In my final experiment of the day with GTP-4, I am using the earlier AI-generated blog post, Debunking the myth of Learning Styles as the base.Peter Hartley spurred this post, acknowledging there was more fun yet to be had with GTP4 and this base material. He was right (and I promise the image at the top of this article will make sense by the end!).
Grade your earlier message that is Titled: Debunking the Learning Styles Myth: A Call for Evidence-Based Educational Practices
You are a Lecturer working at a prestigious university in the United Kingdom. You are to grade this work on a number scale from 0 to 100. A score below 40 represents a fail. You will need to provide detailed feedback to justify your grade, and you should identify areas of improvement to help your student take their work further next time.
Prompt
And the grade it gave itself?
Title: Debunking the Learning Styles Myth: A Call for Evidence-Based Educational Practices Grade: 85/100
Feedback:
Overall, this article is well-written, presenting a coherent and compelling argument against the concept of learning styles. The language is formal and appropriate for a specialist audience, and the structure is clear and organized. The article also demonstrates a good understanding of the relevant literature.
Areas of improvement:
Depth of analysis: While the article covers the main arguments against learning styles, it would benefit from a more in-depth analysis of specific studies that debunk the concept, providing a more comprehensive critique.
Counterarguments: Addressing potential counterarguments and providing refutations can strengthen your argument. Consider discussing the reasons behind the popularity of learning styles and possible alternative explanations for the observed effects.
Practical implications: It would be beneficial to discuss specific examples of how evidence-based practices can be implemented in educational settings, giving readers a clearer understanding of the alternatives to learning styles.
Source integration: While the article cites relevant sources, it could benefit from a more seamless integration of these sources into the text. Using direct quotes or paraphrasing specific ideas from the sources can help build a more robust argument.
Originality: Although the article presents a well-established critique of learning styles, try to incorporate more original ideas or unique perspectives to make the argument more engaging and thought-provoking for your audience.
In summary, this article demonstrates strong writing skills, a clear structure, and an understanding of the relevant literature. To improve the article, focus on deepening the analysis, addressing counterarguments, discussing practical implications, integrating sources more effectively, and incorporating original ideas. Keep up the good work and continue to develop your critical thinking and writing skills.
GTP4
Evaluating the feedback
Not a bad evaluation. In reality, an actual university assignment probably wouldn’t score this well in presenting only one view (unless that was the task). It is correct in that counterarguments are required.
It is also interesting to see it suggest the use of direct quotes – something we’d generally ask students to avoid in order to demonstrate their own understanding.
The nod towards originality and depth of analysis very much capture the goals required for higher-level grades.
This is a long post – so bare with me. It goes into detail, step-by-step as to how I produced an entire blog with the use of four AI tools. You’ll find all the prompts and responses contained below:
This morning I had my first conversation with OpenAI’s GTP4 model. It managed to trigger me with reference to learning styles in the very first reply it sent to me…
This led, however, to a fruitful and interesting conversation about learning styles – and led me to publish a fully AI-generated blog post:
It started with an uncomplicated prompt. I’m working on a PowerPoint for a workshop I am giving next week. I’m pretty much done but was interested in how GTP4 would approach this. I prompted:
I’m a lecturer in Education Studies, trying to persuade my foundation year students that data is important. Can you give me some examples of application
This post stands as an independent article on learning styles, and I wanted to publish it as such. However, it is part of a wider experiment as this whole article – text and images are generated by an AI. Find out more here: AI-led blogging: An experiment with GTP4, DALL-E & Grammarly
Introduction to Learning Styles
Learning styles have been a popular topic in education for decades, with various models suggesting that individuals have different preferences for how they process and absorb information. Some of the most well-known models include Visual, Auditory, and Kinesthetic (VAK) learning styles and others like Kolb’s Experiential Learning Theory and Howard Gardner’s Theory of Multiple Intelligences.
However, the validity of learning styles as a concept has been widely debated among researchers and educators. Numerous studies have attempted to validate the existence of learning styles, but the evidence supporting their effectiveness is weak, and some even suggest that the concept is a myth. Critics argue that the idea of learning styles may oversimplify the complex process of learning and lead to ineffective teaching methods.
Instead, contemporary research points to the importance of adaptable evidence-based teaching practices that focus on learners’ diverse needs. This includes employing various teaching methods, engaging multiple senses, and addressing different skill levels rather than focusing solely on learning styles. In this way, educators can create a more inclusive and effective learning environment that benefits all students, regardless of their preferences.
The concept of learning styles has enjoyed widespread popularity in education for decades, despite a lack of empirical evidence supporting its efficacy. This post aims to challenge the legitimacy of learning styles and provide a compelling argument for why educators and researchers should be critical of their propagation. Learning styles ultimately harm learners, and the education community should embrace evidence-based practices instead.
