Leveraging generative AI for future-proof student assessment

The integration of cutting-edge technologies, such as generative artificial intelligence (GenAI), lies at the forefront of the rapidly shifting landscape of higher education. Indeed, GenAI, with its ability to create diverse content, is the current driving force of an educational revolution, which promises to redefine the parameters of student assessment.

Much has been made of the challenges that AI poses to education, with concerns raised about academic integrity, the robustness of existing assessment practices and cognitive disengagement, as students offload their learning to AI tools.

Much less has been made of the exciting possibilities that this technology offers educators in generating bespoke learning resources and offering personalised learning journeys for students. Its transformative potential to enhance assessments as yet remains under-explored.

A pivotal role for AI

At its core, the purpose of assessment is to provide a standardised measure of comprehension, critical thinking and the ability to apply knowledge – all competencies that are crucial in the graduate workplace where the use of AI is becoming more prevalent.

GenAI can, therefore, play a pivotal role in diversifying assessment methods that accurately evaluate these competencies.

One of the salient features of GenAI is its ability to create unique and varied problem sets, which can be instrumental in assessing students’ critical thinking and problem-solving abilities.

For instance, AI can design scenario-based tasks that require students to navigate through complex, multi-layered problems, similar to those they might encounter in their professional lives. Such assessments not only test the student’s knowledge but also their agility in applying it to unfamiliar situations, a skill highly valued across industries.

Moreover, generative AI may revolutionise the assessment of creative and design-oriented disciplines. Through generating a range of scenarios, case studies and design challenges, AI can prompt students to demonstrate originality and innovation, traits that are indispensable in many fields.

This is not to supplant the role of educators but to augment it, allowing them to focus on mentoring students and providing developmental feedback rather than the laborious task of creating assessment content.

A customised approach to assessment

Personalisation is another cornerstone of GenAI’s utility in assessments. AI algorithms can adapt to the learning patterns and performance of students, offering customised assessments that can more accurately reflect an individual’s understanding and capabilities.

This level of personalisation ensures that assessments are fair and inclusive, catering to diverse learning needs. The data gleaned from such personalised assessments can provide invaluable insights into the learning process, informing curriculum development and teaching strategies. Essentially GenAI can become the 24/7 tutor that would allow Bloom’s Two Sigma Problem to be solved.

Towards process-oriented outputs

The advent of GenAI has also brought into sharp focus the importance of academic integrity. As students have access to AI that can generate essays and solve equations, the traditional modes of assessment may become obsolete.

In response, educators must harness the same technology to develop sophisticated assessments that can distinguish between AI-generated work and genuine student output. This could involve a shift towards assessments that prioritise documenting the process by which the final product is reached rather than the actual product itself. These process-orientated rather than product-driven outputs will compel students to engage deeply with the subject matter.

In this same vein, GenAI can aid in the assessment of soft skills such as teamwork, communication and ethical reasoning through simulations and role-playing exercises. Such AI-driven assessments can mimic working world interactions, requiring students to employ empathy, negotiation and decision-making skills. AI competencies are not only vital for the student’s personal development but are also highly sought after by employers.

A continuous learning mindset

Furthermore, the use of GenAI in assessments can lead to the development of lifelong learning skills. The ability to interact with AI and leverage it for problem solving fosters a mindset of continuous learning and adaptability.

As students learn to co-create with AI, they will develop a symbiotic relationship with technology, preparing them for a future where human-machine collaboration is likely to be the norm.

The implementation of GenAI in assessments does necessitate a shift in pedagogical paradigms. It requires educators to become facilitators and co-learners, engaging with AI to curate and refine assessment strategies.

Institutions must invest in training and infrastructure to fully realise the benefits of this technology. Moreover, a collaborative effort involving policy-makers, educators and technologists is essential to establish guidelines that ensure the ethical and effective use of AI in assessments.

The integration of GenAI into student assessments holds the promise of a more dynamic and relevant educational experience. By aligning assessments with real-world applications and the future demands of the graduate workplace, GenAI can help prepare students not just to succeed in assessments, but to excel in their professional lives.

As we stand on the cusp of this educational revolution, it is incumbent upon the higher education sector to embrace these technological advances and drive the change towards a future where assessments are not merely a measure of memory, but a genuine reflection of a student’s potential to innovate, adapt and thrive in an ever-changing world.

The discourse on the use of generative AI in higher education assessments is not just about keeping pace with technology but about reimagining the future of learning and assessment in profound and exciting ways. As we move forward, it is this vision that will shape the next generation of learners and leaders. After all, as educators, we have an obligation to prepare students for the reality of their futures, not what we would like those futures to be.

Dr Nigel Francis is an award-winning lecturer based in the school of biosciences at Cardiff University, Wales, United Kingdom. He was awarded the British Society for Immunology’s Teaching Excellence Award in 2020, the Royal Society of Biology’s Higher Education Bioscience Teacher of the Year award in 2021 and received his National Teaching Fellowship in 2022. Within the school of biosciences, he is the school’s lead for digital education, which encompasses the use of generative artificial intelligence in assessments. This article is linked to Francis’ participation in the European University Association’s European Learning & Teaching Forum on 8-9 February 2024.