 We'll hand over to Ximpo, technology partner. Thank you very much. Okay. All right. Okay. Good afternoon, everyone. Thank you very much. Join the, my presentation. So, and you see the title. So this is a title, quite, cover quite a number of things, a cover and a pedagogy cover. Students engagement also cover the assessment feedback as well. So, before my presentation, I just want to check on the sum of you. How many of you frequently use the chart GPT? So can you raise your hand? Great. Thank you very much. So you see the talk basically cover three aspects. And I quickly go through the first parts, the pedagogical parts, and then we look at our experience. I really want to share on the you and with our experience regarding how we catch the students engagement, what kind of measurement we use and use that measurement to measure so-called student engagement. And after that, I really want to use one example from chart GPT, from student experience perspective, how they use chart GPT to complete their coursework, their assignment. Okay. So I think over past years, so high education heavily impacted by various challenges. I think the pandemic is the important part. So and the government policy also is very important. So we can see there are many strikes and we are not happy our current environment. So we try to improve it. Okay. And also the key factors, the training factors come from emerging technologies. So they lead us to change a lot of things, change a lot of things. And also the big block of research work on the digital, for example, digital on pedagogy, people talk about the digital and the curative design, even talk about digital universities. So and these kind of things actually bring a lot of changes to our university, to the teaching learning environment. And now the key question is how we are able to measure the student engagement. So and we have some good indicator to measure student engagement because the student can't go to physical class. Okay. That's the traditional way we measure student engagement. But when we put a lot of things online. So and a lot of students to go to, for example, Blackboard and the virtual learning environment. So they can open the web page and then leave the page open and do something else. And a few hours later, they can come back and continue to do something. So what we can use to measure so-called student engagement. So that's a really challenging topic for us as well. So new challenge here is the generative artificial intelligence and chart GPP. So this is really challenging for us from the assessment perspective, from learning experience perspectives. So last year we organized one workshop. The title just enhanced, technology enhanced learning, learning. So we invited one kind of speaker and from the whole university and new or golden. So and he used, this is quite a nice paragraph to summarize some changes for our delivery model pattern. So for example, in 2018, 2019, we basically use a traditional way to teach students in the university environment. And the 2019, 2020, because we're facing the pandemic issues, problems and we just use the mix and the way to deliver our teaching. Okay, students use the mixer environment to learn under their course. So 2020, 2001 basically we entirely locked down. So we put everything online. So from teaching perspective and from learning perspective, everything online. And then in 2001 and 2022, so some things gradually come back. So I add another two parts. So basically what Lexi is under from the half the pandemic and the life from the previous period and what is the challenges at the moment we are facing. So that's basically, so and we call all of these kinds of things. For example, towards a digital university, that could be the important things we need to think about it. So this is Lexi and because you are some of you so frequently use the chat GPT and before and finish this slide, I also talked with the chat GPT and then get some otherwise. So but of course I bring my own ideas and into this list of the Lexis. So left half the pandemic. So an important part of where it be is the digital transformation. Okay, this is the key words. I'm seeing this morning and our keynote speaker also in the Q&A sessions and talk about the digital transformation. That's the important part. So I don't want to read the whole list of the bullet points and you can see so from the important part for us is so and because we are facing everything online, we have to quickly to learn and adopt the digital technology. I think that's from student perspective or from lecture perspective. We have to do so also. And after that, we need to consider so how we assess the students. Okay, so and how we deliver so and our costs. So all of these kinds things actually remain and also use for us in particular from global and international collaboration collaboration perspective. So I think so legacy after the pandemic. So and this way basically significantly improve, promote international collaboration from education sectors. So change already happened. Okay, so now let me give you and the the review. Okay, so call back the for example, 10 years ago and what we did and all these kinds of things and give us ideas and let her to move forward to see what way we can use for the future student engagement. So 10 years ago, we had one workshop and we invited professor at least from Durham University keynote talk. So and she present the one result. This is basically and she published this result in 2006 and the six years later and she still hold the strong opening side. So correlation between physical class attendance with the academic outcome. So closely correlated each other. So this is the outcome, but we had different openings. So and the sum of participants under these issues. So they said, so with introducing new technology into the education sector. And the physical class attendance and the draft and the significant significantly and also with reason some and the questions regarding the physical class attendance the regulation from different universities and by the way, did not draw the conclusion. Okay, we just leave some suggestions there. We just follow same line and then so this study and the from research perspective. So we try to understand. So under what kind of indicators and the measurement for how it can be used to measure student engagement. So under this one that come from the one on the author. So under the and the cool. So and he published his result. So and he divided the engagement from the behavior perspective and from