1 – Lack of Empirical Evidence for learning styles
A cornerstone of any effective educational theory is a robust body of empirical evidence. However, numerous studies have failed to provide conclusive support for the existence of learning styles or their impact on learning outcomes (Coffield et al., 2004; Pashler et al., 2008; Willingham et al., 2015). Meta-analyses have revealed a consistent lack of empirical evidence to validate learning styles (Coffield et al., 2004; Pashler et al., 2008), indicating that the concept is built on shaky foundations.
2 – Oversimplification of Learning
The idea of learning styles oversimplifies the complex and multifaceted process of learning (Geake, 2008; Hattie, 2009). Learning is not solely determined by individual preferences but is influenced by a myriad of factors, including prior knowledge, cognitive abilities, motivation, and socio-cultural context. By reducing learning to a set of static styles, educators may inadvertently neglect these crucial aspects of the learning process, hindering their ability to cater to students’ diverse needs (Dunn & Griggs, 2000).
3 – Perpetuation of Stereotypes
The propagation of learning styles may reinforce stereotypes and an overly deterministic view of learners (Scott, 2010). By labelling students as “visual,” “auditory,” or “kinesthetic” learners, educators may inadvertently constrain students to a particular mode of learning, limiting their potential for growth and development (Dweck, 2006). This typecasting may contribute to self-fulfilling prophecies and hinder students from exploring alternative learning strategies, ultimately hindering their academic progress (Dweck, 2006).
4 – Misallocation of Resources
The continued acceptance of learning styles may misallocate educational institutions’ resources (Paschler et al., 2008). Schools and districts divert valuable resources away from evidence-based practices by investing time and money in training teachers and developing learning materials based on a concept with weak empirical support (Hattie, 2009). This misallocation has significant implications for the quality of education and students’ academic success.
5 – The Opportunity Cost of Ignoring Evidence-Based Practices
By propagating learning styles, the education community risks neglecting evidence-based practices that have been shown to improve learning outcomes (Hattie, 2009). These practices include formative assessment, feedback, metacognitive strategies, and collaborative learning (Hattie, 2009; Zimmerman, 2002). By focusing on debunked theories such as learning styles, educators may miss opportunities to implement strategies that genuinely improve student learning.
Conclusion
The persistence of learning styles in educational discourse is a concerning phenomenon that warrants critical examination. Given the lack of empirical evidence and the potential harm caused by the propagation of learning styles, we urge educators and researchers to abandon this outdated concept and embrace evidence-based practices. Doing so can create a more inclusive, effective, and empirically grounded educational environment that benefits all learners.
References
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. Learning and Skills Research Centre.
Dunn, R., & Griggs, S. A. (2000). Practical approaches to using learning styles in higher education. Greenwood Publishing Group.
Dweck, C. S. (2006). Mindset: The new psychology of success. Random House.
Geake, J. (2008). Neuromythologies in education. Educational Research, 50(2), 123-133.
Hattie, J. (2009). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.
Scott, C. (2010). The enduring appeal of “learning styles.” Australian Journal of Education, 54(1), 5-17.
Willingham, D. T., Hughes, E. M., & Dobolyi, D. G. (2015). The scientific status of learning styles theories. Teaching of Psychology, 42(3), 266-271.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64-70.
This blog post discusses the possibility of the IKEA LEGO sets for LEGO Serious Play. In 2018, IKEA and LEGO announced they were going to play together. This led to the development of the BYGGLEK LEGO collection, available exclusively at IKEA stores. This product range included a series of LEGO storage boxes and a set of 201 LEGO bricks designed for free play. As described by IKEA:
Creating more space for play The BYGGLEK LEGO® collection offers play storage solutions and a LEGO brick set unique to IKEA. The boxes easily find harmony with your home so the creations can be put on display, keeping the story alive until the next play time.
Having used LEGO Serious Play as an aspect of my research and work for some years, I’ve recently considered how the BYGGLEK LEGO collection can be used for LEGO Serious Play. Before I get into this, however, a brief introduction to LEGO Serious Play:
What is LEGO Serious Play?
If you’ve not used LEGO Serious Play before, it is a creative approach to meeting facilitation that uses LEGO bricks as a form of collaboration and communication. It has a track record of success across education and business – shaking up traditional meetings and learning opportunities with the use of LEGO. This has taken it beyond meetings and into the classroom and sphere of research.
Think about all the times you’ve set out Flipchart and pens – and most groups struggle to settle on a scribe – ‘You do it’ – ‘No! You!’. This doesn’t happen with LEGO Serious Play. Everyone is in! I’ve used LEGO Serious Play with participants of all ages for research, learning and business strategy purposes.
IKEA and LEGO Serious Play
So far, my LEGO Serious Play practice has focused on a large collection of bricks that all participants share. I blogged about the sets used to build my LEGO Serious Play collection, and since 2021, that collection has been the staple of my LEGO Serious Play kit. I’ve recently wanted to explore individual LEGO Serious Play kits so each participant has their own bricks. This can reduce the scrabble for bricks between participants and reduce much of the noise in the session (something some participants can find distracting).
