Welcome everyone to our seminar on student experience in a world transformed. As we stand in the year 2034, we find ourselves in an era where our planet has faced significant climatic challenges with global temperatures edging towards a 2.5 degree increase.

In this world, education has undergone a digital revolution marked by the emergence of artificial general intelligence, or AGI. AGI, an advanced form of AI that mimics human cognition, has reshaped how we approach learning and problem solving. 

However, amidst this technological surge, the human element remains central. Our seminar today reaffirms that despite our digital advancements, the human touch is irreplaceable. 

Particularly in regional New South Wales, universities have transformed into digital hubs, embracing AGI and the metaverse, a collective virtual shared space. 

Generation Alpha, the students of today, are digital natives. They were born into a world of rapid tech evolution and environmental awareness. Their educational journey is more than just acquiring knowledge. It's about understanding the interplay of technology and humanity.

They seek education that is responsive, adaptive and empathetic, one that prepares them for a future where technology and human values coexist. 

As we delve into our seminar, we focus on how technology and humanity intertwine to shape student well-being. We explore the role of regional universities as anchors of this human digital nexus, providing expertise, support and a human touch amidst a digital world. 

These institutions are not just centres of learning. They are the custodians of human connection, helping students navigate and creatively harness the power of AGI for their personal and professional growth. 

Join us on this insightful journey as we explore the future of education, a future where technology empowers, but human connection guides and enriches the student experience. 

So that was a deep fake of Mark Evans. And Mark has not seen that before. We purposely asked Mark to do a little video, just saying a few things at the screen. And then we developed a script. 

So he never said those words either. 

Mark, how did the video make you feel? What went through your mind, seeing yourself saying things that you never really said before? 

I guess I felt that, if you have the technical capability, you can develop very convincing fakes. 

Obviously, as part of this process, there was a video taken of me and that included me talking about five minutes. 

And then the fake was developed from that. 

I imagine a lot of people being very convinced by the fake. So here are perils, but possible opportunities there, aren't they?

There are clearly opportunities from that type of technology. But there are ethical perils as well at the same time. 

I guess you could use this technology to ensure that actually you don't have an off day, that there's an upbeat, engaging Mark on an ongoing basis if you got the right performance. 

The big issue for me, is the difference between the face-to-face experience and the online experience, that often you don't have the same breaks that you have in the face to face format. 

The strength would be that you could deliver a high-quality lecture to time, using your avatar, but would you have the same connection and passion with your audience? 

Obviously, you could edit and do a whole range of things. But then there's the broader issue around the ethics of using this type of technology.

If it goes back to the opportunities, I love the idea that, even if people have a fear of public speaking, now you could put your pre-prepared speech and then pop back up in some ways. 

And that's quite interesting because I wasn't even thinking about not having enough days. 

Some of the things that I was considering were things like, you could use digital art or you can use like editing tools or there could be some research opportunities here, but really it's also that piece around - Performance. 

That's the interesting thing about academics, unlike actors, we're not trained at all. We learn through doing. 

I've actually thought we should be trained in that kind of performance. 

But you can see the way in which you can use this technology to develop a really high quality performance.

And for those people who find that more challenging, this provides them the opportunity to do something of real quality. 

There's definitely an opportunity there in the performance nature of teaching. 

We all know how important that is in terms of connecting with our students. 

I'm loving the idea too of the opportunity to be in multiple places at once. 

We could play the video and it looks like you're in the session and maybe not in some ways. 

Let's go then to the risks. There are some ethical risks, but what else do you see? 

What risks do you think universities could face with deep fake technology? –

Well, obviously there's the authenticity piece. And if they start to question the authenticity of what they're seeing, then they may start to question the authenticity of the knowledge that you're presenting. 

In an era where truth decay is becoming a real problem and we're seeing the polarisation of ideas, deep fakes can add to that polarization and that questioning of the authenticity of knowledge. 

