This dissertation in practice explored how College Zeta, a publicly funded postsecondary institution in the Alpha Community College System, could improve its use of student learning outcome (SLO) data to evaluate the effectiveness of its programs and achieve its mission of offering transformative student learning experiences. During its 2023 accreditation cycle, College Zeta identified the underutilization of SLO data as a barrier to evaluating instructional quality and program effectiveness. Guided by the performance improvement human performance technology (HPT) model, this action research study followed a systematic process to identify, analyze, and address the root causes of the institution’s inability to assess student learning outcomes effectively. This mixed methods study was conducted over the Fall 2022, Spring 2023, Summer 2023, Fall 2023, Spring 2024, Summer 2024, and Fall 2024 terms, collecting and analyzing data from key documents, faculty focus groups, interviews with administrators at the site and system levels, and over 1,100 active and documented SLOs.
Findings from this analysis indicated that over 90% of College Zeta’s SLOs did not clearly communicate the targeted skill level; lacked observable, measurable outcomes; or used subjective evaluation criteria. Chevalier’s (2003) updated behavior engineering model (BEM) framed the root cause analysis, which revealed that over 70% of the factors contributing to the institution’s performance gaps stemmed from environmental performance drivers, including a lack of clear expectations and processes, inconsistent procedures, and an absence of relevant guides and exemplars to improve performance. These factors may also have contributed to misalignment in the institutional culture. The identified root causes—high numbers of unassessable SLOs, the absence of metrics in key institutional planning documents, and a culture misalignment—negatively impacted College Zeta’s efforts to achieve its mission.
These findings led to the design and development of a solution set comprised of three high-impact, low-cost tools, including:
• Continuous improvement metrics to guide transparent, data-driven SLO development, student assessment, and curricula revision processes,
• An electronic performance system (EPSS) and custom generative pretrained transformer (GPT, i.e., an artificial intelligence-powered faculty assistant to aid in developing observable, measurable SLOs, equitable assessments to yield actionable data, and aligned curricula to support student learning),
• A LO-SLO dashboard (i.e., a real-time analytics tool designed to give faculty leading indicators for instructional improvement).
Although College Zeta’s president declined to proceed with a pilot implementation of these tools, expert formative evaluations confirmed the theoretical alignment with HPT, universal design for learning (UDL), and student-centered assessment principles, as well as the practical viability of the proposed solution set. The full-scope evaluation model (Dessinger & Moseley, 2004, 2006, 2010) was the theoretical framework for the formative and proposed summative and confirmatory evaluation processes.
This study contributes to the field of instructional and performance technology by offering a replicable model for performance evaluation and improvement in postsecondary education. The provided interventions are high-impact, low-cost solutions that administrators and faculty can use to support student success-focused reform, enhance instructional coherence, and cultivate a culture of meaningful data use. Most importantly, this study’s findings underscored the critical role of organizational culture, leadership, and systems alignment in achieving student-centered outcomes in postsecondary education.