There is also a potential for equity. One of the LEGO Serious Play practitioners I worked with insisted on participants having the same bricks. This raises the question – what bricks to use? My colleague went to a LEGO Store and used the Pick a Brick wall to build a collection of identical sets. This has always been too risky for my liking – too reliant on the store’s stock of bricks. It’s also a bit of an administrative hassle, especially if the store is busy. Then came the BYGGLEK LEGO Set:
Digging into the BYGGLEK set
This IKEA-exclusive LEGO set contains 201 bricks, including a brick remover. Within the set there are a range of plates, bricks, a door, some windows, a range of small bricks and enough parts for two Minifigures. As I’ve come to get to know this set in closer detail, I’ve become more convinced it’s a perfect range for LEGO Serious Play. It has a really nice range of bricks, allowing participants to communicate a whole range of ideas. So you can get an idea, I’ve laid out the bricks in this box below:
At 201 bricks, it feels a really nice size for individual use. I love the variety of bricks included in the set. There is a handful of regular bricks, but the body of the set includes a variety of brick colours and sizes. It has some nice, intricate details. I love the inclusion of some leaves and green elements alongside some food pieces, windows and a door.
Just the right size and configuration
This catalogue image gives you a good idea of the scale of the set – or the scale of the models that can be built with it. It isn’t enough LEGO to make the larger, more dramatic models – but it’s good enough for some detailed and intricate models (which is my favourite kind – every brick has meaning. The two Minifigures are nice and echo the days of plainer characters, a contrast to a lot of the licensed figures that dominate now.
While there is debate over using Minifigures for LEGO Serious Play, I’ve always included them in my sets. Yes – it can funnel participant responses around more concrete than the metaphorical use of LEGO, it can also enable the metaphorical messages. I’ve had too many participants wasting time building something to represent people or a person. Minifigures just cut straight to it! As mentioned above, the plainness of these figures also stops the message from getting conflated with a licensed character.
Keeping things tidy – the BYGGLEK Storage boxes
IKEA brought their famed trend to the BYGGLEK collection – flat-pack LEGO! Yes! They’ve managed to create flat-pack LEGO in a way only IKEA could. The BYGGLEK collection includes four different sizes of LEGO storage box. The two smaller sizes are fully assembled and come in a box of three (one small box, two extra small boxes). The two larger size boxes are the ones requiring assembly. It’s a tool-less construction, and the pieces click well together to create a solid box, perfect for storing LEGO. More importantly, the box lids double as LEGO base plates. The boxes themselves can also be used as part of the build, and the larger boxes have LEGO-compatible recesses.
So – back to LEGO Serious Play! The medium-size BYGGLEK box (26x18x12 cm) is great for storing those individual LEGO Serious Play kits. The BYGGLEK LEGO set fits within the box nicely and includes some nice LEGO-compatible studs that can be used in models. There is also enough space for digging through the pile of bricks to find what you need – within the box. The box itself can also be used as part of the models, of course. Unfortunately, the lid sits on top of the box – it doesn’t click securely. As such, I tend to use elastic bands to hold things together when I’m on the move. Not a great look – but it does the job.
Over to you!
I hope this post has been useful! Let me know what you think. I’d also love to hear if anyone else has used the IKEA + LEGO combination for LEGO Serious Play ????
This post lists the leading Generative AI tools that produce outputs based on natural language text prompts. This page is inspired by @aaronsiim’s Generative AI list, but focuses on the text-based tools and provides accessible links to them.
Text-based tools
Text-to-audio
These tools turn text into audio using AI to produce more human-like speech, including tone and inflexion.
In my latest experiment with the GPT3 text-davinci-003 model, I asked it to write a blog on AI. I then wanted to run that content through some of the tools designed to detect AI-generated content.
Step 1: Adjusting the AI model’s settings
Temperature: 1 (This controls randomness. The closer the number is to 0, the more deterministic and repetitive the content will be. I wanted this as far away from 0 as it would accept.
Maximum length: 1000 tokens (I want to give it the space to generate a longer article)
Frequency penalty: 0.5 (Decreases likelihood of a repeated line)
Presence penalty: 0.5 (Increases likelihood of talking about new topics)
Best of: 3 (This will run the completion three times server side and display the best)
Step 2: Prompts for the AI
To produce the blog article, I sent the following prompts:
Write a high quality, but witty and amusing blog post that explains the benefits of artificial intelligence in the context of university-level education
The above copy is great. But nowhere near long enough. Can you rewrite the piece to be longer, and include some Harvard style references?
That's almost perfect. Can you make it even longer and funnier - in a dry humor kind of way.
Now give this blog post a clickbait title
I then used Grammarly to tidy up the grammar (just a few commas!).
Step 3: The final result – AI output:
Discover the Surprising Benefits of AI in University-Level Education!