And I think for universities, one of the fundamental roles of universities in the contemporary world, it is to debunk myths, it is to challenge fake news, it is to make sure that our knowledge is as credible and as valid and as evidence-based as possible. 

And a lot of that is driven by trust and perceptions of universities being the guardians of trust in the world. Being the guardians of trust in knowledge. 

There's peril there.

I was reading an article actually the other day that talked from the World Economic Forum, looked at global risks and they say that one of the most severe short-term risks in the world is digital deception or deep fakes, because they're becoming so realistic. 

And that creates a culture of deception or the perception that everything and everybody could be deceiving you, that creates kind of a sense of paranoia and fear, doesn't it, potentially? 

Ghana, our executive director, thought it was not very realistic at all. And Matt had some pessimism there too, knowing you and seeing you present more than I had, but I was really shocked at how realistic it was. 

Can we do a poll to ask people in the audience how convinced were you by the deep fake? 

The polls are up. Most people have said six, 35% have said eight. 

I'm going to say like over 50% plus the 35%. I'm going to say that's more than half of us are actually believed the deep fake, right? 

We watched it. We maybe had some level of uncertainty there, but it looked quite good. 

And I think because we've been on places like Zoom over the last few years, the digital disruption that we can sometimes get leads us to believe something that's a little bit more blurred. 

Mark, maybe I'll just quickly throw it back to you and say, how does that make you feel knowing most people believed it or accepted it to some level?

Well, obviously you don't need to convince everybody either, do you, to mobilise bias against a particular set of ideas, you don't need to convince everybody. 

It just shows you how easy it is to mobilise bias.

You can see the way in which certain countries can use bots to interfere in elections. And then you've got snowballing effects as well, because you've got the snowballing effects of the mobilisation of bias.

At the same time, there are huge opportunities if we're able to manage these processes in an ethical way.

I see this as the whispers game where you can set up something and as long as a few people believe it, then the rumours spread. I know in the US with the election coming up, there's already been deep fake phone calls convincing people not to vote. 

In a university setting, you can have these pieces at the leadership level, but also at the student level and how that might catalyse change. 

Trump made the observation that if you say something with sufficient frequency, people will start to believe it, even if it's not true.

Look, that's all we have time for today for the deep fake section. But if anyone is interested, we can send the platform across to you as well.

For the next 40 minutes, we're going to hear from two experts in the field about how the student experience will or may change and the evolving landscape of how this relates to things like student curriculums. 

Are we actually building curriculums that are future fit and also assessments? 

How do we harness technology to fit into our assessment process or adapt the assessment process to technology, or do we just kind of push away?

We have two presenters today. Each presenter will take five minutes to share their insights. And then there'll be a fireside chat where we'll really encourage you as the audience to ask the questions that you have. 

Our first guest, Professor Simeon Simov, who is a professor of information technology at Western Sydney University. He's known for his research and educational leadership across artificial intelligence, data science and intelligent virtual reality. 

I'll just introduce Dr. Mike Perkins is the head of the Centre of Research and Innovation and a senior lecturer at the School of Business at the British University of Vietnam. 

Let's start with Simeon. Would you share where you feel the student experience will lead us with the technologies? 

Thanks Juliette. 

First of all, I'm starting to get very much worried about this deep fake expertise on the other side of the Blue Mountains, so we may have much more work to do in order to detect such things. 

But it was a great synthesis from Mark Evans.

And I would say that one thing from AI perspective that was easier to detect, was the reference to artificial general intelligence, which I think was made on purpose. 

And I would say that this is extremely important to be able actually to filter and create curriculum that has embedded mechanisms for guaranteeing what is in that curriculum and what the AI assisted pedagogy is using is very valid. 

In this sense, years ago, we had ARC funded earlier work on believability, which now emerges as a key issue, an important issue in any technology mediated curriculum. 

But I would like to focus on three specific aspects related to curriculum. 

First of all, the enormous ability for personalised learning. We had another ARC application at the time, which was called the Cambridge Tutor.

And that application was looking at analysing student learning styles, trends, looking for gaps in existing knowledge through developing a personalised AI system.

