A competence based approach to thinking about higher education can offer an answer to the growing conversation about the impact of artificial intelligence (AI) on the future of education, and on assessment in particular.
At the University of Hull our academic portfolio is underpinned by our Competence-Based Education Framework, a deliberate response to the challenges presented by the fourth industrial revolution.
We have defined competence as having the necessary experience, knowledge, and self-awareness to do something effectively. We recognise competence in three domains: knowledge management, disciplinary and professional experience, and self-awareness.
Our framework has been developed to ensure that our graduates leave the university possessing those competences that will support their success as they move forward into further study and/or employment. To achieve this aim curriculum designers ensure that programmes include:
- The disciplinary knowledge required to be successful in their chosen career.
- The technical (disciplinary) role-related skills (e.g. the use of specialist software and/or equipment) and transferable skills (those useful in any role, e.g. communication, teamwork, numeracy) that are essential in their chosen field.
- The personal attributes and behaviours necessary for success (e.g. confidence, resilience, adaptability).
Clearly there are opportunities here for us to embed disciplinary appropriate use of AI within the curriculum to reflect the impact it will have within the work place.
Disciplinary applications
University of Hull graduates are able to source, select and apply disciplinary approaches, knowledge and skills to any given task or practice, and work with autonomy and responsibility.
For students to be able to effectively work with AI, it will be imperative for them to ask the right questions (source), critically analyse (select) and then work with the response (apply) to achieve maximum learning gain.
The same can be said for university educators. AI will have a future in curriculum design, session planning and in marking and feedback, and as a result academics will need to make use of the same competencies.
Professional and workplace applications
“The action and critical thought necessary to address a real-world task/practice in context, be it through working independently or with a team.”
While preparing students for the workplace, it is imperative to provide an authentic experience through the taught curriculum and assessment. AI will affect industries in a variety of ways, and university programmes must reflect this. Students will require the opportunity to practise, fail and develop skills using a range of AI supported technologies in order for them to track their development and identify where their disciplinary knowledge co-exists with any automated content.
Current tools, such as Chat GPT, provide a baseline for content, yet require disciplinary and professional experience to contextualise and draw out the necessary knowledge from real-world scenarios. Therefore, we must find opportunities to connect AI with a culture of criticality and reflective practices to prepare students for the ever-changing work landscape.
Knowledge management
“Source, understand, create and communicate knowledge.”
With the advent of AI generated content, the ability to effectively source and relate relevant materials has become a crucial competency for students. Utilising tools such as ChatGPT effectively, requires an understanding of how to harness its potential, but also an awareness of its limitations when analysing its output.
Effective use of AI has become a literacy in its own right. As a result, it is now essential that we work in partnership with students in developing a shared understanding of the impact in regards to knowledge management.
This conversation must include:
- Appropriate use of tools to generate content
- Appropriate acknowledgement of AI content
- Use of AI to collect and manage resources
- Copyright and intellectual property
Without this, we risk exacerbating the divide in the hidden curriculum, with many students being unaware of the positive possibilities and potential pitfalls.
Self-awareness and personal development
“Self-assessment and regulation in public and private domains, in independent or team working.”
As the sector begins to discuss the impact on assessment strategy, many of the creative ways of integrating AI rely on students’ personal reflections or, within group work, assessing their own performance alongside that of their team. To support this, we need to design a curriculum that allows students to situate themselves within an authentic learning experience and to equip them with the skills for self-reflection.
AI affords opportunities to provide students with personal pathways for development. The ability for a course to adapt to an individual student will rely on them understanding their own areas of strength and where they have room for development.
Linked to this, self-awareness also covers the ability for students to work in collaboration with academics in designing curriculum and learning activities. Providing a space for them to bring their expertise or experience in this area into their own learning.
Inclusivity
Underpinning these conversations at Hull is our commitment to providing an inclusive and sustainable curriculum. There is still work to be done in understanding the ethical underpinning of currently available tools and where it is appropriate for a university to use them. In regards to sustainability, conversations around the carbon footprint required to power the technology should be at the forefront.
A university wide approach is required to ensure that students receive an equitable experience in this area. When looking at current assessment methods, clear communication, regulations and policies can support student’s understanding of how and where it is appropriate to use AI. But there is also a conversation about the wider support that students at all stages have available. For programmes to be able to reflect on where they can integrate AI within their delivery, a similar level of support must be made available to staff.
How AI will impact higher education is unclear but the opportunities that our initial conversations across the sector have established are genuinely exciting. As we support students’ move into a workplace of the future, we hope our competency model, focusing on specific skills and application of knowledge, will give us the flexibility and structure required to provide an authentic learning experience.
Can the author give an example of how students would harness the potential of AI in the context of their higher education please?