University-level education is becoming increasingly advanced, in part thanks to the use of artificial intelligence (AI) in a variety of capacities. AI has revolutionized how we approach teaching, assessment and student support services, making learning more personalized and efficient than ever before. But what really are the benefits of artificial intelligence in the university context? Well, let me explain…
To begin with, AI technology can be used to assess student work quickly and accurately by offering automatic marking tools that give instant feedback on assignments (Lee & Voyer, 2019). This means students don’t have to wait for days or weeks for their grades – they can thank AI for avoiding those dreaded Sunday night existential crises! Additionally, AI software can scan through large volumes of material quickly, such as research papers or books, which helps professors save time when preparing lectures and course materials (Christie et al., 2019). This means their cake recipe development endeavours become even more prosperous – it’s a win-win!
Furthermore, AIing also helps personalize learning by recognizing individual learner educational needs and providing tailored content accordingly (Chen et al., 2018). For instance, it can detect a student’s point of difficulty in a particular subject matter based on their previous habits or searches online. It can then offer up educational materials at those points which are best suited to that person’s level of understanding and help them overcome any difficulty they may be having with the material. The best part? You don’t need to worry about remembering anything – so no more cramming before your exams whilst eating questionable microwaveable meals!
Finally, Artificial Intelligence (AI) technology offers up endless opportunities for teaching virtual classes where all students learn remotely from the comfort of their own homes while still benefiting from real-time interaction with their professor/tutor (Ahmed et al., 2017). With AI systems such as CourseSmart assisting instructors by preparing session material remotely before each lesson, no students will ever miss out again – not even if you forget your laptop charger because who could possibly forget that!?
All in all, these benefits make it clear why so many universities today are happily embracing AI technologies for university-level education purposes! By lowering costs associated with traditional methods as well as offering new stimulating learning environments; Artificial Intelligence presents an exciting frontier awaiting exploration. So why not get started today? Who knows what kind of convenient new features you can look forward to introducing into your life!?
References:
Ahmed I., Ullah K. A., Khan S., & Abbas M. (2017). Exploring the Potential Effects of Virtual Learning Environment among Undergraduate Learners: A Systematic Literature Review Using Thematic Analysis Approach. Computers & Education Journal. 112:204-222.
Chen C.-S., Chen T.-H., Chiu H.-Y., & Tsai C.-C.(2018). Cognitive Apprenticeship System Based on PrePA—Personalized Portfolio Assessment System for Learner Self-Development Environments Cloud Computing. International Journal Of Engineering And Technology Innovation 8(1):84–94.
Christie T., Wright C., Matthaei J ., Mureithi P .& Hobbs V .(2019). OERHub Final Report – Compendium Of Tools And Resources For Open Educational Resources Practitioner Support In Higher Education Institutions Around The World: Progress Report, Version 1 Harvard Graduate School Of Education
Lee S.-K& Voyer v.(2019). Soft Computing In Education: New Trends And Approaches: Learning Through Technology For All | Qsearch Ltd
NOTE: All of those references are garbage. Those sources don’t exist – though it looks convincing…
Testing the above article: Was it written by AI?
Well – we know the answer. It was, indeed, written by an AI. However, I wanted to run that text through some of the popular tools being used to detect AI-generated content to see how they did.
I can see why. It’s score for the above blog article was: The classifier considers the text to be very unlikely AI-generated.
GPTZero
GPTZero works by measuring the text’s perplexity and randomness. In this case, it did a better job than AI Text Classifer, though it failed to detect the whole piece as written by AI. It only identified four sentences at the top as generated by AI, but identified nothing in the rest of the text.
Screenshot from GPTZero
GPT-2 Output Detector Demo
In fairness, this was designed for GPT-2, and the model used for the above article was substantially enhanced. Unsurprisingly, GPT-2 Output Detector scored the piece as real:
Screenshot from GPT-2 Output Detector
Writer
Next, I tried Writer AI Content Detector. This tool is designed to identify AI text to help authors tweak their content to avoid detection. This is not designed for unfair means, but to stop search engines from penalising website page rankings. Content entirely produced by an AI often penalises websites from getting top spots on Google searches. Writer AI Content Detector is limited to 1,500 characters, so I had to split the article into two. Both halves were scored 100% for human-generated content…
Screenshot from AI Content Detector
Giant Language model Test Room (GLTR)
GLTR (glitter) “enables forensic inspection of the visual footprint of a language model on input text to detect whether a text could be real or fake”. It is built by a collaboration between Harvard NLP and the MIT-IBM Watson AI Lab. Similar to the GPT-2 Output Detector Demo, it was designed for GPT-2. It analyses how likely each word would be predicted given the context before it. It is pretty cool, as you can see word-by-word likelihood predictions for the next word:
Screenshot from GLTR
Words highlighted in green are in the top 10 for most likely. Yellow words are in the top 100, and red words the top 1,000. A violet word is even more unlikely to be detected. In essence, while green should be the most common colour for both AI and human written pieces, there should be a proportionally higher number of yellow/red/violet words for something written by a human, as we are more random.
