Academic Integrity in The Age of AI

Academic integrity concerns are an increasingly significant issue for university leadership and faculty due to the widespread impact of AI tools in the hands of students.

However, whilst student assessment is usually the primary concern of academia there are many areas of the student lifecycle and university operations that should be considered.

Our research shows that whilst universities wish to embrace AI as part of both operations and the teaching and learning experience, universities often feel conflicted between adopting AI tools and combating abuse. Likewise, they feel concerned about emergent issues such as bias in data sets and storage of student data.

In the DEC Executive Briefing #002, “Getting Ready for AI'” we proposed a framework for building a Resilient Educational Value Chain throughout a university. Taking a holistic view can enable universities to deal with emerging technologies that are appearing almost daily from AI developers.

Our framework further helps universities consider the potential positive impacts of embracing AI technologies whilst suggesting the adoption of five key principles to build a Resilient Educational Value Chain: Honesty, Trust, Fairness, Respect and Responsibility. 

In the Executive Briefing, we cautioned against relying on AI detection tools as a stop-gap measure and rather invest in processes that build and maintain resilience over time, even as these technologies progress.

Within these processes universities should consider how to build AI-resistant assessments and consider strengthening other processes such as document validation and student identification. They should also create clear rules and referencing guidelines for the use of AI and support teachers and students to use technology to improve the learning experience.

We recommended ways universities can enhance learning over the longer term through providing AI-literacy training to staff and students, consider AI tools that help personalise the learning experience such as Adaptive Learning Platforms and AI-powered tutoring and support and create a collaborative learning environment for students to work together with AI, testing what works and feed positive experiences back into further curriculum and teacher development.

Digital Education Council members have access to examples and case studies for each of these areas.

Universities are encouraged to maintain a posture of continuous evaluation and improvement to both maintain integrity and engage university leadership, operations, faculty, and students in addressing and embracing these rapid developments.

-

The Digital Education Council provides monthly Executive Briefings to its institution members. Our Briefings are designed to provide structured and practical ways to consider today’s issues relating to the use of technology in the world of Higher Education and Workforce Development.

We regularly publish summaries and findings to the public and encourage you to let us know what topics are of interest to your organisation.

‍