um so it will have already just helped me introduce myself and i'm gonna talk about uh the contents directly firstly i still like to talk a bit a little bit about myself with you maybe just for a connection and communication if you like and and i had a bachelorette degree in mechanical engineering automation design then during a gap year i did not know what i want to do in the future and also as you might have studied engineering you might know that as a uh as a female when you're in engineering there are just a lot of uh barriers or you just don't know you're just not sure what you're going to do or how you can be successful related to yourself i went to i made the great decision i had to say i went to recruitment consultancy to be able to see a great range of industries and job professions so which suit me best i still had a problem during the stage and after one year i was so lucky to be admitted into the master science engineering curriculum at ucl i'm still like really appreciate all the help and support i have received from professor abel uh jay and professor david guyo for all their kindness offer because i've never tried something so hard to be admitted into a dream program i think it just enlightened me with all the um like inspirations and passion for engineering education and it was also the first time that i felt myself intrinsically motivated about learning something um i do not want to say that it is so much life-changing but um admittedly it had impacted uh my career and my life very much and so following the program after graduation i joined unesco aichi as the program officer for curriculum development and all of the knowledge and skills and competencies i have acquired from this program had not benefited me to go further so i would now like more refer to myself as an academic practitioner just as inspired by able solving problems in education as an engineer now i will begin my presentation so today which is in all three parts first of all is the emerging technologies in higher education and second the implications for engineering education and third empowering teachers for a digital future uh let's come to the first part and i don't know if you have any like general knowledge about ai but thinking about ai higher education we might want to return to the departure point of how it works so ai it is defined as theories and techniques developed to allow computers uh system to perform tasks normally requiring human or biological intelligence but like ai is a concept and integration of technologies is generally like framed down to the three components i have added here artificial intelligence itself machine learning and deep learning so deep learning is a type of machine learning and they are all uh subsets of artificial intelligence machine learning is about computers being able to think and act with less human intervention and deep learning is about computers learning to think using the models based on human brain so it can work it can continue to work and solve problems with less and less ongoing human intervention so technically uh let's say that deep learning can analyze images like videos and unstructured data in ways that machine learning can't easily do and and to just to uh make a little stop that i'm actually not an expert in ai or big data i've not studied related programs systematically but just as many of you and we are the social scientists maybe in future so today we are probing uh all the potential possibilities from a perspective on social science or will we see the professional practice of engineering education so i will continue with what i have explained about ai and so uh we can see now they are generally like two uh uh like trends narrow ai or general ai and there's also thing about the super ai um which is as much as fun as you can imagine uh in only but the the the reality is actually still far from the conception because the conception actually originated in 1950s and you know imagination can always go really wide and not the eight all the ai we use today are narrow ai which means that they are created to solve specific problems for example a chatbot and generally ai just refers to all ai technologies that can be utilized comprehensively in solving any domains with any problems that require these technologies although it has not been fulfilled the advancements are just accelerating so how ai can be transformed and applied in higher education i've listed a few of the examples so first of all the search engines uh for example these have been like using digital libraries libraries it's just striking like learner behavior and intended study fields to help them just target needed resources more effectively and based on that at the intelligent recommendation systems i suppose many of you have experience of studying moocs and now many platforms just offers the intelligent like learning path that suits your needs and capacity and just collects your uh data of your search engines and your behavior and the time you have stayed on specific courses to predict okay that's that's the courses you need and you help you advance your learning in the most efficient way so let's say the recommendation system is where the ai are commonly used and then the self-adaptive uh learning system for the lms um you know i've seen an example that is a squirrel ai institution in china maybe if you're chinese students you might be familiar about it i'm not sure about uh outcomes effects if they are good or bad with any reputation but uh from the practical examples we have set up like in the systems that help like evaluate students especially in examinations about the test of scores and then the system uh the eye technologies will be able uh to capture this data and find out okay that's the deficiencies of your uh to tap to test your learning uh weakness points or deficiencies to help you critically and efficiently improve your test results uh so that's for the lms in the lms is also reciprocal uh it's a capture student's data and uh it just helps the teachers engage with students especially in other ways and integration with vr and ar uh i think that that that requires like very much uh investments into these fields i think many tech companies um they are having some good combinations like ar er and 5g uh to to do this simulation for example engineering education they can simulate a project or a production process in a factory to be like real-time display for engineering students just in