Publication Details

Keywords: artificial intelligence, institutional policy, higher education, conversational coding, professional development

Higher education (HE) professionals with limited technical or coding experience can now use generative artificial intelligence (AI)-assisted coding tools to create software applications; the recent availability of these coding tools likely impacts the HE workforce that leverages institutional data to meet stakeholder needs and solve organizational problems. In this paper we examine policy considerations culturally, organizationally, and operationally through the lens of a combined design-based research (DBR) and theoretical analysis applied to a proof-of-concept (POC) survey data collection web application built with conversational language. The step-by-step process arrived at a functional POC and revealed practical possibilities for HE workforce development policy. Specifically, from an organizational perspective, HE professionals with limited coding experience could use AI-assisted tools to create software (e.g., tools, interface driven) that addresses the challenges they face in their work. Operationally and culturally, POC alignment to real-world HE problems and their iterative refinement could help meet stakeholder needs via a practitioner-driven approach that would have been technically inaccessible before the development of generative AI.

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