AI study buddies – NotebookLM, stop dabbling!

The current AI landscape is, in a word, overwhelming. Every day, three new tools launch, two others pivot, and the “best” model changes before you’ve even finished your morning coffee.

This “hyper evolution” makes it incredibly tempting to keep chasing the next shiny object, (note to self) but there is a cost to that, you become a jack of all trades and a master of none.

The best way to get real value from AI both in your career and studies isn’t by dabbling in everything, it’s by picking one powerful tool and getting exceptionally good at it.

If you’re just starting out or want to see what all the fuss is about, by all means, spend some time playing with ChatGPT, Gemini or Claude. They are all excellent tools for learning and can give you a valuable insight into how LLMs work and what they can do. But there will come a point when the hard work of learning has to start, and that’s where NotebookLM can really help.

NotebookLM audio overview
Rather than reading this blog why not listen to a short summary or a long form deep dive between two people. Complements of NotebookLM, I think you will be impressed.

Short summary

Deepdive debate

What is NotebookLM?
NotebookLM is an AI powered research and study assistant from Google designed to focus exclusively on the documents you provide. Unlike standard LLM’s that take information from the internet, NotebookLM only searches for answers in specific sources, PDFs, notes, or videos etc. This approach reduces hallucinations to between 10% – 15% and ensures that every summary, study guide or explanation is both accurate and directly cited from your data. Furthermore, it offers a higher level of security, as your uploaded documents remain private and are not shared with others.

See for yourself – This video highlights several key features, showing how NotebookLM can automatically turn your notes into helpful study aids such as audio podcasts, interactive quizzes, flashcards, and even short summary videos. It also walks you through the practical steps of setting up a notebook, generating different types of content, and sharing your work with others.

How to use NotebookLM
The video explains some of the features and gives a good overview but it’s worth taking a deep dive into each of them with examples as to how each feature might help you learn more effectively..

Audio Overview: Generates a conversational, podcast style discussion based on your resources. Best for – Listening to your notes or a long article while commuting or exercising. This can provide you with a high level overview of the information, which may be sufficient on its own or help you better navigate the article when you read it in full.

Video Overview: Creates a short summary with AI-generated narration and relevant images Think of it as your personal tutor who when you get stuck on something can help. Best for – Simplifying complex subjects through clear, narrated explanations and visual illustrations.

Mind Map: Visually organises the key concepts and connections found within your documents. Best for – Gaining an overview of a subject before diving into the detail. You can upload all the chapter headings from a textbook and use the Mind Map feature to visually organise how topics and themes connect to each other.

Reports: Compiles the information from your sources into a structured, written document or article. Best for – Use in the workplace rather than study. It can help you generate ideas or better structure your report, but generally one to avoid, largely because it encourages cognitive offload e.g. the machine is doing the work not you.

Flashcards: Automatically generates digital cards with questions on the front and answers on the back for active recall. Best for – Memorising facts or key definitions which become more important the closer you get to the exam. Remember to take breaks between practicing with the cards.

Quiz: Produces an interactive assessment with immediate feedback and citations to help check your understanding. Best for – Testing your knowledge and forcing recall, which is one of the best learning strategies there is.

Infographic: Turns information into a clear, visual format to highlight important facts and statistics. Best for – Reducing complexity and offering a clear route to the most important information.

Slide deck: Drafts a set of presentation slides based on the core themes of your uploaded content.Best for – Clarifying key points as well as providing a compelling narrative that can help you and others better understand a subject.

Data table: Extracts and organises specific information from your files into a clean, structured table. Best for – Taking large amounts of information and turning it into a table that can help with recall.

Conclusion
What makes NotebookLM particularly effective for learning is that it encourages active engagement with material rather than passive consumption. You’re not just reading, you’re questioning, synthesising, and creating new ways of improving your understanding. It aligns very well with what we know from cognitive science as to what makes effective learning e.g retrieval practice, elaboration, and multiple encoding formats all strengthen memory and understanding.

In a world drowning in AI tools, NotebookLM stands out not because it does everything for you, but because it does one thing exceptionally well, helping you learn – Enjoy!

Back to the future – Reflections and Projections

One of the most valuable parts of learning is discovering new ideas and different ways of thinking. While some of this comes from formal teaching, we all have access to a vast library of knowledge that can help us learn some of these skills for ourselves. We just need to ask the right questions and look in the right place. Oh, and you might find it helpful to have pen and paper.

Simply reflect on a specific experience and critically examine it by asking yourself questions such as, what did I learn from this? What aspects were unclear or confusing? What approaches were effective, and which ones fell short? Reflection not only deepens understanding but will help identify ways in which you can improve.

