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Generative AI is a game changer for higher education

As in most areas of society, generative AI presents risks and opportunities for the higher education sector. But regardless of which side of the debate you fall, it will be a revolutionary technology

The world of higher education is undergoing a profound transformation, driven by advancements in technology. Among these innovations, generative artificial intelligence (AI) stands out as a game changer that is reshaping the way educators teach and students learn. Generative AI enables machines to generate content, mimic human creativity, and adapt to various tasks. Generative AI is revolutionising higher education and has potential to transform the entire landscape.

It is probably not surprising to you that the paragraph above was written by ChatGPT.

Higher education is still coming to terms with the whirlwind launch of ChatGPT, which was only released in November 2022. It achieved one million users in just five days.

Working in higher education in a digital and data role inevitably brings great interest in the threats and opportunities for technology in the sector. Discussions with colleagues and peers centre around a number of issues.

Worries and concerns

At first the UK higher education community reacted with fear and concern that generative AI tools such as OpenAI’s ChatGPT would compromise the acquisition of knowledge and allow students to produce assignments on demand without doing the work required to build knowledge acquisition, communication and collaboration skills. 

Working with plagiarism tools - ubiquitous for plagiarism checking in UK higher education - has helped to develop capabilities to check for the use of generative AI (GenAI) in written student assignments, However, based on our experience at the University of East Anglia, there is a risk of false positives when these tools are being used to assess for the use of generative AI. 

Fortunately there was some rational thinking among sector leaders in the Russell Group of universities when in July they published five clear principles for the use of AI in education:

  • Universities will support students and staff to become AI-literate.
  • Staff should be equipped to support students to use generative AI tools effectively and appropriately in their learning experience.
  • Universities will adapt teaching and assessment to incorporate the ethical use of generative AI and support equal access.
  • Universities will ensure academic rigour and integrity is upheld.
  • Universities will work collaboratively to share best practice as the technology and its application in education evolves.

The future is bright

We are all clear that the use of GenAI presents opportunities and the sector should be encouraging and supporting students to find ways of using these tools to enhance their learning and equip them to enhance productivity and creativity in their future careers. Some of the opportunities being considered can be enabled in higher education.

Accessibility is improved for students when using GenAI applications to translate difficult concepts and when English is not students’ first language. GenAI also supports the creation of more personalised learning plans for students, generating ideas and synthesising information, and summarising a vast amount of text data to help researchers. 

Further opportunity comes in academic teaching and learning assessment. Tools such as the Intelligent Essay Assessor can be used to grade students’ written work and provide feedback on their performance, shortening the time needed for grading, and ensuring consistency in scoring.

What do students think?

Early academic research suggests student views on GenAI are mixed. In their study of student perceptions, Students’ voices on generative AI: perceptions, benefits, and challenges in higher education, Cecilia Ka Yuk Chan and Wenjie Hu from the University of Hong Kong found a complex and nuanced picture of students views, showing both enthusiasm and concerns.

They found that overall, the student participants showed a good understanding of the capabilities and limitations of GenAI technologies, as well as a positive attitude towards using these technologies in their learning, research, and future careers. However, there were also concerns about the reliability, privacy, ethical issues, bias in the responses generated and uncertain policies associated with GenAI, as well as its potential impact on personal development, career prospects, and societal values.

What next?

Like any digital or data technology, GenAI is fast moving and something new is emerging in functionality every day. There is great potential to further enhance the student experience, academic teaching and research. For example: Conversational assistants where GenAI is linked to AI assistants will help students' wellbeing and provide an educational coach available 24x7. Real-time language translation and interpretation offers much wider reach and revenue for the sale of online short courses, undergraduate and postgraduate degrees online. Creative collaboration where GenAI is a creative collaborator for artists, writers, and musicians, helping them brainstorm ideas, generate artwork, or compose music collaboratively.

We know that any emerging technology will have its advocates and adversaries. GenAI has accelerated the debate about the power of AI to do good in society and the power to deceive, create powerful cyber security attacks and do things we normally read about in apocalyptic novels. GenAI will accelerate the advancement of knowledge and productivity in society and will need checks and balances that protects society from those bad actors who have malicious intent. The world of higher education is a microcosm of that wider societal debate.

Sean Green is director of digital and data at the University of East Anglia.

Read more about generative AI

Infographic: How organisations are using generative AI in EMEA - An ESG survey found substantial activity underway, with 42% of organisations using GenAI for business and IT use cases and 43% currently in the planning or consideration phase.

How different industries apply generative AI - Large language models such as ChatGPT, Bard and Llama have changed how enterprises think about technology. While some can use new AI tools now, others face challenges.

We have lift off… The opportunities and risks of generative AI - How you can use AI to benefit your business while navigating the risks.

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