PGCert and AI

The following narrative is contributed by Maria Cruz Garcia Vallejo.

PGCert and AI: where shall we start?

The rise of Generative AI (GenAI) text-to-text agents, such as, ChatGPT, during the autumn of 2022 sparked debates around AI’s irruption in higher education (HE) worldwide. By spring 2023 in the UK, the institutional approach for most universities was that GenAI should be viewed as an ally, not a threat, to enhance HE learning, teaching, and assessment. This inevitably raised questions for PGCert programme stakeholders:

  • How to harness AI for high-quality, innovative teaching and assessment when training new lecturers?
  • What AI skills and knowledge should teaching staff acquire?

It soon became obvious new and existing staff needed training in these novel competencies, termed ‘AI literacy,’ making PGCert programmes the apt place to upskill lecturers.

What is exactly AI literacy?

A review of academic literature on the concept of ‘AI literacy’ shows that this  is an umbrella term that comprises:

  • The technical and digital skills needed  to use AI multimodal agents (ChatGPT, Claude, Copilot, etcetera) ,
  • Higher order thinking skills (Ng et al 2020), such as critical thinking, problem-formulation and the ability to break down complex problems into smaller, manageable sub-problems (Acar 2023),

In the UK, the introduction of AI in the HE sector has been dominated by two attributes of Anglo-Saxon capitalism: speed and productivity, which is consistent with the dominant business model for universities in the Anglosphere.  Let us consider a different vision of HE: fostering graduates bringing compassion and kindness to society, as supported by many ‘Global South’ universities. That vision supports a conceptualisation of the term ‘AI literacy’ that puts ethics and human wellbeing at its centre. AI literacy can be, then, defined as the critical awareness of the potentiality, limitations, technological, social and ethical challenges that the use of Generative AI models brings to teaching, assessing and researching, in order to prioritise human wellbeing and the adoption of compassion and caring as ethical values when using GenAI systems in HE. 

How can PGCert Programmes develop the AI literacy of new lectures?

When it comes to AI, both teaching staff and students are still learners (Bearman & Ajjawi 2023). This means that there is not a solid syllabus or specific curriculum that PGCert programmes must follow to equip new teaching staff with AI literacy skills.

The topics that I propose address the conceptualisation of AI literacy as an umbrella term that involves digital skills, human-centred considerations, high cognitive processes ,such as critical thinking, and an reformulation of existing digital pedagogies and assessment practices.

  1. A basic understanding of how AI, machine learning and how large language models (LLM) work, including ethical considerations on how those models are trained and the environment impacts of large computational centres.
  2. A familiarisation with the most common GenAI conversational multimodal agents (Copilot, Claude, Gemini, Mistral, etcetera), building digital skills to obtain the most efficient results, such chain-of-thought prompting techniques, ethical jailbreaking and how to formulate complex problems to AI chatbot.
  3. Understanding GenAI’s risks and limitations in HE contexts, like hallucinations, bias, lack of transparency, and access inequalities.
  4. Acquiring a sounding knowledge of ethical and regulatory frameworks for the use of AI in society so that teaching staff enrolled in PGCert programme can foster critical conversations on ethical uses of AI with their own students. In the European Education Area (EEA), the regulatory framework is shaped by the EU AI Act and the provisions that guarantee existing legislation of data protection and copyright within the EU area (which is also followed closely by UK legislation on AI).
  5. A critical examination of the concepts of assessment, academic integrity, intellectual ownership and copyright to support GenAI to enhance assessment. PGCert participants could explore the concepts of authentic assessment, project-based learning or assessment as learning as alternative approaches thar support the use of GenAI to build both the AI and assessment literacy of undergraduate and postgraduate students, instead of using AI chatbots to write down the assignment.
  6. An introduction to the institutional policies, guidance and recommendation on AI that the institution accrediting the PGCert programme may have in place  as well as recommendations from international and national agents such as Jisc, UNESCO, QAA, ectara.
  7. Hands-on learning activities in which PGCert participants can try GenAI as students and, from which get inspired to design learning activities with own students.  Examples of learning activities that can be tried in a PGCert course are:
  • Customising GenAI chatbots as digital assistants and tutors.
  • Assessing the terms of use and privacy policies of the most popular LLM providers (OpenAI, Anthropic, Google) in the light of the provisions included in the EU AI Act and EU GDPR.
  • Course debates that highlight the ethical and social dilemmas of LLM models: for example, the impact of AI on employment legislation, use of copyrighted characters with AI multimedia chatbots, etc.
  • Designing assignments based on real-life projects that students would undertake in their professional areas.
  • Use of GenAI chatbots to customise rubrics and individual feedback.

The introduction of AI in PGCert programme should adopt the approach of an open critical debate where new teaching staff can experiment with these new systems and explore new educational paradigms for teaching and assessment. Explore new assessment method that utilise AI as an ally to support the critical thinking and digital skills of our students also require a strong institutional support for those teaching staff who are willing to consider students as equals in assessment.

References

Acar, Oguz A. (2023) ‘AI Prompt Engineering Isn’t the Future’, Harvard Business Review, 6th June 2023. Available at: https://hbr.org/2023/06/ai-prompt-engineering-isnt-the-future (Accessed: 16th April 2024). 

Bearman, M. and Ajjawi, R. (2023) ‘ Learning to work with the black box: Pedagogy for a world with artificial intelligence’, British Journal of Educational Technology, 54, 1160-1173. Available at: https://doi.org/10.1111/bjet.13337 (Accessed: 19th March 2024).

Ng, D T K, Lok Leung, J L , Wah Chu, SK, Shen Qiao, M (2020), Conceptualizing AI literacy: An exploratory review, Computers and Education: Artificial Intelligence, Volume 2, 100041, ISSN 2666-920X. Available at: https://doi.org/10.1016/j.caeai.2021.100041 (Accessed 20th March 2024)