AI in Apprenticeship Curriculum Design: Actual Examples

Back in September, the University of East London (UEL) went through its first full inspection from Ofsted for its apprenticeship provision. As an academic quality assurance professional, one of the things I was most passionate about demonstrating was high-quality course documentation, specifically our course and module specifications.

During an Education and Skills Funding Agency compliance monitoring exercise in 2023, one of the questions we were asked by auditors was how UEL documents the apprenticeship content in our Training Plans:

"How do employers and apprentices know from day one what they will be learning and when?"

For UEL, we explained that our apprenticeship module content undergoes very rigorous validation processes — typical of any UK university — and we commit to ensuring this level of rigour is applied to our apprenticeship provision.

In our module specifications (you might know these as module narratives or unit specifications), we document what the learning outcomes are of the module, how they will be assessed, and what teaching and learning methods will lead an apprentice to achieve success on the module. Our module specifications are appendices to our Training Plan; they provide the level of detail all parties need to understand how the apprenticeship will be delivered.

However, a challenge we faced during our Ofsted inspection was that, while our module specifications comprehensively covered the learning outcomes at every stage of our apprenticeships, there was a lack of clarity on the role of the employer in supporting apprentices to achieve their learning outcomes while the apprentices were in the workplace.

This felt like such an obvious oversight at the time, and I think draws upon the modern university mindset to take full accountability for student success (something I recently explored in my master's dissertation). On reflection, the accountability universities hold for apprenticeships is to ensure that employers are equally complementing teaching and learning in the workplace by facilitating opportunities to apply practical study, and universities need to set these expectations in their course paperwork.

This oversight also made me harken back to feedback I often receive from my academic colleagues who share that employers often misunderstand that through the "day release" model alone, a professionally competent apprentice can be made.

However, the dilemma for UEL and no doubt for any university is that we work with a large pool of employers, of varied sizes, and operating across different sectors. How can we mandate workplace teaching and learning methods that are going to apply to every employer?

For UEL, 2024 is the YEAR OF SCIENCE and following The Quality Assurance Agency for Higher Education Quality Insights Conference 2024 and a workshop on the future of AI in higher education, I recently started wondering how artificial intelligence (AI) could support apprenticeship course design at UEL, specifically to address this issue around the role of employers in teaching and learning. Furthermore, how could UEL document teaching and learning methods that any employer could implement, applicable to both employers we already partner with as well as those in the future?

This month, I analysed all 242 modules at UEL that are validated for delivery to our apprentices. Starting with the module learning outcomes, I began exploring how generative AI could "fill in the blanks" as far as the role of employers in supporting our apprentices' successful module achievement. For the sake of brevity, I have included a case study below of two of these modules, one delivered to our level 6 Digital and Technology Solutions Professionals and one delivered to our level 5 Nursing Associates: two of the most popular higher/degree apprenticeships nationwide.

How can employers build on teaching and learning delivery at university?

One of UEL's modules on our award-winning Digital and Technology Solutions Professional apprenticeship includes a module on database management systems (DBMS). Using the module specification, I wrote the following prompt into ChatGPT :

I am going to write the learning outcomes of a module on a university apprenticeship course. Based on the learning outcomes, complete the sentence:

"In the workplace, employers will be expected to build on teaching and learning delivered by UEL by…".

Make the result two sentences long with a maximum of 70 words. Define activities for the apprentice which the employer will facilitate in the workplace.

The learning outcomes are as follows:
[COPY-PASTE MODULE LEARNING OUTCOMES]        

Let's refer to this initial ChatGPT prompt as "phase one". For the DBMS module, the following result was produced in phase one:

"In the workplace, employers will be expected to build on teaching and learning delivered by UEL by ensuring that employees can describe and evaluate the structure and principles of a relational DBMS."

Additionally, UEL's largest apprenticeship is our level 5 Nursing Associate course. In a level 5 module that focuses on ensuring patient safety, I wrote the same prompt, to which ChatGPT generated the following result for phase one:

"In the workplace, employers will be expected to build on teaching and learning delivered by UEL by encouraging apprentices to actively appraise safety and quality principles, involving patients and families in care decisions, and fostering critical thinking to support diverse individual needs."

What specific tasks can employers set for apprentices?