This was roughly 10 years ago. And it was far away from today's sort of capabilities. But the whole idea nowadays is pretty much implementable. And I would like to put two specific features of generative AI that makes it implementable. 

First that it interacts now in natural language. So that was much bigger difficulty at the time. 

This step now opens a completely new world for curriculum innovation. 

And the other is that it can extract knowledge and extract things directly from text, images, diagrams, and a variety of media in digitised form. 

That opens bold opportunities, but also opens some red flags. 

Another thing that's worth discussing, is that this personalised curriculum may require much smaller granularity in terms of how we constitute the structure of the curriculum. 

At Western Sydney, we did some interesting work on relating curriculum via a few AI technologies with descriptions of professional requirements, job descriptions, and professional requirements, using Sphere Framework, the skills framework for information age, which is focused on ICT and on computing area, but it also is applicable in several other areas, including business. 

That made a system that interacts with the student in terms of career aspirations. 

I want to be a software engineer, and then it composes a personalised program where there are some complete subjects, but there are some subjects that are composed from smaller modules that are guided by Sphere. 

This is still in experimental stage, but it just demonstrates, and this can be changed during the education itself, during the study itself. 

I see that my time on personalised learning is coming to a rapid end.

I would also mention just another thing, immersive learning. 

I know that today in the program there is a visit to a learning space in Metaverse. And in immersive learning, there are too many ways to interact with immersive spaces. 

They can be augmented spaces, they can be solely virtual spaces in Metaverse, and so

on. And they can be populated by bots. We had an indigenous knowledge virtual world a few years ago developed for Parramatta, how the Parramatta campus was before the arrival of the first fleet, for students to explore the environment and to interact with indigenous people in that environment. 

And the third one is the evolving curriculum.

Looking at what's happening outside in the world, in industry, in the development of society that AI can assist really on the directions of evolving curriculum for a specific university, looking at the positioning of that university in those disciplines. 

That was fascinating.

But I'll just quickly summarise and we'll go back to the conversation. On the weekend, my niece went into a hologram room and she was learning about sea life with it surrounding her and myself, amazing and terrifying as well. 

I love the example of being able to capture indigenous knowledge.

Thank you for that. Let's pass it to Mike. 

Mike, would you speak about the future of emerging technology and assessment, but also the student experience in general?

Thank you very much, Juliet. 

Simeon talked about how the curriculum is going to have to change because of generative AI. 

And I'd like to just draw your mind back just two days to a couple of news articles that came out exploring how these new technologies are actually being used by students. 

And what we've seen is in Australia, several Sydney universities surveyed and said hundreds of students using chat GPT to cheat on their assignments. And what does that tell us? 

Well, that tells us that, first of all, students are very keen to adapt to new technology to enhance their learning experiences. 

Secondly, it tells us if universities are still saying that this is cheating, the universities are well behind the curve of what the students are already thinking. 

Now, these articles that I've been reading talk about how the universities use some detection software, and any academics who've joined us today, and many professional staff will probably be aware of Turnitin.

And there's quite a lot of trust in this software for identifying plagiarism.

Turnitin had an AI text detection tool, which they released as part of their software package for free. And they said, "Okay. This is now active on your turnitin accounts. You can now tell whether or not students are cheating using AI." 

But there's a problem with AI text detection as a general technology. And that's AI text detectors exist, but they don't work. 

Now, a big caveat to that. Sometimes AI text detectors as part of an overall package to identify lapses in academic integrity can work, but this assumes generally that students are idiots, and that they do not know how to use any of the software. 

When we say they don't work, we say they don't work accurately, reliably, or really when faced with any methods that students might use to try and hide where this text really came from. 

It assumes that students are taking the raw output from chat GPT and just putting that into their essay and saying, "There's my entire essay." But most students don't use it that way. 

Studies that I've explored looked at several different pieces of software. We saw that with Turnitin, AI detect was only 50% accurate across both Bard, Claude, and GPT for generated content. 

