Back to the future?

by Zac Woolfitt, Inholland University, The Netherlands.

On June 20th and 21st, I joined the Media and Learning Conference in Leuven, Belgium. I’ve been involved each year since 2014 and although I missed last year, I was glad to be back to catch up with old friends and colleagues. (Disclosure – I am a member of the conference advisory committee). This year’s theme, ‘Back to the Future?’ asked ‘Will we make a gradual change to traditional campus-based learning services or jump into the transformative potential of AI and Immersive Learning technologies?’ There were more than 60 speakers, moderators, and workshop leaders, as well as 226 participants from 20 countries, including the USA, Australia, and South Africa.

This report only covers the sessions I attended in person. There were so many great workshops and other presentations. You can access the full overview at the event page. (My apologies in advance if your session is not mentioned in this report).

Editor’s note: Long Read – Reading time 15 – 20 minutes.

Balancing Humanity and Technology: KU Leuven’s Approach

In the opening address, Piet Desmet, Vice Rector of KU Leuven, emphasized the importance of maintaining a human touch during rapid digital and AI developments. He referred to KU Leuven’s 2017-2021 digital strategy, and outlined seven key principles essential for integrating technology to enhance learning while staying human:

Embracing transformation through models like SAMR can help move beyond mere tech substitution to redefining educational tasks. Avoiding silos and ensuring seamless access to all tech tools through integrated solutions like the Toledo portal is essential. Innovations should be scalable to be effective, as seen with KU Leuven’s Learning Lab and MOOCs. Adopting agile methodologies allows for rapid and effective tech integration and continuous improvement. It is crucial to prioritize support for educators through networks and professional development initiatives. Finally, employing evidence-based practices by testing small-scale solutions, such as 3D VR experiences, ensures impactful wider implementation. They offer a free course ‘Online training on AI in education’ with four modules.

He closed by saying ‘Wisdom is knowing what to do next, skill is knowing how to do it, virtuousness is doing it.’ It is impressive to see the strategic alignment within KU Leuven from top to bottom of the organisation, and that they continue to embrace technology to support their learning.

Democratising Technology in Higher Education: Is Innovation Leaving You Behind?

Amanda Murphy from Storyfutures, UK, is a BAFTA award-winning producer and researcher at the Royal Holloway University of London. She shared some great examples (recording, presentation) of using technology to democratize education, by making tools like Extended Reality (XR) accessible to a wider audience creatives. She certainly inspired me to be more ambitious in my own approach to technology. By integrating old and new technologies, higher education can create more situated learning experiences. She shared examples like the “Virtual Veronese” project (from a few years ago) at the National Gallery as an example of how 3D modelling can bring a 16th-century chapel to life, attracting many younger audiences and families.

Virtual Veronese uses VR to situate a painting in its original setting.

Her projects emphasize the importance of practical, hands-on learning. Story Trails had some creative examples of using archival materials to create immersive, place-based storytelling experiences. This shows how accessible tech can engage the public with history in new ways. By using simple, free tools like Scaniverse for scanning people, objects, and places, educators can help students and communities tell their stories in new ways. Bringing technology into teaching can help creativity and inclusivity, making sure no one is left behind as technology advances. Involve students at all levels, learn through practice and use AI to enhance learning experiences.

To make these projects possible, quite a lot of money was raised through sponsors. However, she challenged us to take our teaching to the next level and I plan to be more ambitious in my next projects. Using AR and XR is possible, and the results take familiar subjects to the next level.

When Machines Learn Too: Understanding AI’s Capabilities

Maarten Lamers from Leiden University introduced himself proudly as one of the top 100 ‘nerds’ in the Netherlands. He likes to ‘categorise things’ and has been involved in AI for so many years that he moved on a long time ago. Luckily for us, he is back. His clear yet quirky presentation was spot on and had the audience focused throughout. He gave a brilliant, yet simple explanation of how data can give meaning to otherwise meaningless words. At least meaningless from the perspective of a machine. One important aspect is measuring the distance in text between words, coding them in relation to each other, then predicting which words are most likely to be where. It’s the best explanation I’ve seen so far on how machines (help us) make sense of data.

