New principles on use of AI in education

The Use of Generative AI In Education Realising Teaching Excellence

If we embrace and educate around AI as a digital skill then we can close this divide. In the image below you can see the probability the bot has given to the most likely words and it will use this to generate its response. Generative AI encompasses AI driven tools that can generate content which could take the form of text, images, video, audio, code or other forms. Developed in partnership with AI and educational experts, the new principles recognise the risks and opportunities of generative AI and commit Russell Group universities to helping staff and students become leaders in an increasingly AI-enabled world.

It has revolutionized education, offering tailor-made learning materials and opportunities for exploration. Not all colleges are at the same level of understanding when it comes to generative AI and it’s the responsibility of organisations such as Jisc to help bridge that knowledge gap to upskill staff and limit the risk of students being left behind. Without greater understanding of how generative AI works and what it can (and can’t) do, there is a risk that educators and students alike may be using tools that are not fit for purpose, or not using them to their best advantage. From an educational perspective, the rapid emergence and the wider implications of this technology may appear daunting. The key thing is not to panic, but to embrace the opportunities while understanding the challenges.

Centre for Innovation in Education

We invite theoretical papers and theoretically-informed empirical studies that explore emerging practices and offer new imaginings of generative AI in education. Papers may use a variety of methodological approaches including feminist, critical, new materialist, interpretive, qualitative, rhetorical, quantitative, or experimental. Generative AI is here to stay, but teaching and learning is an area where higher education institutions can shape the international agenda for its use. Ministers want to get a handle on how generative AI is being and could be used in education providers as well as any risks, ethical considerations and training needed for staff. Perhaps most importantly, we should teach criticality and caution around AI, and acknowledge the complexity of the present moment. Talk with students about the confusion, the ethics, and the potential harms.

This process is automated by using the ChatGPT API with a detailed prompt (Figure 2b) and integrated it into the student’s existing workflow. By doing this we can now teach our engineering students how to reflect and evaluate their code based on a research-informed code review checklist (Figure 2a). Finally, teaching students about AI in the context of academic integrity, as well as more generally, is vital. We need to create environments that emphasise and nurture academic integrity, reducing motivations to breach it. Some teaching points could include the importance of claiming authorship only over original work, transparency in how student work is produced, and the shared values of academic integrity among university communities.

It can match quality in listing facts, detailing procedures, and preparing presentations. There are no reliable countermeasures for catching ChatGPT-generated text. Higher education can no longer verify the skills and capabilities of a given student with existing formats of asynchronous assessments such as homework and take-home exams. Conversations around academic integrity and the ethics of producing your own work are a hot topic across students, faculty, and staff.

Collaborative Learning between Humans and AI

Findings will be disseminated later this year, however an example of the output from ChatGPT can be seen in Figure 3. In our initial trial, results from ChatGPT are displayed inside a revision management system (GitHub). By doing this we did not change the current development process that is adopted by most engineering students. One major advantage of doing this means that a student doesn’t need to sign up for, or learn how to use, ChatGPT before they can get useful feedback on their work.

• We’re seeking views on how generative artificial intelligence (AI) is being used across education in England, and the opportunities and risks it presents.
• Nonetheless, generative AI is here to stay and we cannot avoid or delay adapting our approaches to accommodate it.
• Responsible regulation, transparency, and addressing student concerns are essential as we shape the future of AI in education.
• Responsible use of generative AI can provide us and our students with many opportunities.

If all of us are using generative AI, perhaps subconsciously as it becomes deeply embedded in applications, then it tends to suggest authenticity in assessment should trend the same way. Failure to declare the use of AI, which results in the work appearing to demonstrate greater attainment against the assessment criteria than is the case, is academic misconduct. Likewise, so is the use of copying or paraphrasing AI-generated content without reference. We will be updating the academic misconduct policy over summer 2023 to be more explicit about this.