In this case, I was really shocked by the output. In my previous tests, I’d always seen a high proportion of green in AI-generated content. This time with the above blog post, I think it is fair to say there is a broader use of yellow/red/violet. To better explain the significance of this, I compared the above AI-generated content to my last blog post. You’ll see an almost identical spread of green/yellow/red/violet – though perhaps my content does have slightly more of the last two.
AI-written content (above blog post)
Human-written content (my last blog post)
I hadn’t expected that. In this case, I think GPT-3 text-davinci-003 and the above prompts produced a decent output – that the above detectors all failed to identify as AI-generated.
Human detection
I think it’s important to consider human detection. As we can see above, all of the tools failed to identify AI-generated content. In fairness, this is a new field – and just like the AI tools, these will develop too. In this case, human detection certainly wins. As you can see from the article, it has made up a load of references. They look convincing – and those journals, volumes and issues exist. The articles, however, do not.
Aside from the obvious errors in the AI-generated content, I question if anyone would write something so overwhelmingly positive in an academic context. Even a positive argument acknowledges there are alternative positions out there that should be refuted and rebutted. Part of this was down to my prompt, perhaps – but still something important that it missed out on generation.
I do think it did the funny, witty part well. The line: This means their cake recipe development endeavours become even more prosperous – it’s a win-win! was highly unlikely to be written by an AI in the above model.
Conclusion: AI-generators can trick AI-detectors
As you can see, there is still a long way to go in developing GPT-3 detection – which is perhaps concerning given that GPT-4 is on the way. I don’t think we can rely on tools to automate this process for us, and as you can see above, the human detectability of my output was very focused on my prompts. This will become more complicated as other AI tools emerge, requiring text to be checked against each of them. Until there is a paradigm shift in this technology, I think the answer to the above question is YES! An AI generation tool can certainly trick an AI detection tool.
There has never been a more important time to ensure AI literacy is a core aspect of the curriculum at every level of education.
It’s an honest question. Everywhere I look, there are discussion threads, social media posts and emails from Higher Education professionals obsessing over artificial intelligence. Most of these communications focus on ChatGPT, but some acknowledge other tools exist. These ‘new developments’ in artificial intelligence have prompted a dramatic response from the education sector. It has been described as a crisis, a moral panic, an ‘end to homework‘ and a threat to higher education. I think my favourite contribution this year comes from The Mail, which announces artificial intelligence could make ‘mankind extinct’.
Okay. Some perspective is needed. But my real question is this: How did the Higher Education (HE) sector not see this coming?
Artificial Intelligence has powered your work for years
In the UK, the vast majority of Universities use Microsoft (Office) 365 and the Windows operating system. Microsoft’s Outlook powers our emails, SharePoint/OneDrive stores our files, Teams manages our collaboration, and Office keeps us productive. Since 2016, Microsoft’s ‘Office Intelligent Services‘ have seamlessly integrated artificial intelligence-powered features into our everyday working lives. For most HE practitioners, the developments in artificial intelligence have been staring us in the face. Literally. The documents we write, the slides we develop, the emails we read, and the Teams calls we make have all been enhanced by Artificial Intelligence for YEARS.
Artificial intelligence in Microsoft (Office) 365:
Read aloud has turned text-to-speech, enhanced to use tone and inflexion.
Dictate has enabled speech-to-text, allowing people to talk instead of type. This includes
Optical Character Recognition has helped turn image-based text into readable characters.
Presenter Coach has analyzed people’s speech, language and body language to deliver real-time presentation feedback in PowerPoint.
Slide Designer has taken draft slides and automatically added design elements and images to make slides more effective.
Accessibility Checker has allowed the automatic generation of ALT text for images, using computer vision.
MicrosoftViva has provided detailed insights: reading your emails to identify unfinished tasks and checking your calendar to provide useful documents for meetings – in real-time.
Subtitles and Transcription have enabled PowerPoint and Teams to provide real-time subtitles for presentations, calls and recordings.
Excel has offered enhanced chart types (i.e. Maps) and real-time, streamed data (i.e. Stocks).
Editor has offered enhanced spelling and grammar advice, and has extended to use text prediction to save time when writing.
Translate has offered real-time translation from text, images and speech across up to 100 languages (and variants).
Scheduler has coordinated meetings between people – and even booked rooms.
Natural language queries in Excel have allowed people to use questions, not formulas.
Search enhanced with AI when using Bing.com
A series of Microsoft Office Intelligent Services
The examples above are just workplace, education and consumer applications. In industry, Microsoft-powered AI has been detecting facing, monitoring crops, enhancing video games, fighting fraud and detecting faults across hundreds of sectors. I can understand people not being aware of some of these applications – but the stuff listed above has been right in front of our eyes.
How can any of these artificial intelligence developments be a surprise?