The value of reflection is well understood and encouraged within education, and although students may not initially see its importance they will be asked to produce reflective statements or keep a journal in at attempt to get them to appreciate its worth. From a cognitive perspective your brain isn’t just opening a file, its actually reconstructing (ironically like an LLM) and rewiring the information. The process will strengthen the synaptic path, develop new associations, which in turn helps integrate different types of information into a “big picture.” Before finally being resaved as a stronger, more complex version of the original idea or thought.

But enough of what it is, let me see if I can put it into practice by reflecting on 2025 and coming up with a few ideas for 2026.

Reflections on 2025
This time last year I set out some predictions as to what might happen in learning from 2025 onwards with the caveat that making predictions is a “mugs game.” Looking back, there was nothing particularly radical in what I suggested. In that sense, if I was being critical, it may be that the ideas themselves may not have helped that much. Even so, I hope that by narrowing the field of possibilities it made the future seem a little less confusing.

The 2025 predictions:

1. Learning will not change but learners will. A reference to how learners will develop different behaviours as a result of AI. This year research from MIT confirmed what many had suspected that using AI has an impact on brain activity, causing what they called “cognitive debt” e.g. saving effort now, but weakening cognitive abilities over time. This will remain a challenge in 2026 and beyond requiring educators to get ahead of the technology rather than simply acknowledging its existence and use.

2. AI (GenAI) will continue to dominate. An easy one perhaps, of course AI was going to play a hugely important part in learning. But there was specific reference to it becoming the “go to” tool for students and the emergence of teaching chatbots.  A survey by Hepi and Kortext early in 2025 found that the proportion of students now using AI has jumped from 66% last year to 92% this year. Which seems conclusive, AI has become an ever-present aspect of student life and one that cannot be ignored. Teacher bots have also advanced significantly, with research showing they now deliver consistently high‑quality learning experiences. Expect these trends to continue as well as the big tech companies developing AI integrated solutions for learners and educators e.g. Gemini for Education, Copilot for Education, ChatGPT Edu, Pearson +.

3. Watch out for sector disruption, the result of, a reduced need for textbooks, a different approach to assessment and data becoming even more important. In 2025 Chegg, the US publisher reported first-quarter 2025 revenues down 30%! naming Googles GenAI intelligent summaries, as significantly contributing to the sharp decrease in its traffic. And they are not the only ones impacted, Pearson et al are changing their plans, hoping that AI‑enhanced textbooks are the solution to declining sales, personally I’m not convinced.

By late 2025, large companies were finding access to quality data was stopping them getting value from AI. In fact,  Gartner found that 30% of GenAI projects fail because of poor data. As for assessment, in a somewhat backward and reactive step some have reverted to the use of more traditional assessment methods. These include oral exams, handwritten exams and portfolios to combat plagiarism. The smarter more proactive solution would be to build AI into the assessment process, with appropriate guardrails for novice leaners. Some have begun to make changes and will continue to do so into next year but its patchy.

4. Regulation will be in conflict with innovation. This year governments have been working hard to balance innovation with responsible oversight. In the UK and EU, policymakers recognise AI’s potential but are introducing strict rules creating a tension for schools and colleges that want to innovate. In contrast, the US are taking a more flexible approach, offering federal guidance rather than strict regulation. Expect this tension to continue well into 2026, and there’s no simple resolution. While slowing down may feel defeatist, the answer isn’t to rush implementation it’s to accelerate the validation process itself. Meet weekly to assess new tools, prioritise solutions based on the biggest challenges, implement, then move on to the next.

Reflections and projections for 2026 – The level of investment in AI has driven what feels like an arms race in technological development. This has meant keeping up to date with new AI solutions has become increasingly difficult, as has understanding why the latest tool is better than the one, you’re currently using. Technology is advancing faster than individuals or institutions can sensibly integrate and manage within their existing practices. There is no single pathway forward, no consensus on best practice, and little time to evaluate what actually works before the next wave of tools arrive. This mismatch creates risks. Without proper integration, barriers may emerge, whether through poorly designed policies that restrict innovation or the development of tools that undermine rather than support learning. Personalisation and more authentic methods of assessment will remain the North Star for many in navigating this disruptive environment. Keep them in mind, but remember to look down every now and again, you dont want to trip up.

Personally, I’m excited about 2026. AI is opening doors we couldn’t have imagined even a few years ago, and the potential to do good things, to truly make a difference, feels within reach. However, the pace of development is uneven and the world remains unpredictable. More realistically, we are likely to see parts of the education sector make genuine breakthroughs, while others hold back and wait, the result of indecision, or taking a more cautious approach. There is of course no way of knowing which one will succeed in the long run.

