Using Logic Models to Organize and Track Student Learning

Abstract

Logic models are powerful tools that extend beyond evaluation to organize systems change and promote project management (Frechtling, 2007). Ultimately, a logic model is a data visualization (Jones, et.al., 2019) that backwards maps a student learning outcome to the activities, inputs, outputs, and theoretical framework(s) so it is clear how student learning is achieved. The University of North Texas (UNT) Department of Student Services Assessment launched a division-wide logic modeling process to teach logic models and to create systematic student learning tracking efforts within the Division of Student Affairs. We use pre/posttest data analysis from UNT staff collected before and after a logic model workshop series done division-wide to show how data literacy is impacted by logic model frameworks.
We will also show the results of eco-cycle planning and systems mapping that connect student learning at a strategic level within the division. We argue why the logic model is a better tool to organize assessment across large systems. We will discuss how logic models can increase data literacy among staff, are data visualizations departments can use to communicate learning outcomes to students and stakeholders and can systematically inform strategic planning. Our logic model framework expands on basic designs to include the UNT Wellness Wheel initiatives, NACE Marketable Skills, and theoretical frameworks that guide each department’s work.
We hope this (neo)new approach to measuring change after interventions contributes to the larger literature on logic models.