided helpful and timely copy edits and other editorial suggestions. Connie Ferger applied her very impressive content management and marketing skills to support the release of the research materials.