perspective. There are a lot of works around the behavior and the engagement, but there are few works are talking about the emotion engagement, how we are able to measure emotion engagement and we come from the attitude from presentations. So and we can so and see. So if we use the following attitude as the indicator how we are able to capture the attitude. Okay, so we come up with the our solution user sentiment. So my background is from computer science and particularly on the artificial intelligence and we I did a lot of the machine learning things. So we use a sentiment that can measure the people opening can measure and the the attitude, but we mainly based on the text. So we have a tax collection of the tax document and then we analyze the collection of the tax document we try to discover the attitude openings and from the people expressions. But now so where we get this kind of information. So and also the sentiment analysis actually is very important. The tools for how to understand student engagement the attitude the emotion as well. So and here's some things. So for you that particular from the feedback. Okay, so from the attitude to the cost and the program. So so what do we did and we did what one system you also system called the front system. So this system is able to so for each for example cost work or combination we need to give student feedback meanwhile give mark. So we generate the feedback sheet for each of the students and then we label them we give the name of the file and use their email address. So this system is able to release the feedback to students at the same time at the same time in order to because a system has been with us under 76 years so we collect a large amount of data, large amount of data. So and we in order to carry out this study we could finally we do some first processing we collect the 3000 to 300 feedback student record and specifically we look at the three modules, three modules. So I want to give you an idea. So for example once you have feedback you upload it into the system so under this basically you can release your feedback to students. So each of the students will receive the hyperlink as long as the student click the hyperlink and the they can download the feedback system is able to capture as a timestamp once it's clicked and the we receive the timestamp. So you can see there's a time difference between when we release the feedback to student and when the student collect the feedback. So that is an important part for us. We try to use our sentiment technology to analyze student attitude. So first because we concentrate on three modules and we collect their mark, we collect their attendance and then we project them into two-dimensional representation. We divide this two-dimension representation into four areas so you can see and different area represent different meanings. So for example here and the student field with less attendance under this part basically student attendance so attendance is 6% of class and also they passed the module, they passed the module. So this is the statistical result and we also try the different way to look at the so-called correlation between their physical class attendance and also with their marks. So we couldn't find out the linear correlation between them. This is the polynomial on the relation actually. So after that we have another assessment and we look at the how many days and the past they collected their feedback and also we look at their marks as well. So and we get this and we try to understand the correlation between them and after that we divide them into the file intervals and based on the data of the marker collection and then we think so this part basically within the 10 days is good and from 10 days to 15 no risk and the years here we have mature, neutral and then we have potential risk okay. So we use this one to help us to identify the cohort of students and then use that result to create the so-called early invention or different strategies. This is the first result okay. So second result and I want to show you the chart GPT. So this is mainly from assessment perspectives and what is a student experience, what challenges we are facing. So this is from AI perspective so the interpretation what is the generative AI basically and we can use it to generate different things, generate the contents. So we can use it to generate the source code and the Python code, the Java code we can use it to generate the image tags but the chart GPT only can generate the text. So and it can plug in the third party the functions to generate the image and whatever. So this is some technical features and if we are interested and so you can try to learn about the important part here. So because of when we use the chart GPT this is called the prompts engineering. So how we express our questions if we are able to precisely and express what we are looking for and then we will get a better result and if we are not able to precisely to express what we are looking for so it's difficult to get the precise result. There's a big difference between certain engine and the chart GPT. So for example, when you use the same query input the chart GPT from time to time you can get some little bit difference sometimes the big difference answers but when you use the search engine you always get the same answers. Okay, so that's a bit different. So now we look at the whole and what the GPT can do so and you already familiar with and I just try to go through this one so and we can use for example and we can use the some word Chinese okay express your idea and then we use English to and send the this prompt to the chart GPT ask what does this exactly mean so and then so we can get the answer so this first part is this is the prompt this is the response I received okay and then based on what I received I can ask the chart GPT write an aces write a story for me and with the full example 400 please have write the 400 words story based on the following descriptions and then we get this one meanwhile and we also input we can get the Chinese story as well so why I want to this basically currently so and we have international collaboration education program so we have Chinese students and we have English students so the way basically use the same questions to assess students so and they can basically use the way Chinese way eventually to get the answers in English so this is the one module and this is for postgraduate and this is the standard module so and the level 7 and the Friday is the 20 so we expect okay students so