Whatever the reason, 2026 looks set to intensify the “Jagged frontier”.

Perhaps Winston Churchill should close out 2025.

Merry Xmas and a Happy New year everyone – put your running shoes on, but make sure the race is worth running and the prize worth having!

Effective learning = Affective learning

When we think of learning, we often focus on acquiring knowledge and developing skills. But there’s a third, often overlooked dimension, the affective domain. These are our attitudes, motivation, values, and emotions. It’s easy to view them as somehow less important and yet they are what transform knowledge and skill into true expertise.

Imagine two students sitting in a maths class, both are taught about addition (knowledge). They are then asked to add several numbers together, which they do successfully (skill). But one of them believes they are not very good at maths and that the subject is boring. The other likes the subject and is looking forward to the next class. It’s not hard to figure out who will learn more, not because they were in some way smarter but because of the difference in their attitude, levels of motivation and beliefs.

I’m trying something different this month – a two minute video explainer of the blog, enjoy

How to play the violin
One way to understand how knowledge, skills and the emotional side of learning fit together is to consider how you might learn to play the violin.

First you need to be able to read music, this is the knowledge phase. It’s not easy of course, and in some ways may feel a little abstract and lacking in purpose. Next there is the physical skill of being able to play the violin. Reading music is a prerequisite but its practice and repetition that will help you improve. And lastly, you pick up the violin and play a piece of music, this is when the affective domain becomes important. How confident are you there will be no mistakes, do you feel sad when playing, what emotion are you trying to pass onto your audience. To deliver a great performance will require the combination of knowledge, skills, and emotions, interwoven so closely they cannot be separated.

The research – There is a large body of evidence supporting the impact of emotions, attitudes, and beliefs on learning. In 2014 Reinhard Pekrun published Emotions and Learning, in it he demonstrated that positive emotions like enjoyment and pride enhance learning by increasing motivation, engagement, and cognitive flexibility. In contrast, negative emotions such as boredom and anxiety can suppress learning.  Carol Dweck’s work on growth mindset (2006) further reinforces this idea. She showed that learners who believe effort leads to improvement are more likely to persist through challenges. These beliefs rooted in the affective domain shape how students respond to setbacks and how resilient they become in the face of difficulty.

Another Bloom’s taxonomy!
Many will have heard about Blooms taxonomy but what you might not know is that there are three of them. The first is Cognitive, the Bloom most of us have seen before (The pyramid), the second Psychomotor domain, that looks at physical skills, and lastly the Affective domain that defines behaviours that correspond to attitudes and values.

This affective domain has five levels:

  • Receiving – The willingness to attend or listen, giving your attention  
  • Responding – Actively participating, effectively engaging
  • Valuing – Attaching worth to an idea, making it personal, forming the belief
  • Organisation – Integrating the values into your belief system, embedding the belief
  • Characterisation – The learning becomes part of your identity

Why it works – Bloom sets out the hierarchy of development but the reasons our brains respond and change are, firstly emotion directs attention and strengthen memory. Our brains evolved to prioritise emotionally charged information. Secondly, positive feelings boost motivation. When learners feel valued and capable, dopamine release reinforces effort and persistence. And lastly supportive environments reduce cognitive overload, freeing up working memory for reasoning and problem-solving

What does this all mean?
Understanding that there is a third aspect of learning is important, if not educators will spend disproportionate amounts of time on knowledge and skills, which of course is often the case! When in fact they should be thinking about how to use affective techniques to deepen learning. For students it gives an insight into the human side of learning, you are not ChatGPT able to simply scan content and recall it whenever needed, you are a human being who needs to feel, connect, and value the material for it to stick. That emotional and motivational component is the fuel you need for long-term mastery. Simply knowing that can make a big difference.

Want to learn more – Listen to Nick Shackleton-Jones talking with John Helmer about affective learning, and a lot more.

Human superpowers – Creative, Analytical and Critical thinking

Are you sure Gen AI doesn’t make mistakes Mr Spock? Because this just “feels” wrong to me.

Back in July 2022, I wrote about the importance of critical thinking, a skill long considered essential in education, leadership, and the workplace.

But that was before Gen AI arrived in the November, bringing with it the ability to answer almost any question within seconds. Its presence prompted reflection on the nature of learning, how education might change and what role humans should now play, if any.

If you don’t have time to read this month’s blog – listen to my AI alter ego summarise the key points.