classrooms and you just help them just like establish a better understanding cognitively through this combination of technologies uh which is also very intuitive as well and the virtual assistants yeah yeah we are i think we're all very uh familiar with it like the siri or something but it just can be uh simply re-applied in many different contexts and for language translation grammar check we're so familiar with in our everyday uh learning in the grammarly or just as the ppt uh design like functionalities and for facial recognition and image labeling i think um this is one of the concepts of the informing the digital institution but there's yet there are many arguments about it in terms of privacy or whether we should like like insert so much control on students learning behavior and making a class like not not so lively but just like um uh like production mail or something but it's still like um very good uh a lot of innovations based on the ai and what you can do to help us promote a better level of digital transformation um i'm going to talk about the frameworks and analysis of the ai application hierarchy so by this side i would firstly like to show that this is the result of the human emotion image recognition competition one of the most reputable like competition in this field sponsored is sponsored by stanford university princeton google and another company called a9 so we can see that red line stands for the error rate of uh like a trained human uh annotator uh which remained at around like five point one percent across the five years from 2011 to 15 and for that of ai you can see the error rate increasingly went down from 25 to less than five uh four point eight percent in 2015. though that due to study limitations there's no uh specific evidence it's showing that ai can really outperform human being's image recognition at every level but there is just a clear trait that ai develops progressively with significant improvement on decisioning so ai in higher education are there any trends as well um i've quoted this framework it was in a report of the uh ai uh like the uh a report of the logistic report i remember and it it refers to the ai education maturity model and in the first stage we are approaching and understanding these technologies uh it's due in a in a stage of conceptions imaginations and secondly well imagination never stops though and the second nature experimenting and exploring and i suppose uh for my country in china we're pretty much at this stage there are many tech companies and fundings from the government uh from the country from the institutions and they are just investing uh in uh just like digital and ict infrastructure now without thinking and cost uh that was uh that i think the train was uh very wild for some reasons at the current stage especially during the kirby 19 crisis and we are eager desperate to think of okay what would be the future uh would be waiting us in ai how ai and or big data would be uh supportive uh to like uh combat uh the uh current crisis in who knows what's possible in the future so experimenting exploring and there just can be a lot of useful or uh unuseful technologies during this stage and then operational it is then iai will be used for one or more processes across an organization for example chatbox it is mature but for other technologies like the lms it's most of them as you are on the exploration because um it just uh just is a method to do with all the data how you categorize data and uh how you just enhance the uh capacity of the ai to intuitively adapt to your needs and that stu uh requires a lot of work uh how we improve the algorithms and so on so and then in badly i i think i have not like done a lot of research uh about ai applications in this field yes we have not gone before but during this stage it says that uh many of the processes related with ai will be already like um standardized and functionalized or practiced for prior experiences for better improvement and then transformational then the transformational it will be they state that we have comprehensive understanding about what is the digital compass and how these digital technology can just form together as a infrastructure or a basis to support every of the teaching learning staff study activities in interconnected with each other and following that and coming down to the curriculum side um although like i think we should look far into the future but also coming back to what our professional research lies down to the curriculums about uh higher education training for vi so for the uh for this one we can also look for examples as well i would like to share a case study in china as more as i'm more familiar with the context so the program was established uh in 2019 i'm gonna make it a blind kiss um but i hope that the information will be useful for you all so this is one of the most like leading undergraduate ai programs in china and i'm going to talk about it like starting from the admission you might have heard about the chinese college interest examination ccee the time they test chinese students chinese math in english as compulsory courses in arts science at the selectives um i would say it's a life-changing examination for the great majority of chinese students as it can be the long criterion for admission into most chinese universities and so in summary cceee is a selection across the country and is strong connected to students learning and understanding of theories or even their memories and for this program absolutely they recruit the best of the best particularly those showing extraordinary talents in math data science and other kinds of scientific breakthroughs you might find these students usually have successful track records in matter like winning the medals of international olympic math competition or programming context that their genius are half genius as well so that's for the admission part you say the gate is very high i mean for this level of aia programs because we really invest a lot into whatever faculties or curriculum development so it's bad and in terms of the curriculum design it is straightforward design for industrial applications placing itself for international level ai competition at the frontier so for the faculties the courses will be taught by a group of frontline like researcher or industry experts with reputation nationally or internationally and it is interesting to mention that all courses will be lectured in english so have you