A Framework for Integrating Generative AI into

Career and Employability Practices in Higher Education

Whether you’re looking to upskill staff, refine employability practices, or design GenAI tools for students, CAREERGenAI offers a scalable foundation. It aligns with institutional digital transformation agendas while protecting human-centred, reflective practice.

🎯 Why CAREERGenAI?

“We maintain no current GenAI framework exists to support the needs of frontline colleagues working to enhance student employability.”

Higher education is facing dual pressures:

Equip graduates with practical, future-focused skills.
Empower staff to adopt and adapt to advanced technologies like GenAI.

CAREERGenAI bridges this gap, offering a structured, ethical, and practical approach to integrating GenAI into employability services — without sacrificing student-centred values.

⚙️ How It Works

The framework is built on three foundational pillars:

(1)Pedagogy
Informed by adult learning theories and experiential learning (e.g., Knowles, Kolb, Deci & Ryan).

(2)AI Prompting
Emphasises effective, structured prompting using methods like Retrieval-Augmented Generation (RAG) and Chain of Thought (CoT), supporting staff to generate high-quality, context-rich AI outputs.

(3)Ethics
Aligned with global standards from UNESCO and the UK Department for Education, ensuring AI is used responsibly and transparently in career support.

🧭 Why This Matters

💡 Better prompts = better outcomes. CAREERGenAI helps staff move from vague AI queries to clear, evaluative, and pedagogically grounded prompts. This has the potential to better:

Reduce LLM errors & hallucinations
Improve student guidance quality
Enhance staff confidence & digital fluency
Encourage ethical use of AI in HE settings

🧩 See It in Action

CareerGenAI Framework Converter

This form will guide you into crafting a prompt using the CAREERGenAI Framework. You will get both the response and an improved version of the prompt.

[Clarity] Who is your audience and what are they studying? What is the skill level of your audience? What do you need to create for these students?

[Applicability] What frameworks could you use to increase the output’s quality? Is there any additional data you would like to be considered within the response?

[Reasoning] Do you want more clarity in the examples you have requested? Do you need the response to make links to any particular industry or career pathway? Request a rationale for the response.

[Engagement] How would you like the LLM to engage with your query? What are your expectations regarding its engagement with you?

[Evaluation] How would you like the response to be presented? Do you need to ask the LLM to validate any answers or provide further evidence for its recommendations?

[Relevance] What is the overall objective of the prompt? What would you need the LLM to make sure of overall in terms of context?

AI Settings

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Framework Authors

Cato Rolea

Assistant Director for Digital Transformation , ECCTIS

Dr Tom Newham

Senior Lecturer, Nottingham Trent University

Dr Claudia Bordogna

School Employability Manager, Nottingham Trent University