While the ChatGPT results above can a general indication of how employers could support teaching and learning, they didn't specifically give an example of what employers could do to support teaching and learning. Based on the results from the earlier prompt, I decided to implement phase two:

You said:

"In the workplace, employers will be expected to build on teaching and learning delivered by UEL by [RESULTS FROM PHASE ONE]."

What is an example of a responsibility an employer could give their apprentice to effectively demonstrate this? The apprentice is not at full occupational competency so may require mentoring from their line manager.        

For the Digital and Technology Solutions Professional DBMS module, the following result was produced in phase two:

"Task: Collaborate with the IT department to analyse your organisation's existing database structure and functionality. Document your findings, identifying areas for improvement or optimisation. With support from your line manager, propose potential modifications or enhancements to enhance system efficiency and data integrity. Draw upon your UEL training to deepen your understanding of DBMS principles and best practices."

For the Nursing Associate patient safety module, the following result was produced in phase two:

"Task: Shadow a senior member of staff during a patient consultation/procedure. Actively observe their safety protocols and quality standards in practice. Engage with the patients and their families to gather feedback on their care experience, ensuring their voices are heard and incorporated into care plans. In collaboration with a workplace mentor, undertake a quality improvement initiative by analysing feedback data to identify an area for enhancement and propose a solution to address diverse patient needs."

What's worth noting here is that this guidance is all based on generic prompts not tailored to any specific organisation. I would be interested to see, following a similar method, if employers were to copy-paste the job description of their apprentices into ChatGPT, how they might create more tailored, organisation-specific examples of tasks and responsibilities apprentices can be set to demonstrate the learning outcomes of their university modules.

Taking it one step further: meeting Ofsted requirements

As part of the Ofsted Education Inspection Framework (EIF), apprenticeships must embed the four Fundamental British Values (FBV) of Rule of Law; Democracy; Individual Liberty; and Respect and Tolerance. A common query I often deal with, particularly during the validation of new apprenticeships at UEL, is how academics can integrate FBV into their curriculum design. This typically results in me having to get quite creative, however, I wondered whether ChatGPT could accurately interpret this too. Using the same tasks set in phase two, I implemented phase three:

Explain how the following task exemplifies the four Fundamental British Values of the rule of law; democracy; individual liberty; and respect and tolerance:

"[RESULTS FROM PHASE TWO]"        

For the Digital and Technology Solutions Professional DBMS module, the following result was produced in phase three:

• Rule of Law: By analysing an organisation's existing database structure and functionality, an apprentice will observe the legal and regulatory frameworks which govern data management.
• Democracy: By making proposals for procedural modifications or enhancements, an apprentice will initiate discussion and consider feedback from their team, fostering an environment of inclusivity and collective decision-making.
• Individual Liberty: This task allows for individual creativity and initiative within the framework of the project, promoting individual liberty in problem-solving and decision-making.
• Respect and Tolerance: By analysing existing database structures, an apprentice will respect the previous work and contributions of their colleagues before identifying areas for improvement constructively.

For the Nursing Associate patient safety module, the following result was produced in phase three:

• Rule of Law: By adhering to safety protocols and quality standards during patient consultations and procedures, an apprentice is upholding the rule of law by ensuring compliance with legal and regulatory requirements.
• Democracy: By gathering feedback from patients and families and incorporating their voices into care plans, an apprentice will reflect democratic principles by promoting inclusivity and shared decision-making.
• Individual Liberty: This task allows an apprentice the freedom to engage with patients and families, empowering the patients and families to express their opinions and concerns freely.
• Respect and Tolerance: By shadowing senior staff and actively observing safety protocols and quality standards, an apprentice will demonstrate respect for established procedures and the expertise of their colleagues.

It's so easy, right? Drawing upon another requirement of the EIF, how about familiarising apprentices with safeguarding topics?

Safeguarding protects us from ten types of abuse: discriminatory abuse; domestic violence/abuse; financial/material abuse; modern slavery; neglect/acts of omission; organisational/institutional abuse; physical abuse; psychological/emotional abuse; self-neglect; and sexual abuse.