But all is not lost we still have one last card to play, our ability to think and feel, okay maybe that’s two cards. Thinking is hopefully what you are doing whilst reading this blog, neurons will be firing as you reflect, analyse and question what is being said. It’s something we do in between day dreaming, sleeping and unconscious behaviours such as cleaning our teeth.

Thinking is however a little more nuanced, and there are many different types, for example you can think creatively, analytically, or critically. Whichever mode you engage in, there’s another essential human attribute that quietly shapes the process…. our emotions. These are the subjective experiences rooted in our limbic system that help us interpret information and as such see the world. Together these are our superpowers offering something AI can’t replicate, not yet at least!

An Artist, Pathologist and Judge walk into a bar
Critical thinking, creative thinking, and analytical thinking are often grouped under the umbrella of “higher-order cognitive skills,” but each one is different, playing a role in how we process, evaluate, and generate ideas.

  • Critical thinking is fundamentally about evaluation, it involves questioning assumptions, weighing evidence, and forming reasoned judgments. It’s the internal referee that asks, “Does this make sense? Is it credible? What are the implications?”
  • Meanwhile, analytical thinking breaks down complexity into more manageable components, identifying patterns, and applying logic so that we can better understand relationships.
  • And creative thinking is generative. It thrives on ambiguity, imagination, and novelty. Where critical thinking narrows and refines, creative thinking expands and explores. It’s the spark that asks, “What if? Why not? Could we do this differently?”

Humans are emotional – Far from being a distraction, emotions actively shape how we think, judge, and create. In creative thinking, emotion is the spark that fuels imagination and unlocks divergent ideas. In analytical thinking, emotion plays a subtler role influencing how we interpret data, what patterns we notice, and our levels of motivation.  Critical thinking, meanwhile, relies on emotion to provide an ethical compass and improve our self-awareness.

Learning to be a better thinker
Critical, creative, and analytical thinking aren’t fixed traits, they’re learnable skills. It’s tempting to believe they can only be acquired through the slow drip of wisdom from those who have had a lifetime of experience. The truth is, with good instruction, these skills can be learned well enough for any novice to get started. At first the beginner may simply replicate what they have been taught but with practice and reflection, they begin to refine, adapt, and eventually think for themselves.

By way of an example, this is how you might start to learn to think more critically.

  1. Start with knowledge – Critical thinking is the analysis of available facts, evidence, observations, and arguments to form a judgement.
  2. Use a framework
    • Formulate the question – what problem(s) are you trying to solve?
    • Gather information – what do you need to know more about?
    • Analyse and evaluate – ask challenging questions, consider implications, and prioritise.
    • Reach a conclusion – form an opinion, and reflect.
  3. Bring in Tools – These can provide ideas or change perspective, for example Edward de Bono’s six thinking hats.
  4. Apply by practicing with real world problems. This is largely experiential, and requires continual reflection and looping back to check you have asked the right question, gathered enough information, and correctly prioritised.

The real challenge and deeper learning take place in the application phase.  By working in groups, your arguments may well be questioned and potentially exposed by the use of Socratic type questions and differing views.  Your only defence is to start thinking about what others might say in advance. Over time like any other skill, it can begin to feel more like an instinct, requiring less conscious effort, simply popping into your mind when most needed.

To boldly go
Generative AI may offer logic, precision, and even flashes of creativity but it does not feel the weight of a decision, nor wrestle with the moral ambiguity that defines human experience. It is Spock without Kirk, brilliant, efficient, and deeply insightful, yet missing the emotional compass that gives judgment its humanity. True thinking is not just analysis, its empathy, intuition, and the courage to act without certainty. AI can advise, assist, and illuminate, but it cannot replace the uniquely human interplay of reason and emotion. Like Kirk and Spock, the future belongs not to one or the other, but to the partnership. Or at least I hope so…..

I will leave the last word to Dr McCoy.

Measuring success – “Authentic” Assessment

There is a saying often attributed to Peter Drucker – “what gets measured gets achieved.” I think the quote is “gets done” but that always feels a little clumsy. Although it’s easy to argue that the statement is crude and simplistic, it has a real-world truth.

Such is the inherent challenge with exams. Once a syllabus is written and a pass mark set, the students’ goal often shifts from trying to learn the subject to simply figuring out what needs to be done in order to pass. This, in turn, creates a ripple effect for teachers, especially if their performance is measured by pass rates. They will inevitably adapt their teaching methods to align with that target.

If you dont have time to read this months blog – listen to my AI alter ego summarise the key points.

