Mind the gap! Lagging policy support and Academics’ sensemaking and sense-giving of Gen AI applications

Mathew Todres, Yuwei Sun
InSITE 2025  •  2025  •  pp. 08
Aim/Purpose
The purpose of this paper is to review research on the efficacy of Gen AI (GAI) policy and frameworks in Higher Education (HE) teaching and assessment, and to extend our understanding about evidence-based policy and frameworks to understand how academics make sense of and apply GAI, in instances where institutional policy is lacking or lagging.

Background
While recent contributions recognise the importance of evidence-based policy and frameworks to help academics and students navigate AI applications (e.g., Dabis & Csáki, 2024; Temper et al., 2025; Ullah et al., 2024), concerns remain regarding the lack of policy support (Ghimire & Edwards, 2024) and practical training (Kangwa et al., 2025) for educators.

Methodology
Adopting the notions of sensemaking—the process through which people give meaning to their experiences, and sensegiving—the process through which people disrupt their current understandings (Gioia & Chittipeddi, 1991), we examine, ‘How do academics make sense of lagging policy support and training? Furthermore, we examine how and in what cases academics engage in sensegiving to students to fill the gap between lagging policy guidance and leading GAI developments. We conduct 20 interviews with academics based at three Australian universities where there have been notable gaps between GAI policy and GAI training, using thematic analysis to identify coping strategies pioneered by academics working within the gap between policy and practice.

Contribution
This paper contributes to knowledge by offering insights provided by the sensemaking and sensegiving activities of academics in interviews to better understand GAI applications in educational practice and to offer policy development recommendations.

Findings
This paper demonstrates that prior research work has yet to sufficiently (1) evaluate the real-world impact of current GAI policies and guidelines on behaviour; (2) explore how well policies are understood or interpreted by teaching academics; and (3) proposes empirical research gathering insights how faculty navigate the gap between lagging policy and GAI usage and in the classroom and in assessments.

Recommendations for Practitioners
Those drafting policy, regulation and guiding frameworks are recommended to adopt pragmatic evidence-based approach derived from best-practice in the HE industry and via grassroots feedback from formal evaluations and classes - so that academics and students are provided with practical guidance for navigating the challenges and opportunities generated by GAI disruption.

Recommendations for Researchers
As the knowledge base is in a formative phase, researchers are recommended to adopt exploratory research at the grassroots level to shed light on how GAI policy and guidance is understood and applied in the classroom and assessments.

Impact on Society
Universities and the wider HEI sector across the globe will need to accelerate policy and framework updates informed by grassroots practices to catch-up with continuing advancements in GAI.

Future Research
GAI is a major disruptor in HEI (Meadows, 2024) and future research needs to explore how educators relate to, use, and potentially help inform GAI policy and framework development, so that GAI can be applied to enhance educational processes and learning outcomes. Teaching academics serve as a bridge between support policy and actual practice.
AI applications in education (AIEd), generative artificial intelligence (GAI), policy, frameworks, GenAI literacy, sensemaking, sensegiving
19 total downloads
Share this
 Back

Back to Top ↑