Click here to zoom in for a larger view.
Click “Present” in top right hand to view as full screen.
AAC&U Conference Poster eHandout, 2/11/21
Goodrich, Victoria, McWilliams, Leo, Ambrose, G. Alex (2021) One College’s Experience: Exposing Inequities Caused by Pre-Matriculation Credit Earning Policies. AAC&U Virtual Conference on General Education, Pedagogy, and Assessment: Embracing the Best Emerging Practices for Quality and Equity.
Inclusive Curriculum Analytics for Undergraduate STEM Degrees: Using data to identify barriers, measure outcome disparities, and close achievement gaps
As formal credit earning opportunities grow, such as through credit by examination, it’s imperative that institutions understand how their advanced placement credit acceptance policies shape their students’ experiences on campus. While most schools have focused on how students with advanced credit perform in the follow on classes, fewer have focused on how these policies affect students without the same opportunities. This case study will answer: how do credit acceptance policies shape the student academic experience within one College of Engineering? The poster will focus on how one College of Engineering identified inequities through data driven study of students’ college performance as it relates to their credits earned prior to matriculation. It will provide a roadmap for other institutions to investigate their own student data as it pertains to current policies.
Background, Problem, & Evidence:
More and more students begin college having earned multiple college credits. As formal credit earning opportunities grow, such as through credit by examination, it is imperative that colleges and universities understand how their credit acceptance policies shape their students’ experiences on campus. While many studies have focused on program benefits such as additional schedule flexibility, less time to degree, and exposure to advanced topics, few have quantified the collateral impact of credit earning opportunities on the students that do not have credit when entering college. By not specifically quantifying and understanding this, it is easy to perpetuate or expand an achievement gap that started well before students enter college.
In this session, we will show how one College of Engineering used student performance data to identify and understand potential inequities in existing policy decisions. By accepting credit in required courses, in this case calculus, chemistry and physics, two groups were formed: (1) students that were ahead of the stated curriculum and (2) students that were executing the curriculum as published and expected. Looking at shared courses between these two tracks, such as physics or sophomore level engineering courses, exposed real and concerning disparities in grade performance from this policy. This session will present data from this study and describe a methodology for creating similar data analysis at other schools and within a wide range of programs.
Expanded Figures from the poster:
CoursePathVis is a visual analytical tool for exploring and analyzing students’ progress through a college curriculum using a Sankey diagram. We group students in multiple ways (by their AP courses, term courses, and a user-specified fun-nel course) to offer different perspectives on the underlying data. With these flexible grouping techniques and the funnel-augmented Sankey diagram, CoursePathVis helps us identify patterns or outliers that affect student success.”
Resources & Related Work:
Forthcoming ASEE Article (check back soon)
Bartolini, A.; Running, C.; Duan, X.; Ambrose, G. Integrated Closed-Loop Learning Analytics Scheme in a First-Year Engineering Course. 2020 ASEE Virtual Annual Conference Content Access Proceedings. 2020.
Duan, Xiaojing, Ambrose, G. Alex, Wang, Chaoli, Abbott, Kevin, Woodard, Victoria, Young, Kelley (2020) Learning Analytics for Inclusive STEM Student Success. Learning Analytics & Knowledge Conference. Practitioner Report and Poster. Frankfurt, Germany
Duan, Xiaojing, Ambrose, G. Alex, Wang, Chaoli, Abbott, Kevin, Woodard, Victoria, Schalk, Catlin (2020) PerformanceVis: Homework & Exam Analytics Dashboard for Inclusive Student Success. Learning Analytics & Knowledge Conference. Practitioner Demo. Frankfurt, Germany
Ambrose, G. Alex, Duan, Xiaojing, Abbott, Kevin, Woodard, Victoria (2019) Inclusive Learning Analytics to Improve STEM Student Success. EDUCAUSE Main Conference, Chicago, IL
Syed, M., Anggara, T., Duan, X., Lanski, A., Chawla, N. & Ambrose, G. A. (2018) Learning Analytics Modular Kit: A Closed Loop Success Story in Boosting Students. Proceedings of the International Conference on Learning Analytics & Knowledge
Presenters Bio & Contact Info:
Victoria Goodrich, Associate Teaching Professor, Chemical and Biomolecular Engineering
Leo McWilliams, Assistant Dean for Undergraduate Programs, College of Engineering
G. Alex Ambrose, Director of Learning Research, ND Learning | Kaneb Center for Teaching Excellence
Andrew Craker, Pat Miller, Kevin Abbott, Kevin Barry, Alex Oxner, Augie Freda, Shelin Mathews, Ryan Snodgrass, Keith Mcindoo, Roberto Casarez, Joel Dosmann, Chaoli Wang, Brendan O’Handley, Michael Niemier, Morgan Ludwig and Samantha Allison