This NSF-supported workshop was held March 18-19, 2019, on the campus of the University of Michigan in Ann Arbor, bringing together learning and data scientists with various backgrounds and prior expertise to collaboratively solve the research challenges of development of instruction, assessment of competence of current and would-be workers, and evaluation of learning tools.  Three specific questions were addressed: how to define competence, measure competence and evaluate new approaches to learning.  Speakers represented industry and academia to ensure a broad perspective and specifically to take into account employer’s perspectives.

Read more about the discussion topics (pdf)

The workshop was convened through funding from the National Science Foundation Divisions of EHR & CSE, Award #1824998.


Stephanie Teasley, Research Professor, School of Information, University of Michigan

Henry Kelly, Senior Scientist, Michigan Institute for Data Science, University of Michigan

Presentation: Workshop Overview (pdf)

Marie Cini, President and CEO, The Council for Adult and Experiential Learning

Presentation: How Do We Define Outcomes for Higher Education? (pdf)

Bror Saxberg, Vice President, Learning Science at Chan Zuckerberg Initiative

David Blake, CEO, Degreed

Presentation: Degreed Skill Certification (pdf)

Tammy Wang, Vice President, Data Science and Analytics, Riviera Partners

Presentation: Measuring Competence (pdf)

Norman Bier, Director, Open Learning Initiative, DataLab, Carnegie Mellon University

Presentation: Evaluating New Approaches (pdf)

Yun Jin Rho, Director, Efficacy Analytics and Studies, Pearson

Presentation: Learner Profile Analysis: Exploratory and Confirmatory (pdf)

Susan Rundell Singer, Vice President for Academic Affairs and Provost, Rollins College

Presentation: Data Analytics: A Driver for Competency-Based Learning (pdf)