We have shifted from ‘procedural knowledge’ (understanding and being able to perform a sequence of steps or actions to achieve a specific outcome) to ‘declarative prompting’ (specifying what you want the outcome to be without needing to know the detailed steps to achieve it). Now we don’t need to know the steps, we simply clearly describe what we want the end result to be and let AI do the rest. He sees AI’s main function as assisting humans by recognizing patterns in data. The inner workings of AI are complex and often opaque, leading to unexpected, inaccurate, or ‘hallucinated’ outcomes.

How AI works finally seems to make sense

He encouraged us to understand the potential and limitations of AI. While machines can help us recognise patterns and process large datasets, their interpretation may not match our human expectations and can have bias. (e.g., AI used by Amazon to screen resumes unintentionally favoured male candidates due to biased training data.)

We must be aware of such biases when we use AI to complement our human creativity and decision-making. Lamers cited Margaret Boden’s framework on creativity, suggesting that while machines can generate new combinations of data, they lack the inspirational and experiential context that fuels human creativity. An artist such as Bob Ross creates within an established set of rules. Whereas artists such as Mondrian made original leaps during their artistic development and redefined the scope of their creative space. He quoted Ada Lovelace on her views on the capability of machines. Almost two hundred years ago she wrote that “The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform. […] Its province is to assist us in making available what we are already acquainted with.”

It is going to get very interesting once AI gets truly creative (if it ever can) and starts generating things outside the information scooped up in its training models. This was an engaging and well delivered set of three keynotes that set the tone for the rest of the conference.

Empowering Educators: Innovative Tools for Course Creation and Immersive Learning

This session looked at different approaches to enhancing the skills of teaching staff in the use of educational media, AR and VR.

Elke Van der Stappen and Anneleen Cosemans work at KU Leuven’s Course Creation Services. They merge technical, didactic, and multimedia support to enhance course development. Their intensive 4-5 day bootcamp is for educators who want to create MOOCs. They provide a scalable solution for multiple teams. The bootcamps involve a range of experts and cover everything from defining learning goals and target audiences to developing captivating storytelling techniques.

Built into the bootcamp is the process includes iterative evaluation, beta testing, and a quality gate system ensuring strong didactic design before multimedia creation begins. This approach significantly reduces the time needed for course development, giving educators skills they can apply across their teaching practice. With 150 developers across faculties, KU Leuven has created a support system that guides educators through the entire process.

Mary Godfrey from Harvard University highlighted the use of generative AI tools to enhance case-based learning. At short notice, she interviewed 60 Harvard faculty who were addressing the challenge of using Generative AI in their teaching and learning. The short videos can be found here. I recommend taking a look at one or two of them for inspiration. Examples of AI usage include improving grant writing, facilitating data analysis for non-coders, creating novel legal problems, teaching through chatbots, enhancing student course preparation, reducing plagiarism, and understanding student learning in real-time. They are also leveraging AI for interactive games, creative design processes, effective written communication, and solving real-world problems, showcasing the versatile applications of AI in education. E.g., Richard Schwartzstein uses AI’s incorrect answers as teaching moments, demonstrating AI’s limitations.

Harvard’s ‘system prompt library’ provides educators with pre-built prompts to facilitate teaching and learning. I asked Mary if all faculty were adopting AI enthusiastically and she said not all were. She explained that the examples here are good practices. These professors find it is pushing them to rethink and innovate their teaching strategies.

Faculty Voices: Examples of how some professors at Harvard are using Gen AI  

Dr. Gabriel Jones from the University of Leeds highlighted the challenges and potential of using immersive VR in higher education. They have conducted a survey recently and he presented some data on that. Central to the research was the (UTAUT) Unified Theory of Acceptance and Use of Technology. It suggests that ‘the actual use of technology is determined by behavioural intention. The perceived likelihood of adopting the technology is dependent on the direct effect of four key constructs, namely performance expectancy, effort expectancy, social influence, and facilitating conditions.’