thought about the question so why english will be the instructional language for many engineering courses obviously or especially those related with the construction of ai algorithms or data sciences that's just because uh i don't know but from my own perspective i suppose that is the strong connection with the linguistics like how the data algorithms are built following what kind of logics they are referring to so i think it is one of the small evidences i found okay they are realizing how language or linguistics as a profession itself is important for ai courses okay and the most significant characteristics of the curriculum are broadly broadly introduced knowledge mastery level foundations and cross-disciplinary supervised and i know it sounds really difficult right but i think that's a another aspect of the education in china you squeeze and squeeze the talents in to see how they whether they can outperform themselves um just again to the end it's a selection based curriculum but um yeah as well it just offers flexibility for you to study which you find yourself as well but they're just um more space and rooms uh for for those who are really interested in use to this study and you who are just the ones for it uh okay so the main objectives are i found there are four focuses that is how to build stronger ai photonics bottlenecks for ai research and technology application such as the eilp self driving and third is a courtship making manufacturer of artificial intelligence technology and then uh and following it is the novel statistical models so there are also a project-based learning embedded in the curriculum uh which are generally based on like introduce the plenary challenges in ei um i have to study uh like however you still might see that this program will receive different from the western uh understandings of the engineering education that is that it is still that place a lot of theoretical learning at a comparative uh high level especially at the start of the learning stage which can be quite different from what accepted in western views i have studied the master of science engineering education at ucl being very impressed at pbl to be implemented at the ever start of the learning stage i think you you all might have heard about how pbr can be used for its best outcomes but it's just different for many curriculums in china so however what i have observed just as i mentioned the cce has a great impact on overall design curriculum design connecting high school students to universal university level uh learning it just cannot be neglected a lot of lots of chinese students are taught about theories in their previous uh learning routes and they are therefore better at understanding series or you can see they the better innovate on theoretical or abstract level it just coheres with the progression of engineering curriculums that engineering uh even top top tier like universities you tend to be more conservative in embracing full pbl intervening early studies just to make sure that engineering students they are not too much self-frustrated facing a huge gap between theory and practice so in another word i think theories might be considered in the same way as the stimulating problems in pbl just to keep students going to make them feel uh i can learn it i can master it everything is in control and with them uh continually increasing expiration to apply this advanced knowledge in future when everything is ready already so i'm going to make any i'm not going to make any argumentation here about which would be a better replay so pbl is also popular here there is a train that more universities adopt this as early as you can they are just aware of the gaps between theory and practice which is how to manage the ppl just seems to be the an adult okay so for this program uh you can see the focus on the the right side uh like many uh fields in first two years they are encouraged to achieve the greatest intensity of advanced knowledge that undergraduate students can usually achieve in four years so they are squeezing it into two years technically and in the last few years the program will encourage students to have more opportunities like cooperating with professors from cross-disciplinary departments and to make meaningful applications of ai and what to mention about is the internship or apprenticeship or professional work experience they will have a chance properly to work in top institutions and they are offered with the full funding 100 funding for international exchange and scholarly and mobilities and quite another way of students intervening isn't it okay so that's for uh this ai program and secondly for better for the big data the definition of big data is that it contains like great variety and arriving like increasing values and with more velocity and this is also referred to the three risks and the big data technologies just can review the insights from data sets that are like diverse complex and from a massive scale and here is a mckinsey global institute report i have just uh just got this information that there are three important elements about big data first one is the techniques just that the a b testings cluster analysis for sourcing and then is the technologies um more related to the context which they can be applied at business intelligence cloud computing databases and maybe digital training as well and then the visualizations such as the charts graphs and other displays of the data it's in three major fields and so data has an application uh just in a variety of industries you might have heard that business executives medical practitioners for example in the curving 19 they use the big data algorithms to predict uh what will happen in the future uh is it is it going to be are we all going to face a higher risk going outside or what is a better decision like for inter national uh like transport travels and also for advertising governments who they readily like meet difficulties with large sets of data in areas including like fintech healthcare analytics graphics information systems and also in some science fields like genomics uh kinectomics in complex like physics simulations like what i mentioned about the digital twin and biology environmental research etc in terms of education so what can big data do especially in higher education well i say it can do a lot of things but i i would especially like to mention that big data does not only serve the students for better needs but also