Having spent over 30 years helping accountancy students pass high-stakes exams, I’m not personally going to criticise this (exam driven) approach, though I appreciate many will. I have seen how effective it can be in providing clarity and focus for students, helping them manage the huge amounts of information they are required to learn, and in many ways making what might seem impossible – possible.

But this isn’t an argument for ‘teaching to the test’, it’s an acknowledgment of a fundamental truth that targets shape behaviour, regardless of how well intentioned the original objectives. Keep this in mind as we discuss one of the solutions currently being proposed to improve assessment, it’s called – Authentic Assessment.

Authentic assessment
First a definition, authentic assessment (Grant Wiggins 1989) involves evaluating learners through realistic tasks that reflect the types of challenges they will face in the workplace. It prioritises realism, and encourages learners to “do” the subject, mirroring or simulating the real-world. These assessments measure a learner’s ability to apply knowledge and skills to complex, realistic tasks. There are two main components, one a real-life task that needs to be completed by the learner and two, a rubric by which their performance can be measured.

Beyond the exam room – Instead of asking learners to sit in a room for two maybe three hours regurgitating memorised content, an authentic assessment might need the learner to prepare a portfolio, complete a project, engage in a debate, and even enter a realistic business environment, as required for a case study or simulation. Many consider them more engaging and motivational largely because learners can appreciate their real-world application. They also foster the development of critical thinking, problem-solving and ease the transition into the workplace.

But they are not a panacea – and there area number of problems with authentic assessments, not least the lack of consistency in measuring performance. This is because they prioritises validity (measuring what it’s supposed to) over reliability (consistent results – marking scripts to the same standard). The issue with reliabilty is partly the result of not having a “perfect” model answer that can be used as a benchmark, nor a sufficiently robust rubric (marking guide). Traditional exams by way of contrast aim for high statistical reliability through objective scoring but allow little flexibility in rewarding learners who produce creative or original answers and arguably benefit those who are just good at exams.

In addition to the difficulty in objectively measuring success, as a method of assessment they are not well defined, for example what exactly is the “real world,” and what is meant by “authentic.” One company’s definition of the workplace will be very different from another.

One final observation, although authentic assessment has been proven to increase employability type skills, there is no evidence to show that having been assessed in this way increases you chances of getting a job!

What gets measured……
Changing the assessment directly alters the focus for both learners and teachers, shifting it towards real-world tasks means that learners are less a consumer of information but active participants in its use. For teachers, instead of concentrating on delivering content their role becomes more facilitative, guiding learners through complex tasks rather than just lecturing. And overall this change in approach is hugely positive.

But as highlighted above, it comes at a cost, there is some confusion over what authentic actually means, and measuring success becomes subjective making it difficult to mark consistently. This last point is important, because it means that one person may interpret your answer as a pass and another as a fail – it then becomes the luck of the draw!

The answer….well one of them – think of assessment not as a single exam but as a framework under which several different formats and approaches can be used. The assessment framework will expose the learner over several modules or even several years to a blend of formal (reliable) exams and authentic (valid) exams. The outcome, might just give us – the best of both worlds.

The virtual educator has arrived!

But which one is me?

Inspired by a recent LinkedIn post I made regarding what it might be like to have an avatar as a teacher, I thought I should check out the evidence in terms of the effectiveness of avatars to improve learning before I get too carried away with the technology itself.

What is an avatar?
An avatar is a digital or computer-generated representation of a person or character in a virtual environment. It can take various forms, for example a simple profile picture on social media or an audio avatar talking about a specific subject using a synthetic voice. However, with major advancements in generative AI, avatars are evolving beyond static images or basic voice interactions. We are increasingly seeing lifelike digital humans emerge, sophisticated AI-driven avatars capable of “understanding” what we say and generating intelligent responses, speaking with realistic voices and impressive synchronised lip movements. This transformation is redefining how humans engage with AI-powered virtual beings, blurring the lines between digital representation and authentic interaction.

As to what they look like, here are some examples:

  • Firstly, an audio avatar that I have now built into my blog to provide a different perspective on what has been written. Here the avatar “chats” about the blog rather than simply reading it out loud. See above.
  • Secondly a Pixar style avatar. The goal here is to challenge the assumption that an avatar must resemble a real person to be effective.
  • And lastly, this is a more realistic avatar. Effectively an attempt to replicate me, in a slightly imperfect way. This is not about fooling the audience, although this is now possible, but to explore the idea that humans respond better to a more human like character.

The talking head – good or bad?
However there’s an elephant in the room when it comes to avatars, why do we need a talking head in the first place? Wouldn’t a simple voice-over, paired with well-structured content, be just as effective?