Despite VR’s ability to enhance teaching quality, significant barriers such as cost, lack of engagement, and concerns about support and inclusivity restrict widespread adoption. The Helix Innovation Hub at the University of Leeds is making efforts to make VR more accessible, but only a small percentage of faculty plan to use it soon. Many educators recognize VR’s pedagogical relevance but hesitate due to uncertainties about practical implementation and available support. Institutional support and peer influence are crucial for increasing VR adoption in educational settings. Educators see the benefits of VR, but concerns about implementation difficulties and lack of support are prevalent. Encouraging factors include fun and engaging experiences, yet there is mixed confidence in VR’s pedagogical relevance and low institutional expectations remain challenges. We are still not there yet using VR at scale within higher education.

Stéphanie Vanneste from Vives University of Applied Sciences shared insights into the XR Zone initiative in Flanders. They distributed 250 XR boxes to schools. These boxes include various tools like Pico 4 headsets and scanning iPads, enabling schools to explore XR technology in a practical, hands-on manner. Their solution is to make the equipment easily available and let the schools get on with it. The initiative supports professional development and includes ergonomic setups for comfortable XR experiences. Schools can enhance 360-degree videos with their own content and assess their preparedness for XR integration. They are trying to democratize access to XR technology, encouraging educators and students to experiment with and adopt immersive learning tools.

Providing a box to 250 schools with VR equipment, instructions and an action plan

Re-thinking Teaching and Learning spaces and approaches in higher education.

I was glad to have the chance to moderate a session on innovative teaching and learning spaces in higher education. Pre- and post-Covid I’ve conducted research into different forms of Hybrid Virtual Classrooms so it is a subject close to my heart. I was joined by Johanna Fenton from the University of Leeds in the UK, Dr. Jan Petrus Bosman from Stellenbosch University in South Africa, and An Verburgh, an educational researcher at UCLL in Belgium.

An Verburgh, Johanna Fenton, Zac Woolfitt and Dr. Jan Petrus Bosman discuss re-thinking teaching and Learning spaces

Over the past year, Leeds has implemented multimode teaching spaces and recruited students as Multimode Assistants (MMAs) to support faculty. These student assistants are paid and provide lecturers with technical support, help with training, and ensure smooth interaction between in-person and online participants. The initiative has shown that when staff receive adequate support, they are more willing to experiment with ambitious hybrid teaching contexts. They need to ensure continuous evaluation and feedback which are crucial to refine the approach. In Stellenbosch there is a focus on the stark contrasts between pre- and post-pandemic realities and the limitations of unchanged institutional systems. UCLL prioritises designing blended learning environments that achieve specific learning outcomes in complex communication.

Their insights show common themes such as the complexity of hybrid teaching, the necessity of strong support systems for staff, and the importance of an ongoing design processes based on user feedback. These shared experiences show the need for thoughtful planning and resources in creating effective hybrid learning environments. The session raised several questions: How do pre- and post-pandemic realities influence hybrid teaching strategies? What balance should be struck between standardized support and differentiated design? How can specific learning outcomes be effectively built into broader hybrid models? These considerations are crucial for educators looking to enhance their own teaching practices in a rapidly evolving educational landscape. It was an enjoyable session with questions from the audience

Some pros and cons of new and innovative technologies

Day two began with three keynote from Lizzy Bleumers, Thomas More University of Applied Sciences, Belgium, Gary Burnett, Loughborough University, UK and Maya Georgieva, Innovation Centre, XR, HCI, AI & Quantum Labs, The New School, USA.

At Thomas More University of Applied Sciences, they emphasise the importance of embracing AI to enhance teaching practices and overcome digital divides. Educators are encouraged to develop AI literacy and adopt a nuanced approach, utilizing resources like Magic Slides, Mediagenie, and Wakelet to integrate AI into their classrooms effectively. Practical applications of AI include tools like Maia, which assists in lesson planning and student engagement, and Enlighten AI, which streamlines assignment creation and feedback. They also refer to the SAMR model (see above) as a framework for leveraging AI. They start with AI in small, manageable ways and critically reflect on its outputs. It is good to reflect on how you might start incorporating AI in your teaching practices, and what meaningful applications do you see for your classroom.`

Loughborough University are using immersive technologies for student engagement. I was inspired to see the different examples of using Virtual Reality to create a sense of presence and involvement. Students enter immersive scenarios as avatars and learn in this context. It raises interesting questions about how students act and learn differently when in a 3d online context as an avatar. They can take on different perspectives, stepping into the role of a lawyer or witness, which can deepen their understanding and empathy for the subject matter.