providing like new metrics and analyzing telling us what is good education or the criterions like identifying what are the bad ones so currently there are like common applications use the uh open source big data learning platform for students to practice and conduct data simulations as a virtual or distant laboratories and learning evaluation so um it's like um it can just predict any kind of the failure that is likely to happen before it really happens and just make a meaningful impact on your studies and for your teachers to better supervise you and in the resource allocation curriculum design so it can identify uh the like possible frustrations in the curriculum or administration process for teachers to better collaborate with each other and quality assurance so quality assurance is just like the real time observation or intervention for learning allowing like more flexible teacher interventions and smart administration system i think it is more connected to how digitized the campus has been built up with the technologies so it can just it can then just realize with these functions i would also like to show a few of the um like the examples you can see um that sorry okay i also like to uh show fill up the example so we have mentioned about the real-time observation and administration system i think it will be a good example that is when i visited um a uh like technical school in china and the uh at industry like university industry partnership forum and there was a showcase or you can say a pilot project for the school to implement a full like data big data based analysis system uh to record uh students uh like entrance uh or leave uh for school because it was during a special day of the copied and they need to test that who are the students they are from high risk regions in and when they come into the school and how the university can support them better to send them to medical services or to help them just get into the quarantine process and how they are affecting other students and the value of the students who where they are traveling if they would like to being in their data as well so we just kept help kept the cumbersome state uh i hope it's uh it's a good example and another one i would like to show sorry um real that is the iot one i wonder if you can see the video but this one is actually when big data and the internet of things in education work uh in conjunction okay so uh the the iot like everything about the classroom uh and the like university facilities where they are interconnected with each other and they are able to like produce a lot of unstructured data uh to be recorded into the to be recorded uh into the big data system and uh i think it will be applied for like school administrators they can better see what is happening within the compass and if there are any like fires uh happening so they will be able to help and following that i can share about the frameworks and pathways of applications like what we have traditional rely on the education uh was the theory driven approach to construct a learning capacity and to test if the results are valuable reliable or replicable and that's how we see the world in such methods are deeply rooted with interpretivism critical realism at epistemological level and in terms of learning sciences or psychology we refer to those as behaviorism in constructivism cognitivism and so on so therefore we have the testable hypothesis we keep in mind that we know like experience to continue with the question to prove it and adjust the solutions but in the future uh let's imagine that for big data higher education with various tools of data mining modeling network analysis machine learning it just promotes us to think uh one step ahead how to say the results are connected with the solutions the more transparent way showing the relationships in different factors that we are within controls we can always make changes and improvements to make sure we are on the right track um i would argue that neither is sufficient just don't forget that data can lie as well we need to approach like learning and innovation from both directions to do testable hypotheses on what we know and look for patterns in the data to lead us to think things that we haven't thought of before and that's improving a lot of things like including goal setting objective design time management evaluation so on and following that there's a big data curriculum you can see the numbers of the curriculum big data is generally like more widely accepted than those of ai and for the three major types that data science the types of degrees because big data compared to ai is more like a methodology that can be recontextualizing different like industrial settings so the three main major types of degrees the big data and science is a first one is it's a management exercise degree bachelor of science and second one is a management degree and third one uh it is of the mathematics side so this is a curriculum case in china you can see that the program adopts a combined teaching approach for management theories and practical application of big data similar to that ai you can see still i think it is like a trend or something for many chinese like science or engineering programs the first two years i've pretty much founded on advanced theories especially math physics and just to like just it feels to me like these are the raw materials that can make future uh projects more effective so i'm not going to go through the details of this curriculum but just to mention that you will just develop develop help you develop the breast and depth of knowledge step-by-step based on um just what they have innovated on lecture-based learning is that they made it as panels maybe the traditional lectures are way too uh boring and they have invited like like uh researchers or industry experts uh to introduce uh students what they are what what what is happening every day out of their textbook and comfort zone so they can just um feel like more easily to adapt to theoretical learning maybe at the initial learning stage and so for the for the for all for all the four years throughout the program theoretical learning is placed on a high level and for the last two years we have projects and we have more focus on designing scenarios and they have different types of applications for students choose their favorite interests for example big data management and web development applied statistics logistics operation analysis healthcare