Explain how the following task may requires an apprentice to consider these safeguarding topics:

"[RESULTS FROM PHASE TWO]"        

For the Digital and Technology Solutions Professional DBMS module:

• Financial/material abuse: By ensuring that data stored in the database is protected from unauthorised access/misuse, safeguarding against potential financial/material abuse through the misuse of personal information can be considered.
• Discriminatory abuse: By maintaining the confidentiality of sensitive information stored in the database, the apprentice prevents potential breaches that could lead to discriminatory abuse, such as access to protected characteristic data or medical history.
• Organisational abuse: By implementing appropriate access controls to prevent unauthorised individuals from tampering with or accessing sensitive data, the apprentice safeguards against potential organisational abuse, such as the falsification of financial data.
• Training and Awareness: By providing staff training on data management best practices, the apprentice raises awareness about safeguarding issues related to data management.

For the Nursing Associate patient safety module:

• Domestic abuse: During patient consultations, the apprentice may observe signs or indicators of domestic violence or abuse, such as unexplained injuries or patterns of behaviour.
• Neglect: Through interactions with patients and their families, the apprentice may identify instances where patients' needs are not being adequately met or where there are gaps in care provision.
• Physical abuse: While observing safety protocols and quality standards during procedures, the apprentice should be prepared to intervene or report any concerns relating to the mistreatment of patients.
• Training and Awareness: Apprentices should be trained to recognise signs of abuse and know how to respond appropriately, including providing support and referring patients to appropriate services for help.

Wow! And what about apprentices who are undertaking level 2 English and maths functional skills alongside their studies? Or moreover, even for those who aren't, how can this same task develop an apprentice's functional skills in English and mathematics?

Functional skills in English are described as follows:
- Listening, understanding, and making relevant contributions to discussions with others in a range of contexts. 
- Applying understanding of language to adapt delivery and content to suit audience and purpose. 
- Reading a range of different text types confidently and fluently and applying knowledge and understanding of texts to one’s own writing. 
- Writing texts of varying complexity, with accuracy, effectiveness, and correct spelling, punctuation, and grammar. 
- Understanding the situations when, and audiences for which, planning, drafting, and using formal language are important, and when they are less important.

Functional skills in mathematics are described as follows:
- Demonstrating ability in mathematical skills and ability to apply these, through appropriate reasoning and decision making, to solve realistic problems of increasing complexity. 
- Considering new areas of life and work and the corresponding mathematical concepts and problems which, while not of immediate concern, may be of value in later life. 
- Developing an appreciation of the role played by mathematics in the world of work and in life.

How might the following task build upon an apprentice's functional skills in English and mathematics?        

For the Digital and Technology Solutions Professional DBMS module:

• English: The task requires the apprentice to effectively communicate their findings and proposals to the IT department and potentially other stakeholders. This involves listening and understanding technical discussions, adapting their language to suit the audience (e.g., using plain language when discussing complex technical concepts), and writing clear and concise documentation to convey their recommendations.
• Mathematics: Analysing the database structure and identifying areas for improvement involves mathematical reasoning and problem-solving skills. The apprentice will need to apply mathematical concepts such as data normalisation or performance optimisation algorithms to propose modifications that enhance system efficiency and data integrity. This task encourages the apprentice to apply mathematical skills to solve real-world problems in a professional setting.

For the Nursing Associate patient safety module:

• English: The task involves actively engaging with patients and their families to gather feedback on their care experience. The apprentice needs to listen attentively, understand their concerns, and communicate effectively to ensure their voices are heard and incorporated into care plans. Additionally, the apprentice may need to draft reports summarising feedback and proposed solutions, requiring them to write texts of varying complexity with accuracy and clarity.
• Mathematics: Analysing feedback data to identify areas for enhancement and propose solutions requires mathematical reasoning and decision-making skills. The apprentice must apply statistical methods to interpret the data effectively, such as calculating averages, percentages, or correlations. This task helps the apprentice develop their ability to apply mathematical concepts to solve real-world problems in the context of improving patient care quality.

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In conclusion, I hope this little blog shows a simple demonstration of how anyone could start integrating AI into their apprenticeship curriculum design today and how it offers a transformative opportunity for universities to streamline processes, enhance employer co-creation, and ultimately enrich the learning experience for our apprentices by creating endless, bespoke teaching and learning ideas.

Feel free to use and adapt the ChatGPT prompts I've written throughout this blog to see just how easy apprenticeship course design could be in the future. I'd be keen to hear how it works for you!