7OS03 Technology Enhanced Learning Question 4 (AC 4.3)

7OS03 Technology Enhanced Learning Question 4 (AC 4.3)

Introducing learning technology at work isn’t just a matter of picking the newest tool and rolling it out with a cheerful email. There’s more going on beneath the surface. In our look at 7OS03 Technology Enhanced Learning Question 4 (AC 4.3), we’ll dig into the real-world things that can help, or quietly derail the process.

Sometimes the tech looks promising, but then the Wi-Fi struggles. Or the team isn’t really on board because, well, change is uncomfortable. And even when everything seems ready on paper, you might sense something’s missing, a kind of hesitation that’s hard to name but easy to feel.

That’s where this question becomes interesting. It asks us to reflect, honestly on the actual factors that shape whether digital tools genuinely support learning or just become another unused shortcut on someone’s desktop.

Question 4 (AC 4.3): Evaluate the role of artificial intelligence within learning and development, including examples of how AI is, or could be, used as a part of the learning and development strategy within your organisation, or an organisation with which you are familiar.

Part 1 – Understanding What the Question is Really Asking

Before we even begin to write a response, we need to be clear on what the examiner is expecting.

This question is sitting under Assessment Criteria 4.3, which uses the word “evaluate.” Now, in CIPD terms, evaluate doesn’t just mean describe or list things. It means you’re expected to look at AI in critical depth, weighing up its usefulness, possible drawbacks, how it fits into practice, and where it might fall short or surprise us.

So, this isn’t about praising technology. Nor is it about fear-mongering. It’s a balanced, thoughtful look at how AI can or does play a role in Learning and Development (L&D), with realistic examples to bring that to life.

Now, let’s connect this to the case study.

Case Study Context:

You’re preparing for a focus group, arranged by your local CIPD branch, to update peers on how technology is being used to support learning at work.

They’ve asked you to reflect, and bring examples, possibly from your own organisation or one you know well.

Let’s imagine you’re part of the L&D team at “CoastalCare NHS Trust”, a fictional UK-based healthcare provider managing staff development across hospitals in both urban and coastal locations. It mirrors the shift we’re seeing in real public sector services, where budgets are tight, expectations are high, and digital learning is gradually being adopted.

This setting gives you something familiar. You can explore realistic examples, such as staff induction, mandatory training, or CPD, and how AI shows up in those areas.

Step-by-Step Breakdown for Your Written Response

1. Begin with a clear opening that reflects the question and context

Something like:

In preparing for this focus group discussion, I’ve been reflecting on the growing visibility of artificial intelligence (AI) in workplace learning. While digital learning tools have been around for some time, AI feels different, not just another method, but something that could gradually change how learning is delivered, how it’s experienced, and even how it’s designed. At CoastalCare NHS Trust, we’ve only started scratching the surface, but the direction of travel is becoming clearer.

Why this works:

• It mirrors a human voice, reflective, a bit tentative.
• It shows you’re answering the question from within the scenario.
• It doesn’t jump straight into ‘definitions’, that’s more of a school approach than a workplace one.

2. Explain what AI means in this context

You don’t need an academic definition. Instead, try something like:

When we talk about AI in L&D, it’s usually not robots or big dramatic systems. It tends to show up in the background as part of learning platforms that suggest modules, or systems that track progress and adjust content slightly depending on what someone got right or wrong. We’ve seen this in our e-learning provider, where the system now offers optional refreshers based on incorrect responses. It’s complicated, but it means learning is slowly becoming more responsive.

What’s happening here?

• You’re explaining AI in your own words.
• You’re keeping it applied, not theoretical.
• You’re giving a specific, realistic example.

3. Evaluate its benefits, but with realism

Now, explore the positives. But remember, you’re not trying to sell AI. You’re analysing it.

One clear benefit has been in onboarding. Our junior nurses now complete digital induction that adjusts slightly depending on their department, the system recognises whether someone is in paediatrics, emergency, or elderly care, and shifts some of the core modules accordingly. It saves time and makes the learning feel more relevant. Though I do wonder if it also means people might miss broader context that used to come up in the full group sessions we did before. That social element’s a bit lost.

What this shows:

• Positive application, tailored onboarding.
• Realistic critique, loss of peer learning or cross-departmental exposure.
• A bit of personal reflection, “I do wonder…”

4. Evaluate its challenges or risks

Let’s continue the evaluation by raising a few issues.

There’s also the matter of how much we rely on the system’s suggestions. In some cases, staff follow only what’s recommended, which may mean they’re missing broader learning that isn’t flagged by the AI. I’ve noticed this particularly among administrative teams who’ve stopped checking the full course catalogue. It raises questions about whether AI is narrowing rather than expanding our view of development.

Again, a few things to notice:

• No need for dramatic language. Just calm observation.
• You’re still engaging with the question, you’re not going off-topic.
• You’re showing critical awareness: AI can shape our choices more than we realise.

5. Consider future potential, but avoid grand claims

Now shift slightly to what might come next, but don’t fall into the trap of sounding too excited or too cynical. Something like:

One of the areas we’re considering is using AI to support reflective practice. There are platforms that can track language patterns in reflective journals and suggest areas for follow-up or supervision. I’m not sure how staff will feel about that, some might find it helpful, others may see it as invasive. It does open up possibilities, but also questions around trust and transparency.

This:

• Grounds your comment in a real issue, privacy, trust, surveillance.
• Doesn’t declare AI as “the answer.”
• Maintains that natural, professional tone.

6. Tie it back to L&D strategy by showing the broader link

Now, pull out what this means for a strategic view of L&D.

