This paper reports the design, administration, and preliminary results of a brief student survey instrument developed to measure sustainability learning outcomes in courses taught by faculty participating in the University of Texas at Arlington (UTA) Engineering for One Planet (EOP) Institutionalization Program. The program’s original semester-long Sustainability Professional Learning Community (SPLC) proved difficult to scale during Year 1, and in Year 2 the team centered faculty development on a two-day Sustainability High Impact Practices (SHIP) bootcamp that was opened to faculty from any discipline. That pivot created a measurement problem: how to evaluate student-level impact in a large, heterogeneous set of courses without adding substantial burden on faculty or students.
To address this, we developed a 15-item survey organized into five constructs: Awareness and Exposure; Relevance and Learning; Knowledge and Definitions; Engagement and Behavior; and Overall Impressions. We administered the survey in Fall 2025 through SHIP-trained instructors in approximately ten courses spanning engineering, computing, and other disciplines. We obtained 246 responses from an undergraduate population that is 45.6% Asian, 25.2% Hispanic or Latino, 13.1% Black or African American, and 46.5% first-generation college students.
Across the sample, 80.3% of students reported that their instructor included sustainability content, 68.5% rated that content was moderately or very relevant to their career, and over 70% reported that the material made the course more engaging. Goal 9 (Industry, Innovation and Infrastructure) was the most frequently recognized Sustainable Development Goal (SDG), with Goals 6 and 11 close behind. An initial large language model (LLM)-assisted thematic analysis of open-ended responses identified three recurring themes: real-world application, hands-on project work, and a broadening of students’ definitions of sustainability beyond environmental concerns.
We report these findings alongside a set of item-level validity concerns the pilot surfaced, and we describe a planned validation pipeline that includes confirmatory factor analysis, human–LLM inter-rater reliability testing, and demographic disaggregation across cohorts. The results suggest that brief, course-embedded instruments can produce useful, comparable evidence of sustainability learning outcomes across disciplines, and they provide a foundation for the continued instrument development the program will undertake as it scales. An updated Spring 2026 dataset is being collected and will be incorporated in future work.
http://orcid.org/0000-0003-0559-4699
The University of Texas at Arlington
[biography]
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