we have contacts the hour six hours and then we want a student to use 140 hours for independent study okay so put it together is 200 so we have two assessment so in past years we have two assessment both fully 100 coursework and also so this is learning auto-com two important part for the learning auto-com one is the module try to divide a student with independent problem solving skills this is one and the second is a critical thinking this is another important aspect so we use the two pieces of work and then we expect a student and for each of them for two coursework they spend about 30, 40 and 50 hours to complete the assessment so now so we release this one so this requirement and what is the student experience I think that perhaps you want to know so in July I invited two students one is enrolled this year and another student enrolled the last year last year so both the students study my module deeper learning so both of them have experience of using chart GPT so and I ask them to help me to complete this assessment this coursework so and both of them tell me they only spend less than two hours to complete we expect a student to spend 40, 50 hours to complete they need to put this amount of time for the effort but eventually we only get the two hours so and they also have opinion they said if let the some students who don't have the appropriate good experience play GP chart GPT they perhaps just and spend a few hours so and when we start to mark their result so what mark I can give them so I can give them 55 until 60 percent so they not only pass the module also they can get the two one they can get the two one so what is the challenge to us so that's the challenge so and the way when we divide the module specification we have two aims so why is the problem-solving skills we try to develop students also we try to develop a critical thinking but when students use the chart GPT so we are not able to achieve that so this is some prompts the students use okay so you can see this is the question to students from students understand the answer generated okay students just directly use the requirement of cost work as the prompt and the input into the chart GPT so then they get the answers so they get the answers okay and also they can ask the chart GPT to generate a code for them so they can play this code with a less effort and make it works as well make it work as well so we see the chart GPT bring opportunities to us okay so from language perspectives from the writing perspectives okay they can help us for example I'm foreign so I use the chart GPT can help me to learn English and also sometimes I struggle to complete something and I use the chart GPT can help me to writing okay that's good and also they can use the chart GPT for example do some preparation cost work examination okay so and also so and that is the what you're doing so and whatever time they want to use and then they can use okay this is an advantage of course there are other advantages as well so there are a lot of challenges and it bring to us so and so for example we are not able to use currently given current situation we are not able to achieve the objectives we previously we designed in module specification develop student independent problem-solving skills and the critical thinking okay so and also it brings the plagiarism and if they don't have appropriate acknowledgement so that's where bring the some of the plagiarism as well so and so for example also promote the laser so students sometimes don't actually proactively to work they just rely on GPT rely on this technology and also there is the concerns related to the ethic issues and because when chart GPT basically collect the data over internet some and copy right already there so if they don't have appropriate acknowledgement so that's a trigger another important part so that is something I want to talk so the come up the summary of my presentation so I said lecture so and the given current the rapidly rapid development advancement of the AI in particular chart GPT so we are facing a lot of problems there's one also we have legacies and from after the pandemic so we some things and the students already get used so they like to use that way to continue their coursework and their study so we need to consider appropriate approach to move away from the traditional teaching style to the current the technology enhanced as a flexible learning environment but can we so I move away and for example the new ways from the for example and the impression examination given current GPT can can do so this presentation thank you very much international students coming into the UK very knowing English and just getting a degree yes I think so I think so yes you just repeat what the question was so it was the question was about the international students getting okay so I think the international student because so of course for international students for joint the program for example and the student they have the language requirement okay they have to pass else the six even if they pass the L6 they still have the big difficulties to complete for example assignment so like this kind of coursework so some of them the heavily use the different tools they use the Google for example try to search answers and also because there are a lot of the open sources available so and for example source code so they can use the Google engine Google and the search source code and then adapt the source code to complete their task okay this one but now so chart GPT not only provide the source code also can provide the English writing I think that is really really challenging for us so which is slides you prefer okay so this is a sentiment analysis and so frankly we did not verify so what actually they are thinking because you see when we have a large number of data is really difficult for her to trace back so and this is basically and really come from data we have so and based on the data we have and based on our understanding based on our research so and this is what we draw so and we just use that way for example regarding the early invention so if a student so for example if a student around this time around one month later they still have not collect their feedback and then we purchase them so and this is around the less than 20% around the 20% students and we purchase them so and definitely so they yes this they express they were whatever reason they did not collect the feedback so and they always see some good words and they will make effort to do their study but never knows difficult