From a wider perspective, AI could gradually shift how we think about L&D planning. If systems are identifying gaps, recommending training, and even generating micro-content in response to performance trends, the role of the L&D professional may shift from delivering content to curating pathways and guiding choices. At CoastalCare, we’re not there yet. But you can feel the shift starting, even if it’s patchy and a little unclear for now.

Key technique here:

• You’re referencing strategy, as the question asks.
• You’re also acknowledging uncertainty, which is realistic.

7. Bring it to a close

Just close your thoughts, like this:

All this said, I think AI in L&D will remain a mixed picture, part helpful, part distracting, sometimes both. It has potential, but it also demands care. The more human the intention behind it, the more useful it’s likely to be. That might be the bit we still need to figure out.

Again:

• It sounds natural and personal.
• You didn’t force a balanced argument.

Final Reminders Before Submitting

• Avoid listing AI tools like ChatGPT, Coursera, or adaptive learning systems unless you’re describing how they’re used in context.
• Your example organisation (e.g. CoastalCare NHS Trust) needs to feel real, think like someone working there.
• Evaluate means what works, what doesn’t, what might happen, and why it matters.
• Don’t aim for polished corporate tone, let it breathe.

Question 4 (AC 4.3): Evaluate the role of artificial intelligence within learning and development, including examples of how AI is, or could be, used as a part of the learning and development strategy within your organisation, or an organisation with which you are familiar.

As part of preparing for this upcoming CIPD focus group, I’ve found myself thinking more closely about the role of artificial intelligence (AI) in workplace learning. It’s something that’s been bubbling under the surface for a while, often in quiet ways we don’t always notice. At CoastalCare NHS Trust, where I work in the people development team, we’ve had a few early experiences with AI-supported learning. Nothing revolutionary, but enough to see where this might be going.

When we talk about AI in learning and development, we’re not necessarily thinking of high-tech robots delivering lectures or replacing our teams. It’s often embedded into learning platforms already in use. For example, our e-learning platform includes features that respond to how a learner performs, if someone consistently struggles with medication calculations, the system automatically recommends extra practice modules. That’s AI in action, just not in a very flashy way.

In terms of what it’s actually doing for us, well, I’d say one area where we’ve noticed a genuine shift is during onboarding. Our newly recruited junior nurses are now placed on a digital induction journey. The system detects which clinical area they’re joining and then adjusts the pathway slightly. So, someone joining paediatrics might receive child safeguarding training earlier in their programme, whereas someone in elderly care will be prompted to complete dementia awareness first. It’s not a full redesign of the process, but it’s made it feel a little more tailored, and some staff have commented that it made the first few weeks feel more relevant.

That said, I do find myself wondering about what’s being lost. Before we introduced this AI-supported system, there were more group sessions, people across departments would meet, talk, and learn from each other’s areas. Now, with more isolated and targeted content, that cross-departmental conversation isn’t really happening. It’s not necessarily a bad thing, just a shift we hadn’t quite planned for.

Another pattern I’ve observed is how AI might shape what people learn, or perhaps, what they don’t. Our platform now shows recommended modules based on job roles and past completions. On paper, that sounds helpful. But I’ve noticed some admin teams stop exploring beyond what the system suggests. The catalogue’s still there, but fewer people are browsing it freely. So there’s a question of whether AI-supported learning is narrowing options without us realising it. It’s efficient in one sense, but maybe a bit limiting too.

Looking forward, we’re tentatively exploring ways to use AI to support reflective learning. One system we’ve been reviewing claims to analyse language in digital journals and prompt users with reflective questions, or flag areas for potential supervision. I can see how that might help staff who find written reflection difficult, especially with time pressures on clinical teams. On the other hand, there’s a clear risk, if AI starts drawing attention to certain themes in someone’s writing, could that feel invasive? Would staff feel watched rather than supported? We’ve not introduced this yet, and honestly, we’re still debating whether it’s worth the potential pushback.

All of this raises questions about how AI could influence our overall learning strategy. It’s already shifting the role of the L&D function. There’s less focus on delivering standardised training to everyone and more on guiding people through increasingly personalised digital pathways. At CoastalCare, this is still early-stage, the tech exists, but our internal processes and team capacity haven’t quite caught up. Still, it feels like the L&D team is slowly moving into more of a consultative space, helping people make sense of what the systems are offering, rather than deciding the whole programme for them.

So, where does this leave us? I suppose AI in L&D is becoming part of the furniture, not always visible, not always dramatic, but slowly reshaping things. It brings certain benefits, better targeting, flexible pacing, sometimes even higher completion rates, but it also poses real questions about choice, autonomy, and how people learn together. I wouldn’t say we’ve figured it all out yet. In fact, most days it still feels like we’re experimenting. But that might be alright, as long as we keep asking the right questions, and stay close to the people actually using these systems.

FAQs

1. What does Question 4 (AC 4.3) of 7OS03 ask us to focus on?
It invites you to look beyond the tech itself and think about the practical and human factors that shape how technology works in learning. Think culture, user support, trust, timing, and digital skill gaps.

2. Why is it not enough to just have the right technology?
Because people matter. Even the best software falls flat if learners don’t trust it, feel overwhelmed, or lack confidence in using it. Often, success is about preparation, not just tools.

3. Can cost be a deciding factor when adopting new learning technology?
Yes—and no. Budget does influence decisions, but so does long-term usefulness. A cheap tool that no one uses isn’t really saving money.

4. What role does leadership play in technology-based learning?
Quite a big one. If managers show interest and encourage participation, people are more likely to engage. Without that, new platforms often get quietly ignored.

5. Are staff training needs part of the decision-making process?
They should be. If users don’t feel ready or supported, they’ll avoid the platform, even if it could help them. Familiarity and confidence take time to build.