That was when there was no manipulation of the content, just the raw content. It was only 50% accurate across our range of samples. And when we started to do some other testing, we saw this accuracy levels drop even further when we start to use smaller samples. 

Things that you might expect to see for responses to online assessments where we say students interact with each other on a forum. 

And we saw that there was actually only 39.5% accuracy for this unmanipulated content. And when the text was manipulated in some way, this ended up dropping all the way down to only 22%. 

This tells us that there are some major concerns about trying to say to students, "We are going to do what we've done forever in that we're going to do the same assignments that we've been setting students for years and years. And you're the ones who have to adapt by not using these technologies. Because if you use these new technologies, we're going to stop you or we're going to find you." 

And the research is showing that this is just not the case. 

If that's not the case, what's the future of the student experience when it comes to the use of AI tools? 

Well, I think these really need to be integrated more closely into the curriculum and more closely into assessment strategies themselves. 

Something that I've been doing some work on with several authors is what we call the AI assessment scale. 

If you can't detect text that's been created by AI tools, what we've got to be able to do is say, "Look, this is how we want you to use this technology in an appropriate and in an ethical way."

And this is the method that we've come up with to explore this. 

This is a five-level approach, to saying to students, "Look, in this assignment, in this case, this is how I expect you to use these AI tools." 

Starting at the level where a lot of universities are thinking at now is no AI. 

And some of you may think, "Oh, well, that's okay. I can just say to students, no AI at all and that's fine." 

But unless this is in an invigilated condition, maybe it's a live presentation, a live demonstration, an invigilated exam, this level is not really suitable for anything where we send students away to do something. This is only really suitable for assessed, invigilated or in-person assessments. 

The next level is when we go on to, "Okay, you can use AI to present some ideas or to get some ideas or to help with structuring your work, but you can't use the existing content." 

We might use this in cases where we're trying to assess directly students' use of language. 

In English language teaching, this would be one use case for it. But again, how are we going to tell from other students who we expect to have a certain level of proficiency of English? 

We're not really able to tell that with any degree of certainty. For us the minimum level that we actually set students and the way we set assessments is this AI-assisted editing. 

We say, "You know what? What we're looking for is your ideas." As long as you use your ideas, we don't mind if you use your ideas expressed in a different way to help you get those points across.

And that's at the level three where we say, "Okay, you go and you submit your assessed work and that can be including AI-generated tools and include that content." But what it can't do is just not be your ideas at all. 

We ask students to produce their own work as an appendix. Again, this is the very minimum level. But what we're really pushing students towards is more of a complete integration of AI into assessments.

And for me, that's where I really think that we need to be pushing for the future of education in AI, the student experience being a deeper integration of these technologies into both their learning experience and their assessments by saying, "Hey, here's these tools. Use these tools how you like, and we trust that you're going to use these in an appropriate way." 

It's hard for universities to do. It's hard for individual faculty members to do. It's often hard for some students to do. But I really think that this is the only way that we're going to start to get ahead of this idea that students use these technologies to cheat because cheating is what we say it is.

And I'll stop that there. 

Thank you for that. That was super interesting.

First of all, your statement, but how do we even define cheating?

Even technology can't detect cheating in some ways or use of AI tools. 

When I went to university, we used to go into the exam hall. 

And then you had to be careful that people weren't looking over each other's backs, as opposed to now, most of our assessments are online. 

And so we have to adapt the curriculum. And most people I know have used chat GPT or some level of AI because it is useful.

So, Luke, let me ask you a few questions.

Do you think we should accept technology in some ways? 

But I think we've come to say there are obviously risks, but uses. 

When I was thinking about this AI assessment tool, one of the things that you had to consider was also level of privilege or children's socioeconomic background. 

And could you give an example of what we need to consider with technology around that piece? 

Thanks, Julia.

I think that the digital divide is a really critical element that we've got to consider when we're using new technologies, especially at this tipping point, when we're moving ever towards more technology being integrated. 

