An illustration of a robot working at a computer to suggest generative AI and curriculum design.

‘Without change there is no innovation, creativity or incentive for improvement; those who initiative change will have a better opportunity to manage the change that is inevitable.’

William Pollard


Creativity is often triggered by disruption. ChatGPT, and other generative AIs, represent the latest wave of disruption to hit academia. We can either choose to manage that change or be swept away by it.

Generative AI is here to stay. Concerns around cheating and academic integrity have, understandably, dominated the headlines; however, tools like ChatGPT also have the potential to transform how we deliver teaching and assessment. They have the potential to help enhance staff and student creativity through imaginative approaches to course design and content production as well as by providing opportunities for collaboration and personalisation to students.

Generative AI has the potential to be a creative and time-saving disrupter. Academics on Twitter have shown how it is enabling them to enhance teaching and learning, for example through providing feedback on designing learning activities as well as writing learning outcomes and discussion prompts.

 There is no denying that ChatGPT may provide challenges to educators. However, Jay Rayner’s comment in The Observer Magazine that, ‘educational assessment will fall apart because a machine can write an essay as well as any human’ is short-sighted.

In the short term, we should be mindful of making changes to assessment as an immediate reaction to the challenges posed by ChatGPT. Used correctly, ChatGPT could empower students to develop academic skills such as critical thinking and inquiry-based learning skills.

Creative approaches to written assignments can breathe a new lease of life into the traditional essay assessment. Where students are required to produce written essays, they could be given more autonomy in designing questions for themselves or choosing their own topic areas and reflecting on, and evidencing, their reasons for this choice.

Ultimately, students could be required to use AI to generate answers to questions, or produce a written essay, but then be required to critique that output and reflect upon the appropriateness (or not) of the use of AI. This is important: machine learning technology such as ChatGPT should be explored as a method to develop critical evaluation and problem-solving skills - but not be a substitute for them.

We should consider how assessment can be designed in a way that requires students to use their knowledge and skills to solve specific problems or tasks. Such assessments might involve students working with different sub-sets of data, producing presentations in groups to an external audience, working with external partners to solve a specific challenge, group projects developing non-written work that is assessed on originality, for example performance or production-based outputs such as podcasts.

Let’s not forget the value of formative feedback and assessment in curriculum design, which plays a critical role in the process of learning itself and ultimately contributes to student success. We know ChatGPT can provide students with useful feedback. Following the delivery of MDS30021 Podcast and Radio Production module, we tested ChatGTP to investigate how it might have supported the development of student’s own creativity (for example the ideation process, with the aim that students would be better prepared to pitch their idea to an industry panel) with interesting results. However, like any generative AI tool, the quality/usefulness of output will depend on the effectiveness of the questioning, prompting students to improve their inquiry-based learning skill.

However, it is important not to overstate the capability of these tools and we need to be mindful of its limitations and ethical and accessibility implications. Currently, ChatGPT is available free to use but this may not always be the case; due to its nature it can be prone to inherent bias, factually inaccurate and unpredictable. It is still an experimental technology, and our institutional view is that we need to embrace this technology as part of our strategy to enhance teaching and learning innovation at Keele.

*ChatGPT was not used in the writing of this piece.

About the author

Catherine Chambers is Director of KIITE (Keele Institute of Innovation and Teaching Excellence) & Module Lead MDS30021, Podcast and Radio Production, at Keele University.

With thanks to Katie Szkornik, Dean of Academic Enhancement and Mike Lancaster, Digital Learning Producer for their contributions.

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