Gary also talked about his innovative uses of holograms. Back in 2020, I had the chance to teleconference as a Hologram between London and Toronto and I see potential in this format for specific learning contexts. Gary collected data from students who experienced a lesson from him as a hologram (and a control group of students who didn’t) and were then tested on their retention.

My experience is that interacting with a life-size hologram is very cool and has a certain wow factor, that engages the students in a different way. However, will this only be a novelty effect when we bring in external speakers? Or will learning reach new dimensions when we create realistic interactions with historical figures? As educators, we still need to balance the digital with the physical. You can incorporate real-world props and scenarios to enhance the learning experience which can make lessons more dynamic and impactful.

During my own experience of being recorded as a hologram, I found it difficult to see the interviewer I was talking to (or as a teacher, the class of students). Engaging with the audience in a meaningful way will require extra planning and cognitive load from the educator. Once recordings studios (hologram capture spaces) are set up in various cities, then guest speakers can be recorded there and beamed into different educational locations. ABBA and various other musicians are being reincarnated as AI enhanced Holograms. Once this technology becomes more accessible and less expensive, I imagine we can see it occurring in more educational settings. It is great that Gary is also focused on the learning effect for students, rather than the wow factor.

Maya Georgieva gave a dynamic and inspiring overview of some of the many different ways there is convergence of creativity, technology, and ethics in education. We should embrace emerging technologies like VR, AR, and AI. Integrating design thinking into education can help students engage in immersive storytelling, collaborative projects, and hands-on learning that extends beyond traditional classroom boundaries.

It was great to see an excellent example of one of her student projects being showcased in this international context. Students developed a fully immersive VR game called ‘The Life of Bees’. Designed to challenge our thinking, we start the game from the perspective of a farmer in the U.S., putting on a protective suit, and going out to spray crops with pesticides. Halfway through, we switch to the perspective of the bee. This cleverly highlights the complex space where commercial issues of farming clash with biodiversity and the ethical issues of how we should manage our planet. This was a fantastic professional product. All credit to the student creatives who reached the next level with this project. It is clear that students are the creators and architects of their (and our) own future. Genuine learning occurs through experience and reflection. We should challenge our students and support them using AR/VR/AI during the next learning curve. If you get a chance to see Maya speak, don’t miss it!

The 3d beehives on the farm which you walk through in the role of the ‘farmer’.

Ensuring pedagogical quality in media-rich teaching and learning

In the afternoon I followed a session on Resources and approaches for ensuring pedagogical quality in media-rich teaching and learning. Speakers were Klara Bilić Meštrić, Croatian Academic & Research Network, Camila Monge Pizarro, Université Ouverte des Humanités, and Kaat Somers, University Centre Sint-Ignatius Antwerp, Belgium.

In Croatia, although traditional methods of education like PowerPoint slides dominate, there has been a shift towards creating learning communities and action research has been vital. Video is not often used, there is a lack of formal recognition for teaching, and various psychological issues faced by educators. Several support tools, workshops, and webinars were developed. Educators began teaching each other, learning about intellectual property rights, and using AI tools like ChatGPT. The focus shifted from mere knowledge transfer to making students responsible for their learning.

The Université Ouverte des Humanités in France updated us on their digital innovation efforts. They emphasized the use of open educational resources (OERs) and digital libraries, supporting a variety of thematic digital universities. These resources, built into Moodle courses, provide valuable educational content freely accessible to both teachers and students.

The University Centre Sint-Ignatius Antwerp in Belgium discussed their approach to digital empowerment and learning experience design. They use service learning as a pedagogy to promote inclusion and diversity. Their initiatives included a Digital Empowerment Manifesto and a MOOC for higher education teachers and staff. This course, available as a free, open-access resource, has 8 modules. These addresses digital mindfulness and offers tools like the Learning Experience Canvas and a tech personality quiz to help educators integrate technology thoughtfully into their teaching practices.

When do students stop watching a video?