A lot of positive spin says AI is going to be this great leveller. 

And it allows students who are non-native speakers of English to express their ideas in a clearer way. And that's certainly possible. 

However, if universities don't accept that these technologies can be used in an assessment situation, what you end up with is students who don't have access to the latest and greatest LLMs and the foundation models like GPT-4, Cloud 3, Gemini Advanced, and they may be using free and open-source versions, which are potentially more detectable than other software tools. 

You then get a set of students all using AI tools, but only the ones who are disadvantaged and can't afford to pay $20 a month to buy the more advanced tools are actually the ones getting caught, whereas everybody else gets off scot-free. 

I think that's probably one of the biggest problems that we've got to try and adapt to.

Thank you. 

And Simeon, can I ask you about inclusivity from a staff perspective and detection as well? 

Yeah, but first of all, I want to add to what Mark said, to the Australian Framework for Generative Artificial Intelligence in schools that was accepted, that was basically published by the Department of Education at the end of January, has fairness as one of the principles.

And the importance of what you're saying about accessibility and inclusivity at all levels, including a cultural and intellectual perspective. 

From a staff perspective, what I have observed, is there was immediate shift in changing assessment scenarios and learning scenarios, so they make an attempt to benefit from what is offered by these models.

These models can offer a larger variety of options and opinions. For example, there is an exploration of opinions of an idea, they can speculate from different perspectives. 

And that may develop the ability for critical thinking. 

Again, I'm an optimist, I'm a little bit biased, and because of that, I look at the way that this critical thinking can be developed and facilitated by AI.

But there is a big community with valid arguments that may lead to the opposite effect. 

Well, I was also thinking about staff perspectives about the use of or detecting AI. 

Some staff detected students who had used AI on their assessments and therefore were counted as an academic misconduct. 

But then the students had fortunately, so maybe this is something too that we need to tell the students to take notes and to capture their work, had fortunately had detailed notes or journal entries about what they had been doing across the board to refute back.

Yeah, that came from a real case.

But what you mentioned, reminded me my early days at the University of Sydney, when we were in the Faculty of Architecture, in the courses on design computing, one of the subjects involved developing a reflective journal in order to capture the emergence of the design ideas and the sort of the evolution of design ideas through what students were doing. 

So how do we think the curriculum will change? 

How can we use generative AI to teach critical thinking?

Let's start with thinking about that. How do we think education and teaching around the curriculum will change?

Mike, maybe I'll throw it to you for to start. 

Oh, thank you. In answer to the question, how can you use Gen AI to teach critical thinking? 

One option is you start to integrate this into assessments and in the classroom, and you open this opportunity up to students. 

You say that this isn't cheating. You can use it. And what we want you to do is to be critical about the output of these tools. 

A lot of students are faced with what's called the illusion of finality when they use something like chat GPT, they put in a prompt, they say, answer this essay question for me. 

And then what comes out, they say, I couldn't possibly ever do this myself. This is it. This is the answer.

Because it looks so nice and neat and tidy, but we recognise that when we're drafting pieces of work, draft doesn't just appear in your bullet points or notes, it can appear like a fully written manuscript. 

And that's still a draft that can actually then be adjusted. 

By asking students, what is missing in the AI text? Or what are the potential biases in there?

There are several different ways which we can explore this using both the text generation tools, and also things like the image generation tools, asking students to create images and then saying, well, what does this say about how these models were trained when you ask for a family setting? 

And what does it give us a family setting? 

There are a few different ways of being critical about that. And that is a growing body of AI research at the moment, saying, we need to be careful and not just say AI is great, let's use it for everything. 

But what about the fact that it's not fully reflective of an original idea?

There are people who are now suggesting that we're getting to that point where some of the AI tools, especially Claude three and the Opus model, there are more ghosts in the machine. 

When you start chatting to it, you can start to think that actually, there are these original ideas. But we have to remember, this is just the size of the model, growing and growing and growing to encompass more of a body of human knowledge. 

