Harshman Research Group
Discipline-based education research at the University of Iowa
The Harshman Research Group seeks to better the landscape of chemistry education by conducting highly robust research using both qualitative and quantitative methods. We are also passionate about R, a statistical coding language that many of the group’s members find extremely helpful along the way.
# focus areas
doctoral education
instructional practice
robust statistics
# 01 / doctoral education
Effective Doctoral Education in Chemistry
Over 20,000 chemistry students are currently enrolled in doctoral programs across the country, receiving training over five and a half years on average before pursuing careers in industry, academia, government, and beyond. Our group is interested in identifying what knowledge and skills these students gain throughout their programs as well as what they will need, in order to discover gaps in preparation and improve the effectiveness of traditional graduate components.
# related publications
Qu, T. & Harshman, J. (2022). Situational interview based investigation of advisor-advisee conflict communication in U.S. chemistry graduate education.
Journal of Chemical Education, 99(3), 1400-1409. doi.org/10.1021/acs.jchemed.1c01117
Harshman, J. (2021). A review of the challenges that face doctoral education in chemistry.
Journal of Chemical Education, 98(2), 259-269. doi.org/10.1021/acs.jchemed.0c00530
Busby, B. & Harshman, J. (2021). Program elements’ impact on chemistry doctoral students’ professional development: A longitudinal study.
Chemistry Education Research and Practice, 22, 347-363. doi.org/10.1039/D0RP00200C
Cui, Q. & Harshman, J. (2020). A qualitative investigation to identify the knowledge and skills that chemists require in the workplace.
Journal of Chemical Education, 97(5), 1247-1255. doi.org/10.1021/acs.jchemed.9b01027
# 02 / instructional practice
Instructional Practices in STEM Classrooms
Our group investigates patterns in instructor observations using the Classroom Observation Protocol for Undergraduate STEM (COPUS), with the hope of more directly linking classroom behaviors with education outcomes. We also maintain the COPUS Analyzer website with Dr. Marilyne Stains at the University of Virginia, a tool that provides meaningful feedback and classifications from observation data.
# related publications
Popova, M., Kraft, A., Harshman, J., & Stains, M. (2021). Changes in teaching beliefs of early-career chemistry faculty: A longitudinal investigation.
Chemistry Education Research and Practice, 22(2), 431-442. doi.org/10.1039/D0RP00313A
Popova, M., Kraft, A., Harshman, J., & Stains, M. (2020). Untangling a complex relationship: Teaching beliefs and instructional practices of assistant chemistry faculty at research-intensive institutions.
Chemistry Education Research and Practice, 21(5), 513-527. doi.org/10.1039/C9RP00217K
Stains, M., Harshman, J., Barker, M. K., … & Young, A. M. (2018). Anatomy of STEM teaching in North American universities.
Science, 359(6383), 1468-1470. doi.org/10.1126/science.aap8892
# 03 / robust statistics
Robust Statistics in Chemistry Education Research
We are passionate about advancing statistical reasoning in chemistry education research and advocate for the use of R, a free and powerful programming language. Our group also collaborates with Jack Barbera at Portland State University and Regis Komperda at San Diego State University on CHIRAL, a centralized resource for chemistry education assessment instruments.
# related publications
Stanbury, D. & Harshman, J. (2019). Large-scale models of radiation chemistry and the principle of detailed balancing.
The Journal of Physical Chemistry A, 123(47), 10240-10245. doi.org/10.1021/acs.jpca.9b07470
Stains, M. & Harshman, J. (2017). A review and evaluation of the internal structure and consistency of the Approaches to Teaching Inventory.
International Journal of Science Education, 39(7), 918-936. doi.org/10.1080/09500693.2017.1310411
Harshman, J., Nielsen, S., & Yezierski, E. (2017). Putting the R in CER.
In T. Gupta (Ed.), Introduction to Computer-Aided Data Analysis in Chemical Education Research (CADACER). American Chemical Society, Washington, DC.
Harshman Research Group 