KU STEM Analytics program enables teams of faculty to harness institutional data to address questions about teaching, learning and student success.

• Collaboration between Center for Teaching Excellence, Undergraduate Studies, Institutional Research

• 8 department teams, known as STATs

Builds on two initiatives that generated faculty interest in the contributions of individual courses to student progression through the curriculum.

Aims and Background Program Results

Program Impact

The STEM Analytics program has …• Led to a growing interest in the use of institutional data to help

guide curricula.• Helped teams build departmental consensus and shared

responsibility for student learning.• Helped departments broaden their views of curricula and see

connections among courses and curricula.• Fostered STEM department focus on student success, equity

and inclusion.• Generated tool development and changes to institutional

research culture to empower faculty use of data.

Evidence of Downstream Effects. Several departments studied how evidence-based course transformation supported student success and equity in later courses. For example, biology found that transforming the Organismal Biology course led to improved success in the later Genetics course, especially for underrepresented students. More specifically, the number of D’s, F’s and withdrawals dropped 9% overall, and 20% for students from underrepresented minority groups. Conversely, the number of B’s and C’s rose substantially. This finding has helped spread the transformation model further across the biology curriculum.

GOAL: Faculty-Led Course and Curricular Improvements (to Enhance Learning, Retention, Progression, Equity)

TRESTLE &KU Course

Transformation Initiative

KU Learning Outcome

Assessment Initiative

(program-level)

KU STEM Analytics

Working Group

Geol STAT

Biol STAT

PhysxSTAT

Civil EngSTAT

MechEng STAT

GeogSTAT

Math STAT

ChemSTAT

Department-Level: Faculty teams represent their department, empowered to envision and plan curricular changes. Each team received $500 stipend.Autonomy: Teams identify and explore their own questions about students and courses. Scaffolding: Representatives from teaching center, institutional research and undergraduate studies provide data access, guidance and initial analysis.Community: Teams convene 1-2 times a semester to compare inquiries and explore how department curricula interact.Iteration: Teams review data and ask additional questions, allowing ideas to develop over time, informed by evidence and input from other teams.Public Products: A presentation, poster, or actionable plan

A Process of Collaborative Inquiry

Interdisciplinary Discussions Help Ideas Spread

30.1 words

What is the effect of transforming Biology 152?

What is the effect of transforming Biology 152 on the performance of

underrepresented minority students in Biology 350?

What Types of Questions Drew Teams Into This Work?• Common curriculum pathways• Student progress toward

graduation• Effects of course

transformation Initial question Later question

New Insights about Student Pathways. As data analyses raised new questions, the teaching center applied a visual method to evaluating student paths through curricula. Faculty found that those paths were rarely as linear as they thought, as in physics (right).

New Courses and Requirements. After identifying holes or barriers in their programs, departments are rethinking course sequences and course content. For example, geology found that calculus was a key barrier to students’ graduation. After rethinking which math skills are necessary for success in the program, the geology faculty dropped the calculus requirement

KU STEM Analytics: Using Data to Promote Culture ChangeAndrea Follmer Greenhoot, Doug Ward, Joshua Potter, Caroline Bennett, Mark Mort, DeAngela Burns-Wallace

Teams’ questions grew more sophisticated as they gained experience using university data and learned more about their courses and curricula. An example from biology:

376 IterationsTotal research questions created in

“We want what you gave mechanical engineering in the last round.”

Ideas ‘Traveled’ Among TeamsCross-department discussions promoted learning and the transfer of inquiry among departments.

What Themes Became More Prevalent Over time? • Predictors of retention• Diversity and equity in

student success• Success of transfer students.