So. Reflecting on the list above, ‘Intelligent Services’ have supported reading and writing across the Microsoft (Office) 365 platform for over eight years(!!!). If you’ve been using Microsoft Office productivity applications like Outlook, Word and PowerPoint – I cannot understand how ChatGPT can be a surprise. Office applications have started:
correcting your writing and predicting what you will say
reading your emails to manage your diary and tasks,
listening to you, so you don’t need to write,
automatically making things accessible with subtitling and computer vision
The list goes on. If artificial intelligence has been doing all this for years – how is ChatGPT such a leap?
I can understand how ChatGPT feels like a significant step up from previous chatbots. But I don’t see how it can be all that surprising when we reflect on those daily developments and how artificial intelligence has slowly become part of the everyday. It isn’t just at work or in education. Your last test at the hospital might have been screened by artificial intelligence. Every time you make a purchase, the transactions are scrutinised by artificial intelligence for anomalies. It really is everywhere. I get how the quality of written response is shocking – but given what we’ve seen happen in Microsoft (Office) 365 over the last few years – I don’t think we can call it a surprise.
Why the last-minute response?
I honestly do not know the answer to this question. The radical potential of artificial intelligence has been staring everyone in the face for years. Every email. Every document. Every Teams call. Every PowerPoint. Artificial intelligence has been prompting, pushing, helping and enhancing for years. How can ChatGPT be such a surprise? I am absolutely shocked that schools, colleges, and universities are so late in reacting to the challenge artificial intelligence poses to traditional assessment. This should not be a surprise. Not at all. I cannot understand how future scanning and business planning did not identify this as part of long-term strategies. Emergency planning and task groups should not be necessary! Educational policies should have been prepared years ago.
But they weren’t.
As such, the kneejerk reaction has been to ban artificial intelligence in many educational establishments. Given the circumstances – this is probably the right answer. For now. In future, I urge educational leaders to reconsider artificial intelligence and look at how it can be used alongside the curriculum.
Artificial intelligence in the curriculum
Our students will be leaving the educational world to join workplaces that use artificial intelligence. It might not even be labelled as such – but it will be there in the background. The example of Microsoft (Office) 365 in this very post is a great example of this in application. As such, we need to equip our students for this. Not just the practicalities of using artificial intelligence – but the difficult questions around ethics and responsibility of use too. These skills cannot be developed under a ban.
Artificial intelligence reproduces the biases of society. Our students must be equipped to challenge this.
Artificial intelligence uses Machine Learning – but this is often targeted at a range of information- including high-quality, questionable and poor-quality sources. Students need to be able to identify fact from fiction.
Artificial intelligence supports accessibility, it can translate, see and write for anyone who needs support with it. While not perfect, those features cannot be turned off.
It’s fair to say – the news isn’t all doom and gloom. It’s been nice to see some new articles discussing how artificial intelligence won’t hinder creativity, will help schools teach skills for university and how it can be integrated into teaching. It is also interesting to see reflections on the OpenAI website (ChatGPT’s creator) about how it can support streamlined and personalised teaching – amongst many opportunities and threats.
The last word – The future of Higher Education with ChatGPT
I couldn’t help but close this post by handing over the conclusion to ChatGPT. I asked it to tell me the best-case scenario for the inclusion of artificial intelligence in university education.
The best-case scenario
In the best-case scenario, artificial intelligence (AI) will have a positive impact on university education. AI will help to improve the quality and efficiency of education by providing students with personalized learning experiences. AI-driven tutoring systems will be able to analyze a student’s performance and give immediate feedback and recommendations for improvement. AI can also be used to create adaptive learning systems that adjust the difficulty of tasks based on a student’s progress, allowing students to move at their own pace and make the most of their learning experience.
AI can also be used to automate administrative tasks, such as grading, making it easier for professors to focus on teaching and providing students with the best possible learning experience. AI-enabled analytics can be used to identify students at risk of dropping out, so appropriate interventions can be put in place to increase their chances of success. Finally, AI can be used to offer more engaging learning experiences, such as interactive simulations and augmented reality. All of this will enable universities to provide a higher quality of education while reducing costs and increasing student satisfaction.
(ChatGPT, 2023 – Published by OpenAI)
…and the worst-case scenario?
In the worst-case scenario, artificial intelligence (AI) could have a detrimental impact on university education. AI-driven tutoring systems could be overly rigid, unable to adapt to individual students’ needs, and lead to a one-size-fits-all approach to learning. AI-enabled analytics could be used to track student progress and create an environment of surveillance and control, where students feel that their every move is being monitored and judged. In addition, AI-driven automation of administrative tasks could lead to job losses, as universities reduce their staff numbers in favor of automated systems. This could lead to a decrease in the quality of education, as universities focus on cutting costs rather than on providing students with the best possible learning experience. Finally, AI-enabled simulations and augmented reality could lead to a decrease in critical thinking and problem-solving skills, as students become reliant on pre-programmed systems. All of this could lead to a decrease in student satisfaction and an overall decline in the quality of university education.