If you look at YouTube, almost everyone uses talking-head videos in different ways, surely if they weren’t effective, no one would have them, a kind of “wisdom of crowds.” But does their popularity actually prove their value, or are we just following a trend without questioning its impact?

Let’s have a look at the evidence:
After reviewing multiple studies, the findings are somewhat mixed. However, there’s enough insight to help us find an approach that works.

First, we have research from Christina Sondermann and Martin Merkt – Like it or learn from it: Effects of talking heads in educational videos. They conclude that the learning outcomes were worse for videos with talking heads, their concern was that it resulted in higher levels of cognitive load. But participants rated their perceived learning higher for videos with a talking head and gave better satisfaction ratings, selecting them more frequently. Secondly, another piece of research published five months later by Christina Sondermann and Martin Merkt, yes, the same people, What is the effect of talking heads in educational videos with different types of narrated slides. Here they found that “the inclusion of a talking head offers neither clear advantages nor disadvantages.” In effect using a talking head had no detrimental impact, which is slightly at odds with their previous conclusion.

A little confussing I agree, but stick with it….

Maybe we should move away from trying to prove the educational impact and consider the student’s perception of avatars. In this first report, student Perceptions of AI-Generated Avatars, the students said “there was little difference between having an AI presenter or a human delivering a lecture recording.” They also thought that the AI-generated avatar was an efficient vehicle for content delivery. However, they still wanted human connection in their learning and thought some parts of learning needed to be facilitated by teachers and that the avatar presentations “were ‘not … like a real class.” The second report, Impact of Using Virtual Avatars in Educational Videos on User Experience raised two really interesting points. Students found that high-quality video enhanced their learning, emotional experience, and overall engagement. Furthermore, when avatars displayed greater expressiveness, they felt more connected to the content, leading to improved comprehension and deeper involvement.

For those designing avatars, this means prioritising both technical quality and expressive alignment. Avatars should be visually clear, well animated, and their facial expressions should reinforce the message being conveyed.

What does this all mean?
Bringing everything together, we can conclude that avatars or talking heads are not distractions that lead to cognitive overload. Instead, students appreciate them, relate to them emotionally, in fact they see little difference between a recorded tutor and an avatar. Their expressiveness enhances engagement and might prove highly effective in helping student remember key points.

To balance differing perspectives, a practical approach might be to omit the talking head when explaining highly complex topics, (reducing cognative load) allowing students to focus solely on the material. However, keeping the avatar visible in most other situations, particularly for emphasising key concepts or prompting action to ensure maximum impact. Alternatively, why not let the student decide by offering them a choice to have the talking head or not.

How might avatars be used?
One important distinction in the use of avatars is whether they are autonomous or scripted. Autonomous avatars are powered by large language models, such as ChatGPT, allowing them to generate responses dynamically based on user interactions. In contrast, scripted avatars are entirely controlled by their creator, who directs what they say.

A scripted avatar could be particularly useful in educational settings where consistency, accuracy, and intentional messaging are crucial. Because its responses are predetermined, educators can ensure that the avatar aligns with specific learning goals, maintains an appropriate tone, and avoids misinformation.

This makes it ideal for scenarios such as:
– Delivering structured lessons with carefully crafted explanations.
– Providing standardised guidance, ensuring every student receives the same high-quality information.
– Reinforcing key concepts without deviation, which can be especially beneficial when high stake assessments are used, as is the case with professional exams.

However, if we power these avatars with Generative AI, the possibilities increase significantly:

  • More personalised learning. One of the most exciting prospects is the ability of avatars to offer personalised and contextualised instruction.
  • Help with effective study. Avatars could be used to remind students about a specific learning strategy or a deadline for completion of a piece of work. A friendly face, at the right time might be more effective than an email from your tutor or worse still an automated one.
  • Motivational and engaging. These avatars could also have a positive effect on motivation and feelings about learning. They could be designed to match an individual’s personality and interests, making them far more effective both in terms of higher levels of motivation and engagement.
  • Contextualised Learning. AI-based avatars can support teaching in practical, real-world scenarios, including problem solving and case-based learning. Traditionally, creating these types of environments required significant resources such as trained actors or expensive designed virtual worlds.

A few concerns – autonomous avatars
Of course, as with any new technology there are some concerns and challenges:

Autonomous avatars pose several risks, including their ability to make mistakes, the problem with avatars in particular is, they will be very convincing. We are already acutely aware that large language models can sometimes ‘hallucinate’ or simply make things up. Data protection is another concern, with risks ranging from deepfake misuse to avatars persuading users into sharing personal or confidential information, which could be exploited. Finally, value bias is a challenge, as AI trained avatars may unintentionally reflect biased perspectives that a professional educator would recognise and navigate more responsibly.