In another session, Matthew Gilooly, of the University of Derby, UK presented his detailed analysis of when students stop watching video, and gave us his own explanations. He went into micro-detail, like a YouTuber trying to reduce drop off rate and retain attention. By analysing specific fragments of when students stopped watching, he found a set of patterns and can use these when improving future educational video. In general, between 20-25 seconds, there is always some attrition. He found that strange and sudden cuts from one scene to another, or certain language usage that indicates you are wrapping up a session, leads to quick drops. It will be interesting to see how these findings translate into the production of better educational videos at scale.

Unlocking the Potential of AI in Higher Education Media Production

In the afternoon, I followed a session with Markus Tischner from FAU in Germany. We shared our favourite AI supported tools for media production and learned a lot from his mind map. It lists the following categories: AI Tool Aggregators, Research/Concept, and Generating and Optimizing Audio, Photos/Graphics, and Video.

Tools and Efficiency: Tools mentioned were Microsoft Copilot to Google’s MakerSuite which help organize, rank, and dive deep into resources like YouTube videos which makes it easier to find and use quality content.

Enhancing Video Creation: Research Rabbit is a research tool that suggests video titles and helps create short educational films. The tool offers text-to-video features and the quality is still evolving. Lumen5 helps educators to compose and edit video scripts, providing a user-friendly way to create compelling stories and teaser videos for educational purposes.

Avatars and Animation: Runway and Synthesia offer AI-generated videos with avatars, though they can appear robotic. For more engaging content HeyGen lets users animate historical figures or artworks, bringing a creative touch to explanations. This tool shows promise as an AI co-creator, offering innovative ways to present information.

Voice and Audio: Eleven Labs stands out in the audio production realm, converting text to speech with natural-sounding AI voices. It supports dubbing and provides various voice styles, making it a game-changer for educators.

Interactive Learning: Polycam and Suno were shown as useful tools to create interactive and musical content. Polycam scans and creates avatars, while Suno transforms text into songs, providing a creative approach to educational content. Suno is currently facing some legal challenges due to copyright issues. Markus demonstrated these tools and it was very impressive to see how quickly a song on a theme could be written with AI, then turned into an actual song.

There are so many amazing AI tools being developed, it is overwhelming. Afterwards I discussed with Markus my idea to provide some kind of structure for us all in navigating through the AI options. This could be a list of ten tasks that you should perform (e.g., text to text, text to video…). Once you’ve completed this, you can post this as evidence and move on to the next ten tasks relevant for your area of expertise. Completing these tasks could be done at your own pace and would provide you with a series of steps to try out tools in your own context.

16th Annual MEDEA Awards

One evening we went to Leuven city hall for the 16^th Annual MEDEA Awards. They recognise and reward excellence in the use of media to support learning and teaching. There were 125 entries from across Europe, the US, Australia, Canada, Singapore, Kazakhstan, and Indonesia. They showcased exceptional examples of MOOCs, podcasts, online games, media literacy interactive videos, virtual reality training resources, and many other innovative multimedia educational tools. There was a very high level of entries this year and you can see more details here.

Congratulations to this year’s MEDEA Award winners

A great network of international experts

The conference was well arranged and had a positive atmosphere throughout. We were welcomed in Leuven and had plenty of time to network and meet sponsors.

How I used AI to support my writing of this report

During each conference session, I typed extensive notes to record what I found interesting, or what caught my eye. I took photos of relevant slides and accessed the conference slides afterwards. I then processed my rough notes through ChatGPT in multiple phases for specific chunks of text with a variety of very detailed prompts. I then edited and rewrote the synthesised text, added my own vocabulary and spin, to ensure my own impression of the session was represented. You can judge for yourself whether it is readable, interesting and relevant.

The AI certainly simplified the task of writing this report. However, it was still a lot of work. I hope that next year I can use the next generation of AI tools to simplify this process further.

Finally

Thank you for reading this far. Comments, suggestions, or corrections, please contact me directly at zac.woolfitt@inholland.nl. 

This article was originally published on Zac Woolfitt‘s blog and is shared with the author’s permission.

Author

Zac Woolfitt, Inholland University of Applied Sciences, The Netehrlands