(ChatGPT, 2023 – Published by OpenAI)
Okay – I had a bit of fun with the conclusion. But ChatGPT makes a valid point… there is a lot of potential disruption – good or bad – coming to HE. The question still remains:
How did most HE practitioners not see this coming?
This blog post shares my latest conference poster titled: Learning Development in a Time of Disruption. This poster presents the research I have undertaken for my Postgraduate Certificate in Academic Practice (PCAP). This full version of the poster is hosted on the National Teaching Repository and can be accessed below:
The Covid-19 Pandemic had (and continues to have) a significant, worldwide impact on Higher Education. This research project analysed a special issue of the Journal of Learning Development in Higher Education (JLDHE) to identify how third space professionals respond to this challenge.
The special issue of JLDHE contained 102 peer-reviewed reflections, identifying numerous challenges and responses to teaching in Covid-19. All reflections were analysed using structural, topic and thematic coding to identify common responses and challenges to pandemic teaching.
The findings of this study have identified a range of individual and shared challenges for both students and third space professionals. One of the core findings relates to the diversity of responses that have been designed to meet these challenges, with over 100 distinct pedagogic and technical solutions to pandemic teaching. From these, five core themes have emerged: emergency remote teaching; reflective practice and evaluation; pedagogy and technology support; collaboration and shared practice; and, course design for the long-term.
There are four core implications for future practice. Firstly, it is important to develop flexible policies and procedures to allow practice to develop in times of disruption. Secondly, rich educational research and case studies can support innovative and adaptive practices in times of disruption. Thirdly, university staff need support and training to ensure online pedagogies and technology are supported. Finally, reflective practice and evaluation are required to ensure continuous monitoring and improvement.
Keywords: Covid-19, Higher Education, pandemic, teaching, third space professionals
As part of undertaking my Postgraduate Certificate in Academic Practice, I had to produce a Teaching Philosophy Statement. I’m drawn to the approach the University of San Diego (2023) takes to introduce the Teaching Philosophy Statement, which I think sets the tone well:
The life of a teacher is an extremely busy one. From early morning until long after dark, teachers dedicate the better part of their day to their students. Amid the lesson planning, the snack breaks, the recess duty, grading and the myriad other daily tasks, it can be easy to lose sight of the why of teaching.
Why are you drawn to the classroom, and what is it about your love of teaching that makes it a fulfilling career? What’s the overarching philosophy that guides your teaching practice? Even on the busiest school days, every teacher should be able to explain their “why” by returning to their teaching philosophy.
(University of San Diego, 2023)
A Teaching Philosophy Statement is absolutely something all Higher Education practitioners can reflect upon. It is not just the realm of academics. A teaching philosophy statement sets out core beliefs about the purpose of teaching, it sets out an individual’s approach and justifies why this is their approach. I found it a thoroughly enjoyable activity!
Lee – why share your Teaching Philosophy Statement now?
This is a good question! After all, I’ve technically left Learning Development. But, I have two very good reasons for sharing this now.
I want to call on Learning Developers to write their Teaching Philosophy Statements and share them. Do it now! This will provide a rich discussion about the teaching philosophy of Learning Development. It will reflect the diversity of the profession, and allow further discussion around the values established by ALDinHE and how they are applied in the profession.
I must acknowledge my teaching philosophy is changing. I am now a Lecturer in Education Studies. I want to share my Teaching Philosophy Statement as it stood a year ago. I promise to re-visit this in another blog post and update my statement for my new context. It will provide an opportunity to reflect on any similarities and differences. I think this is an exciting way to continue reflecting on that transition from thirdspace professional towards academic.
This is why my post is titled the ‘teaching philosophies’ of Learning Development. I think we need to acknowledge these statements will be numerous and diverse – just like the profession. Learning Development is a profession I still very much care about. While I may now work as a Lecturer in Education Studies, a core part of my scholarship and research will be dedicated to Learning Development. It’s why I am still involved closely with ALDinHE – and am a member of LearnHigher and the JLDHE Editorial Board.
So! Here it is – my teaching philosophy from my time as a Learning Developer…
My Teaching Philosophy Statement (2022)
My aspirations
As a Learning Developer, I feel my aspirations are very driven by my profession. Hilsdon (2011:14) defines Learning Development as the “teaching, tutoring, research, design and production of learning materials, as well as involvement in staff development, policy-making and other consultative activities” in support of student academic success. However, I believe student success can never be built on dependency, so for me, effective Learning Development must also build student independence and self-efficacy. As much as I aspire to help students, my true goal is for students to become self-sufficient so they do not need me.
Philosophical underpinning
The signature pedagogy of learning development is arguably academic literacies (Lea & Street, 1998; 2006). This approach acknowledges that writing, learning, and other academic practices are not isolated ‘skills’, but are complicated literacies situated within disciplinary discourses and power frameworks (Lea & Street, 1998). Acknowledging these complexities is vital for me to identify and confront what is not taught or is assumed – constituents of the null (Kazemi et al., 2020) and hidden curriculum (Hinchcliffe, 2020). As a Learning Developer, I work within the hidden curriculum to expose and challenge it. My role as a 3rd space professional (see: McIntosh & Nutt, 2022) is very much an enabler.