Conclusions
Avatars, whether simple or lifelike, are gaining traction in education. Research indicates that while talking heads don’t necessarily improve learning outcomes, they don’t harm them, and students perceive them positively. A key distinction lies between scripted avatars, offering consistent and accurate pre-determined content, ideal for structured lessons, and autonomous avatars powered by AI that open up a world of possibility in several areas including personalisation.

Avatars are a powerful and exciting new tool that offer capabilities that in many ways go beyond previous learning technologies, but their effectiveness very much depends on how they are designed and used. But hasn’t that always the case….

Finally – This is an excellent video that talks about some of the research I have referred to. It is of course presented by an avatar.  What Does Research Say about AI Avatars for Learning?

PS – which one is me – none of them, including the second one from the left.

You can’t outsource learning – Cognitive offloading 

As we begin to better understand the capabilities of Generative AI (Gen AI) and tools such as ChatGPT, there is also a need to consider the wider implications of this new technology. Much has been made of the more immediate impact, students using Gen AI to produce answers that are not their own, but less is known as to what might be happening in the longer term, the effect on learning and how our brains might change over time.

There is little doubt that Gen AI tools offer substantial benefits, (see previous blogs, Let’s chat about ChatGPT and Chatting with a Chat Bot – Prompting) including access to vast amounts of knowledge, explained in an easy to understand manner, as well as its ability to generate original content  instantly. However, there might be a significant problem of using these tools that has not yet been realised that could have implications for learning and learning efficacy. What if we become too reliant on these technologies, asking them to solve problems before we even think about them ourselves. This fear has found expression in debates well before Gen AI, in particular an article written by Nicholas Carr in 2008 asking “is Google making us stupid’’ – spoiler alert, the debate continues. And an interesting term coined by the neuroscientist and psychiatrist Manfred Spitzer in 2012, “Digital dementia”, describing the changes in cognition as a result of overusing technology.

But the focus of this blog is on cognitive offloading (Circ 1995), which as you might guess is about allowing some of your thinking/processing/learning to be outsourced to a technology.  

Cognitive offloading
Cognitive offloading in itself is neither good nor bad, it refers to the delegation of cognitive processes to external tools or devices such as calculators, the internet and more recently of course Gen AI. In simple terms there is a danger that by instinctively and habitually going to Google or Chat GPT for answers, your brain misses out on an essential part of the learning process. That is reflecting on what you already know, pulling the information forward, and as a result reinforcing that knowledge, (retrieval practice), then combining it with the new information to better understand what is being said or required.

As highlighted by the examples in the paragraph above cognitive offloading is not a new concern, and not specifically related to Gen AI. However, the level of cognitive offloading, the sophistication in the answers and opportunities to use these technologies is increasing, and as a result the scale and impact is greater.

Habitual dependency – one of the main concerns is that even before the question is processed, the student instinctively plugs it into the likes of ChatGPT without any attention or thought. The prompt being regurgitated from memory, “please answer this question in 100 words”. This will lead to possibly the worst situation, where all thought is delegated and worryingly the answer unquestionable believed to be true.

Cognitive offloading in action – Blindly following the Sat Nav! Research has shown that offloading navigation to GPS devices impairs spatial memory.

Benefits of Cognitive offloading – it’s important to add that there are benefits of using cognitive offloading, for example it reduces cognitive load, which is a significant problem in learning. The technology helps reduce the demand on our short-term memory, freeing the brain to focus on what is more important.

Also, some disagree as to the long-term impact, arguing that short term evidence (see below) is not necessarily the best way to form long term conclusions. For example, there were concerns that calculators would affect our ability to do math’s in our heads, but research found little difference whether students used calculators or not. And the debate has moved on to consider how calculators could be used to complement and reinforce mental and written methods of math’s. These benefits have led some to believe that cognitive offloading increases immediate task performance but diminishes subsequent memory performance for the offloaded information.

Evidence
There is little research on the impact of Gen AI due to it being so new, but as mentioned above we have a large amount of evidence on what has happened since the introduction of the internet and search.

  • In the paper Information Without Knowledge. The Effects of Internet Search on Learning, Matthew Fisher, et al found that participants who were allowed to search for information online were overconfident about their ability to comprehend the information and those who used the internet were less likely to remember what they had read. 
  • Dr Benjamin Storm the lead author of Cognitive offloading: How the Internet is increasingly taking over human memory, commented, “Memory is changing. Our research shows that as we use the Internet to support and extend our memory we become more reliant on it. Whereas before we might have tried to recall something on our own, now we don’t bother.”

