Generative AI and Higher Education: Changing Landscape of Assessment and Feedback

To explore these issues and more, Rob Howe, Head of Learning Technology at the University of Northampton (supported by University staff, external colleagues and the National Centre for A.I.), will be running a series of debates and talks on campus and online. These discussions will aim to assess the potential of AI tools and examine their ethical implications. Participants will discuss the challenges and opportunities presented by AI, and debate the best ways to incorporate these tools into the classroom. The perceived ability of these software to ‘do our work for us’ has prompted concern for the implications for academic integrity should students submit AI-generated work as their own.

There are lessons to be learned from the introduction of technology in education in the past. The pace at which we embrace, understand and standardise the use of generative technology should match that of the market that produces these tools. As impossible a task as this may seem, only by engaging and showing the willingness to learn that we expect of our Learners, can we ensure that technology is responsibly utilised to its maximum potential.

Theorizing the Future of Generative AI in Education

This ensures technology fosters meaningful relationships, not hinders them. Educators can also tailor curricula to suit classroom needs, optimizing learning for every student. Deep Learning, part of Neural Networks, handles complex tasks via interconnected layers. Convolutional Neural Networks (CNNs) master images, while Recurrent Neural Networks (RNNs) process text and speech. Layers refine outcomes, empowering Generative AI to improve its content.

• As AI steps in to automate admin tasks, it opens up more time for teachers to spend with each student.
• We want to ensure that the machine helps the human to the level of sophistication required, no more, no less.
• Finally, teaching students about AI in the context of academic integrity, as well as more generally, is vital.
• With AI managing routine tasks and tailored learning, educators concentrate on mentoring, inspiring, and nurturing critical thinking.
• They craft detailed diagrams and distill intricate concepts into clear infographics, amplifying understanding, and memory.
• Picture a learning journey that respects your pace, style, and strengths.

With the judicious use of technology, including generative AI, people can find themselves liberated from administrative tasks, enabling them to focus their energies on innovation and delivering exceptional experiences. For Tutors this means more time for one-on-one interactions, fostering personalised learning journeys that are truly transformative. For Assessment Developers this means more time to consider alternative and innovative ways to assess and differentiate learner attainment. Students have already been trained by our system to think instrumentally or extrinsically about the outcomes of their work. Many focus on getting the essay done, achieving the passing grade, obtaining the piece of paper.

Students should acknowledge all uses of generative AI tools in assessment to avoid academic misconduct

Generative models will then be able to create more effective lesson plans or resources, ensuring better student outcomes. Students are aware of AI tools and will start to use them regardless of what we do. It is also incredibly hard and potentially impossible for a tool to identify if a piece of work has been generated by AI and any tools that do emerge are quickly being made irrelevant due to the speed at which AI tools are improving.

Yakov Livshits

The aim of this special issue is to spark theoretical development and theoretically-informed empirical research about how generative AI may shape socio-technical practices in education. The integration of artificial intelligence (Al) and machine learning (ML) tools in education has been a growing trend in recent years, with a particular focus on the use of large language models for generative AI, such as ChatGPT. While the potential use of generative AI as a  teaching and learning resource has been acknowledged, there is a lack of research exploring how it may influence pedagogy, learning, and authorship. This special issue calls for new research to better understand the impact of generative AI on these areas and the ways it may shape the future of education. Despite these concerns, half of secondary school teachers globally say that the potential of generative AI as an educational tool outweighs the risks. The second video, “Generative AI and Academic Integrity,” continues the conversation with Kaz and Navi, focusing on the academic integrity aspect of using generative AI.

Why Businesses Governments Must Obligatory Embrace Digital Transformation in a Time…

Yet, as with any technological leap, there are nuanced challenges that demand careful consideration. The education community must reckon with the emergence of AI-driven malpractice. As AI can seamlessly create content, safeguarding against potential misuse is critical to its adoption. Schools, colleges, universities, and awarding organisations need to proactively cultivate a culture of responsible use. We must work together to create rigorous mechanisms to prevent malpractice and be proactive to ensure academic integrity.

The full extent of how AI tools will fit into daily academic life is yet to be determined. While some believe that AI has the potential to revolutionize the way in which we teach and learn, others remain skeptical about its ethical implications and its potential to negatively impact student engagement. In terms of how AI might be utilised by academic staff, genrative ai Lee Machado, Professor of Molecular Medicine, describes his use of AI tools in cancer classification and how AI tools might be used to help answer questions in his field. Lee also discusses how he feels AI tools such as ChatGPT could improve student experiences by providing personalised feedback on essays and by simplifying complex information.

But consider for a moment whether their skill could or might even be better demonstrated by summarising, analysing or synthesising information that doesn’t just include primary sources, but the product of generative AI. Is it authentic and relevant to show how they can take the information generated by AI and their own research to demonstrate their analysis across sources? If so, permissive referenced use of generative AI might lead to better outcomes. Its accuracy can be hit and miss, partly based on your prompt, partly based on what it knows and partly on its inherent ability to process data. But there is still a great deal of human skill involved in ensuring that you don’t fall into the ‘Rubbish in, rubbish out’ trap.

It was only when ChatGPT blasted onto the scene at the back end of 2022 that we all suddenly stood up and took notice. “AI breakthroughs are already changing the way we work and its crucial students get the new skills they need to build a fulfilling career. University staff also need support as they look at how AI can genrative ai be used to enhance their teaching and help bring subjects to life. The statement, published today (4 July) and backed by the 24 Vice Chancellors of the Russell Group, will shape institution and course-level work to support the ethical and responsible use of generative AI, new technology and software like ChatGPT.