To summarise, the journey of AI in education is an evolutionary voyage that offers the promise of enhanced learning experiences and more effective and efficient processes. By responsibly harnessing AI, we can usher in an era where education becomes a beacon of progress, harboured in both innovation and ethical responsibility. The other common concerns in the field include ethical issues related to student privacy, data security, and algorithmic bias. Governments across the world are making consistent efforts in formulating appropriate policy responses in this rapidly evolving landscape – further developing or refining national strategies on AI, data protection, and other regulatory frameworks. As AI continues to rapidly advance, educators are compelled to reassess the fundamental purpose of education in this new technological landscape. They are grappling with the profound implications AI brings to classrooms and considering how to adapt their teaching methods to prepare students for a future where AI is increasingly prevalent.

Founder of the DevEducation project

What are the dangers of bringing AI like ChatGPT into schools?

It’s essential to balance AI integration and maintaining the human touch in education. Ensuring fairness, consistency, and transparency in grading is a challenge. Additionally, maintaining a balance between constructive feedback and human touch is essential.

Equipping staff with a clear basic understanding of how these tools work and giving them the time and training to experiment for themselves can help lessen the load and boost creativity. By completing routine tasks such as lesson planning, schemes of work and resource creation in a fraction of the time it would otherwise take, they allow teachers to prioritise education over admin and help them to be more effective in the classroom. Those placing all their eggs in the AI detection tool basket run the risk of missing instances of AI-generated content or of falsely accusing students of cheating.

AI can drive efficiency, personalization and streamline admin tasks to allow teachers the time and freedom to provide understanding and adaptability—uniquely human capabilities where machines would struggle. By leveraging the best attributes of machines and teachers, the vision for AI in education is one where they work together for the best outcome for students. Since the students of today will need to work in a future where AI is the reality, it’s important that our educational institutions expose students to and use the technology. Here, AI literacy is understood as “a set of competencies that enables individuals to critically evaluate AI technologies, communicate and collaborate effectively with AI, and use AI as a tool online, at home, and in the workplace”2. Students were made aware they should not use ChatGPT in the review of confidential code nor should they share private information in their prompts (code with personal comments or data from real users). Students were also encouraged to critically review received feedback from ChatGPT.

Like the brain, they spot patterns, powering Generative AI’s creativity. Many of our guides, resources and events are open to everybody to view and attend, and we are always open to conversations about our approach. Video guides on small to larger scale changes to make in your assessment setting. Nancy W. Gleason, Phd is the Director of the Hilary Ballon Center for Teaching and Learning at NYU Abu Dhabi. Her research focuses on the Fourth Industrial Revolution’s impact on higher education, employment disruption, and upskilling of adults. She is the editor of Higher Education in the Era of the Fourth Industrial Revolution (Springer, 2018).

Synthetic data creation is one of the leading use cases for generative models in other industries. As AI becomes increasingly prominent in schools, this data generation will become more important. Generative AI’s potential is immense, with some experts predicting it’ll account for 10% of all data generated by 2025.

While the concern is real, where does that leave educators when considering assessment authenticity? Keep your hand up if you’ve used it to help you with a real-world task rather than asking it to write you a rap about the value of student feedback. If you haven’t used generative AI, then I’d encourage you to do so in order to see what it is and – just as importantly – isn’t capable of doing. Much of the discussion in the area of genrative ai and assessment has been to quickly consider how candidates can be prevented from misusing it.

It may seem like generative AI has been a hot topic in education for quite a while now, but it was only with the introduction of OpenAI’s ChatGPT at the end of 2022 that the conversation really started to ramp up. Other generative AI tools are emerging, such as Bing’s ChatGPT-powered search capability and Google Bard, Alphabet’s equivalent project. Additionally, there are code generators like GitHub Copilot, text-to-image tools such as DALL-E 2 and text-to-speech tools like Murf.ai and Speechify. There are no simple answers and our response will require constant review as generative AI continues to evolve. None of the information on this website is investment or financial advice. The European Business Review is not responsible for any financial losses sustained by acting on information provided on this website by its authors or clients.