What should you do?
To mitigate the risks of cognitive offloading, the simple answer is to limit or reduce your dependency and use Gen AI to supplement your learning rather than as a primary source. For example, ask it to come with ideas and lists but not the final text, spend your time linking the information together and shaping the arguments.

Appy Christmas – Apps for learning

appsIt’s always interesting writing a Blog in the holidays, maybe it’s because you have more time than normal so think you should come up with something different, dare I say original. The reality is that when you have such a large canvas on which to think, you can’t think of anything!
The answer is to narrow it down, give yourself something specific to think about. So whilst staring at my ipad for inspiration, I stopped thinking about “everything”, focused on what was on my ipad and then it happened, an idea… ..Why not write about the apps I use most and how you might use them to improve your studying, so here goes.

It’s not about the technology stupid
First a disclaimer, although technology can be all absorbing, learning is a human quality, technology in many circumstances only makes learning more convenient, you still have to work at it. What it does do is provide you with the ability to study when you want and where you want. Time that would be wasted waiting for or actually on a train/bus etc can be much more effectively used learning. How good would it be if you had finished studying before you got home?

Google CalendarGoogle calendar – Helps plan your studies
I have written before about the importance of timetables and calendars. Sitting down and planning what you will study and when not only helps you become more organised it is essential for setting targets and challenges. And remember target setting is key to motivation.

Evernote Evernote – Organise and store notes
I am finding that I am using Evernote more and more. It is in effect a cloud based folder system. Consider setting up a folder for each subject you are studying. Then within each subject folder you can type notes, attach PDF’s, photos, maybe of places/objects/people relevant to that subject. You can even attach video. And if you want to collaborate with others just share the link. Maybe have a folder for revision with the questions you want to attempt linked via PDF, comment on what you found difficult and share with your friends. Evernote has so many uses.

PenultimatePenultimate – for making hand written notes and drawing mind maps
If you prefer to write rather than type, penultimate is for you, although I don’t think there is an android version at the moment. It is part of the Evernote family and links with Evernote so is easy to use. It is just like a paper based note book with a front cover showing the subject, page numbers and has a nice page turning feel. Unlike a paper based note book however, you can change the paper, plain/lined etc, save your work, add photos, and share with others. It also has a very clever way of making sure your hand when resting on the screen does not interfere with what you are writing.

Put simply it’s the best handwriting software I have come across, and comes close to replacing paper, close but not just yet….

DropboxDropbox – for file storage, back up and file sharing
Many of you will already be familiar with dropbox, it is free simple to use cloud based storage. Dropbox is great for saving/backing up all your files. This means that as long as you can get electronic versions of your text books and question banks you will be able to have them with you anywhere…

And you can share folders with friends.

Adobe ReaderAdobe reader – keep all PDF notes in one place and you can write on them!
This is just for Adobe PDF’s but as most documents can be turned into a PDF format that should not be a problem. Imagine having your notes in a PDF file, opening them up wherever you are and then updating them either by typing or writing on top of the PDF. You can also make margin notes that open up in a speech bubble, little reminders of what you were thinking, or additional work you need to look at.

Explain-EverythingExplain everything – become a teacher and teach yourself
Explain everything is a white board that you can add in pictures, shapes etc, and then the really clever part, record what you are doing in a high quality video. What makes this so good is how easy it is to use.

This would be ideal for working through a question, talking out loud explaining your thoughts (Explain everything will record your voice and your white board actions) and then when you get to the part that is difficult or simply don’t understand, ask your question out loud….? Then send the Mp4 file to your tutor/teacher or study colleagues for an answer. Unfortunately as with Penultimate I don t think there is an android version just yet.

twitterTwitter – limitless knowledge and support
Twitter can get a bad press when it comes to studying, it can be very distracting! But if used properly it can be great. The key is to follow people that have answers to your problems or are like you. If you are studying accountancy for example you will find lots of tweets from experts providing you with up to date news and information often linking to more in depth guidance, websites/PDF’s etc. Twitter is the most up to date text book you can get.

Okay a word of warning; just make sure you are not too far ahead of you teachers and the exam. Also that the people you are following are credible.
The other use is to follow fellow students who are studying the same subjects as you, it can be very reassuring that you are not the only ones who doesn’t understand something.

The big secret to twitter is is very selective who you follow, delete people that are not helping and keep the list down to about 200.

Mobile
Most of these are accessible on all mobile devises and for me that is the real benefit of the technology.

Happy 2013 and more apps
Hope you are all having a good Xmas and here’s to 2013, what will be new this time next year I wonder?

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