What is original thinking? Is any thought actually original anyway? 

If we say something, are we saying that we are just parrots to what we've heard and read? 

Are we actually thinking ourselves anyway? 

I often think about this when I first use chat GPT, humans are so much the same, so the fact that this looks what I would write, I find really interesting. 

I think it's a good question.

If we can go to the next question. 

What is the panel's view on the effect of dependence on generative AI technologies on students critical thinking, or so are we over relying on technology?

There are specific strategies for retraining a model and using it in a specific subject. 

And then developing the skills of prompt engineering, it's labelled as prompt engineering, but basically the strategy of how and what to interact. 

Basically, there is a learning from the human side of how to interact with the model in order to develop the thinking. 

Currently, the strategy is to keep the human finger on the selection, and decision making where it matters to be done by humans.

I know that there are schools teaching language coding as a language model.

It’s up to us, to ensure that we educate students in a way that they get a basic understanding of the models that are behind AI. 

They don't need to become computer scientists, but they have a basic understanding of the principles of the probabilistic nature of the plausibility of the conclusions or responses that these models provide. 

This is an extremely important skill. So computational thinking and now AI understanding should be included across the whole curriculum, not the computing curriculum as STEM, but across the whole curriculum. 

If I could just ask you one last really quick question each. 

If you had a magic wand for the universities, to advise them on how to approach the assessment and university experience, what would that be? 

So, Mike, if we go with you first, and then Simeon again. 

Thanks, Julia. 

A magic wand is always going to be difficult, because universities take a long time to adapt to new technologies. 

And it's only now that we're starting to see universities saying, Oh, maybe we need to do something about this. And we're now talking 18 months after this really came about. 

A magic wand would be being able to push things quickly, more quickly, through university panels, senates to adapt for new policies for these new technologies, having people recognise that these technologies need to be embedded into curriculum and into assessment as well. 

Innovations exist and people go, that sounds really interesting. I'm sure there's some people who say, oh, that AI assessment scale sounds great. But it's never going to get through all the different committees. 

The magic wand that I would bring in and say, look, we need to adapt to these new technologies more quickly. 

Right. Thank you for that. Okay. And Simeon?

In order to push things through quicker, we probably need to have that university-wide discussion and commitment to moving forward at pace because technology is moving at a much faster pace than what universities are.

We are now going to move into an immersive digital experience where there may be more questions that come up. 

Now I'm sharing a metaverse world that we can have for Charles Sturt University. In a short time, I will share a link with everybody, and you'll each get the opportunity to come in and use and walk around and experience the metaverse world. 

But I did want to just give some basic instructions, just to try and make it as easy and positive experience for everybody as we can. 

When you come into the metaverse world, it will give you a prompt to add your name and then enter the world and you will appear within the space. And in the first instance, you will look like a robot.

So, it will essentially just be a bot-like character that will be standing in this world. For new directions, you simply use your directional keys. So, forwards or upwards on your directional key makes you go forwards and down makes you go backwards. 

Your two side keys make you turn around so you can spin one way or the other. Within this world, we have a couple of key areas. In front of me now, you could be able to see the amphitheatre, which is behind a large Charles Sturt sign. 

This is where you will start your metaverse experience. And in that space, there is a video from our executive director, around the use of technology within the classroom. 

So, in the first instance, I would love you to get comfortable to watch that video. And then following watching that video, start to explore by moving around using your avatar. To move around, as I mentioned, use your keys. 

We have over here a survey room. I would love you to actually go in and interact with the surveys. Simply, if you walk into the room, you will see these white dots. By clicking on the white dots, it gives you the question to be able to answer. 

Another feature as well is just a zoom. So, the zoom is controlled by the scroll on your mouse. Or if you have a touchpad, the scroll on your touchpad. By zooming in, you come right into the back of the avatar. 

Zooming out, you can see more simply. So, in some instances, you might actually find if you're zoomed out and you come into a world, you can see the wall gets in the road. By zooming in, you will then remove that risk. 

