Presenter:

Ethan Ake-Little PhD: Executive Director, AFT Pennsylvania

Ethan Ake-Little’s career spans both K-12 and higher education. Prior to his role at AFT Pennsylvania, he was a Research Assistant at Temple University, where he supported program evaluation efforts of the General Education Program. He has authored several studies on teaching and learning as well as education policy, reviewed for academic journals, and published commentary in outlets such as The Philadelphia Inquirer, Education Week and The Chronicle of Higher Education. Before higher education, Ethan was as a high school biology teacher in urban charter and suburban independent school settings and currently teaches statistics in the University’s Executive Ed.D. program.

Presenter:

Dana Dawson: Associate Director of the General Education Program, Temple University

Dana Dawson is an award-winning instructor with eighteen years of experience in higher education teaching, research, and administration. Prior to joining the General Education program, she taught for Temple University’s Intellectual Heritage Program and launched the Office of Scholar Development and Fellowships Advising. She holds an MA in Social and Political Thought from York University (Toronto, ON) and a BA in Sociology from the University of Lethbridge (Alberta).

Description:  

Collecting and analyzing data has become an inescapable aspect of the workplace from healthcare to politics. However, the prospect of data-driven decision making in higher education has elicited a range of reactions from instructors who fear their teaching will be reduced to a numbers game to administrators who believe that data analysis will solve their most vexing academic problems. In this pre-conference session, we will explore not only how quantitative and qualitative data can be used to support program evaluation but also the inherent strengths and limitations of each analysis. Using the Temple University General Education Program as a case study, we will:

1. Eiscuss the appropriate use of quantitative and/or qualitative analysis in relation to its need;
2. Provide examples of data analysis employed by the GenEd Program ranging from the charts and graphs to rubrics and focus groups and even complex statistical modeling;
3. Consider ways in which this data can be used to close the loop between data collection (assessment) and program improvement (teaching and learning), especially in service of faculty professional development, and;
4. Reflect upon how the GenEd Program used data to inform institutional policy in the wake of its 2020 Middle States Accreditation review.

Learning Outcomes:

At the end of this workshop, participants will be able to:

1. Recognize which data types and methodolgies are an appropriate fit considering the question(s) asked.;
2. Examine data analyses derived from supplied student artifacts and institutional data;
3. Understand the benefits and limitations of data analysis in promoting programmatic and institutional change.