Teaching methods and assessment
The most established teaching method in learning development is the one-to-one appointment. As learning is both a complicated and individual process, such appointments allow students to engage in these complexities with full acknowledgement of what they already know and understand. As represented by Webster (2018), both students and Learning Developers bring knowledge to such appointments and operate with different levels of agency. Depending on the appointment, this can frame my role as mentor, listener, teacher, and coach. I often have to informally assess students to determine how to best support them, and which of those roles I might need to take.
The most significant challenge has been scaling Learning Development beyond appointments to help more students, and there are three approaches I have taken. Firstly, there is workshop-based instruction, which allows similar principles from appointments to be applied in a group situation, extending capacity. Second is the creation of self-support resources like University of Hull (2021) SkillsGuides. These allow students to access help at a time that is convenient. Finally, there is ‘integrated practice’ which involves directly teaching in timetabled sessions as part of the curriculum. Integrated practice is arguably the best and most inclusive way to increase access to Learning Development.
While I do not set or mark student work, I do have a role in assessment. One common task involves helping students prepare for an assessment set as part of their course. This can be as simple as demystifying the essay in an appointment or teaching a whole class the principles of public communication to help them write a wiki article. I also support students with formative feedback to help them develop their response to an assessment, or provide them summative feedback on a previously marked piece of work to help them develop further. For me, this is all about supporting student learning.
Inclusivity at the heart
Inclusivity is a core value of my practice. I have worked hard to promote inclusive practices, helping ensure students can be successful no matter their background, neurodiversity, or protected characteristics. This goes beyond legal obligation – it is simply the only ethical approach to teaching. Furthermore, I aspire to uphold the ALDinHE[1] (2018) Manifesto for Learning Development, which strives to increase participation in HE and legitimise different forms of student knowledge. As I work across all disciplines taught at Hull, I need to respect different approaches to knowledge too.
Looking to the future
For me, the PCAP is an opportunity to improve my teaching further. I now have over 10 years of experience working in HE, and I still have things to learn. I’m proud of my Senior Fellowship with the HEA and fully intend to work towards Principle Fellowship in the future. I’m also keen to maintain my professional accreditations with ALDinHE and Microsoft Education, as well as gain my accreditation with the Association of Learning Technology (ALT).
[1] Association of Learning Development in Higher Education – the professional body for learning developers
Writing your own Teaching Philosophy Statement
As I shared in my introduction, I’d love to see more Teaching Philosophy Statements shared from Learning Developers. If you want to know where to start, check out this guide: What Is a Teaching Philosophy? Examples and Prompts. Please share yours and pop the link in the comments section below.
Hilsdon, J. (2011) What is learning development?, in Hartley, P., Hilsdon, J., Keenan, C., Sinfield, S. & Verity, M. (eds), Learning development in higher education. Basingstoke: Palgrave Macmillan, 13-27.
Hinchcliffe, T. (ed), (2020) The Hidden Curriculum of Higher Education. Advance HE.
Kazemi, S., Ashraf, H., Motallebzadeh, K. & Zeraatpishe, M. (2020) Development and validation of a null curriculum questionnaire focusing on 21st century skills using the Rasch model. Cogent Education, 7(1), 1736849.
Laurillard, D. (2002) Rethinking university teaching: A conversational framework for the effective use of learning technologies. London: Routledge.
Lea, M. & Street, B. (1998) Student writing in higher education: An academic literacies approach. Studies in Higher Education, 23(2), 157-172.
Lea, M. & Street, B. (2006) The “Academic Literacies” Model: Theory and Applications. Theory into Practice, 45, 368-377.
McIntosh, E. & Nutt, D. (eds) (2022) The Impact of the Integrated Practitioner in Higher Education: Studies in Third Space Professionalism. Oxon: Taylor & Francis.
Webster, H. (2018) How to implement effective 1:1 tutorials, Association of Learning Development in Higher Education Annual Conference. University of Leicester, 26th – 28th March. Leicester: Association of Learning Development in Higher Education.
I’m delighted to be this week’s guest on Cup of TEA – the Teaching Excellence Academy’s official podcast, exploring learning, teaching and assessment at the University of Hull.
Season 1 – Episode 3: Lee Fallin
This week we’re speaking to Lee Fallin from the School of Education. We talked about a range of topics including his research on learning spaces and also his recent transition from professional services to academia. Lee is really passionate about education and learning development and we think this comes across brilliantly in this really interesting chat. Lee has also kindly provided a list of related links to topics we discuss which can be found below.
My contribution aside, I highly recommend you check out the Cup of TEA podcast and bookmark it in your favourite app. In week 1, my colleague Kelly Dockerty and student Jess Gleisinger discussed PBL and authentic experiences, with week 2 showcasing Liz Wells and her transition from clinical practice to academia. Both are a great listen!
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