By zooming out, again, you won't be able to see yourself. So, that's just a tip for if you can't see where you're going.

What I'll do now is I will each give you the link.

The link will be coming up into the chat area. And if everybody can start to move over to this Metaverse world, that would be fantastic.

Welcome to the future of education with the lines between the physical and the digital world's blur creating unparalleled learning experiences. 

My name is Ganna Pogrebna, I'm a director of AI in Cyber Futures Institute and today we will look at some of the most exciting technologies that help us revolutionise classrooms.

In the age of AI, lecturers no longer lead human teams, they lead human machine teams.

Machines are in every classroom at the moment. We have tools like CEDGPT, Bing, Microsoft Copilot, Dali and others helping us and sometimes hurting us in the classroom.

It is very important to incorporate tasks that would allow us to use GPT-type products or generative AI products in learning experiences. 

Students will use those technologies anyway and banning them simply will not get us anywhere.

It is very important to have assignments that would incorporate bits and pieces of different technologies like for example Microsoft Copilot, that allows us not only to ask questions to the technology but also gain valuable references that would teach students how to incorporate reference work and do literature reviews. 

Another type of technologies that we currently have in classrooms is coding aids.

It's very difficult to learn coding, we've all been there or some of us have been there and when we try to teach students about machine learning models or convolutional neural networks it's incredibly difficult to explain how they work, how they learn.

Now we have tools like Teachable Machines from Google where you can have immersive experience with machine learning models without the necessity of coding. 

You can have coding experience without actually coding.

Isn't that great? Flashcards. I personally love flashcards. Flashcards help us remember things, learn things and revise.

And now we have tools like QuizLab that allow us to quickly generate online flashcards that are very interactive and are helping many students learn materials seamlessly.

Tools that help us read PDFs. 

Very often we have to read very lengthy PDFs and extract information. Tools like Chat PDF and there are many, many GPTs at the moment that allow us to read PDFs and extract information. 

Those tools are very useful in the classroom.

Learning tools like Socratic where you can devise your own quizzes, you can ask academic questions, you can find relevant YouTube videos to explain a particular concept are very useful as well. 

We can learn foreign languages with online technology and digital technology.

For example, apps like Duolingo allow you to learn various languages in a matter of several lessons. Isn't that fantastic? 

Gamification is a big part of every lecturer's job. I personally use Kahoot that allows me to create interactive quizzes and I always like to have these quizzes both at the beginning and at the end of the class to check what my students knew at the beginning of the class and what they actually learned at the end of it.

Robotics tools. Well, robotics tools are extremely powerful. 

From good old programmable Lego solutions to B-boats to other boards to robotic docks that we use in the institute.

All these tools are incredibly interactive and allow your students to quickly see what they can do with physical world, not only with the digital world.

Dot and dash robots allow us to have very interactive experiences and learn seamlessly both programming tools and understand the line between the physical and digital environments inside and outside the lab. 

Augmented reality tools, virtual reality tools and the metaverse are really powerful in the classroom. Everyone can design beautiful avatars and have really interactive experiences in interactive and digital classrooms.

This is a really fantastic experience for any students. For example, in tools like Engage and Mozilla Hubs we can recreate classrooms digitally and each student can have very personalised experience that they really want to have.

We also can design digital labs, immersive labs that have seamless experience with science.

For example, the tools like Labstar allow us to completely recreate a science lab and have science lessons in there in complex scientific environments explaining very complicated scientific concepts without actually being in the physical lab. 

At universities we are currently educating people who will be retiring in 50 years-time. And we have all these fantastic tools that could help us.

But new technology in the classroom can be both friend or foe.

And it's very important to talk to your students about the potential ventures of technology

to talk about the environmental impact that it could have. The fusion of AI robotics and metaversing education is not just about adopting new tools, it's about reimagining learning journey, making it more inclusive, interactive and impactful for everyone. 

If you want to learn about new technologies that I talked about in this video and possibly more, check out our media blog at the Cyber Futures Institute.