fintech and you can just choose the project teams that are designed for you and their supervisor can conduct any kind of like care studies and the uh so uh let's come into the second part implications for uh engineering education but i can't answer this question but it's a big question right but just as a learner i think um it would be valuable if we could just propose some questions to see what kind of changes are related to in the age of ai um the first one would be um so is there like is there any need for ppl to be placed at an advanced level so let's say ai is are put into the process of learning or more human uh ai interactions more factors more distractions more innovation more problems so i think first of all it's there's a need to design the environment more thoughtfully ai can create this functional environment with revenge effects such as technology that hinders students ability to stay on task and we can see a pbl learning cycle proposed by uh cindy and so ai technologies can be quite different from existing ones right from when they can always um respond to us induct our needs so there is a possibility that students learning cycle engineering might be accordingly lengthened by getting to know a broader range of ai technologies that inspire them so it's harder to manage it and secondly just be more critical on problem solving so i i've always wondered uh once we have opening pandora box are we solving the problems or are we creating more problems um so i think we should be more critical and problem solving in problem itself or how to say and the third one i'll just directly move on to the third one as the time is very limited is to enhance afterwards peer revaluation so uh many effect solutions are effective or beneficial on a larger sky but in ppl is a promotion of individually meaningful space variety of solutions i often appreciate appreciated however do we get a chance to talk about the risks we know that potential ai is great um but the risk is that ai is also a double sword it's commonly known uh among many ai engineers that they're just they're just an ethical line we cannot come across no matter how beneficial it can be so is the solution cost effective is it ethical does it have any environmental harms is it designed to contribute to human society or in other words it's a human-centered design i do think that peer review and reflections after the major pbr works deserve more time and consideration and through this we also engage students to be professional language in the new era and i am critical thinking about ethics identity and society as a whole and question two so what's beyond the projects um i think compared with the project what inspires me most is about experience which is very powerful learning because it's not only engaged with the conscious level but also your subconsciousness what is happening around you you might not have time to analyze it but the ai and technologies will influence the way of how you think so we might think about what will happen in the digital science environment what types of knowledge experience will be generated how are they related to big data and ai technologies and how does it contribute to engineering learning innovation and inward ways and here's a framework i use to build like integrating nicole's work the excel model experiential learning model any any a kind of innovation model that is the ici knowledge technology uh technology and the doing and experiment experimenting model so we can see that just a lot of the uh functions between the different factors and ict tools will reshape the overall environment about how these factors are interrelating and impacting each other and following different uh consequences in the question three like what is next for the aim of design um let me just show picture you can see the first one uh is the buildings in the second industrial phase and first and then the next one is the fourth uh stage of the uh department today so i think enough uh is there a need to uh for nature and technology to be integrated especially for engineering students we are now having the new objectives of corp cop26 where we are considering sustainable development but how it can be better embedded into the curriculum and secondly considering a human-centered technology design i think it is important to analyze like more deeply into the social science and structure uh for societies operating as a whole so what is the role of ai how it should be placed um is it is it designed to challenge our capabilities or to support uh our like it's like human uh like technology uh or ai augmented learning and innovation we we really need to think about it and also think about the risk or the the just the gates not to cross a line so what are they it just requires more energy to find out and the third one is the generation of new jobs and before that we're always thinking of design-based learning with designing products but beyond that what's beyond the products uh are we giving enough consideration to the whole ecosystem are we well uh ai mentally it was just a lot of jobs and diminishing but uh if we uh will uh just be more active to look at the uh the other side is how ai uh how human potential can be unleashed uh creating new meaningful jobs on the basis of ai and i think that's also i mean for a few days to explore and coming to the third part and almost i've almost finished my presentation and this part is basically based on my own professional experience empowering teachers for a digital future where we just talk about a lot about the uh futurism perspectives about ai and we barely have a chance to look at how we can really get everything started where we rely on teachers to impart the essential knowledge skills and capacities competencies for students facing the digital future the teacher themselves or teaching as a profession itself has long been undervalued so i'm looking at the digital gap so how far can we how far away from these overarching goals i think it kind of just because i work in international organization it gives me opportunity to oversee a greater landscape how these technologies have have been accepted in different regions where the difficulties they face you know we have some smart classroom projects but in some like african regions or west asia those least developing countries they they want to implement the ict resources but they don't even they don't even sometimes have the electricity of water to support the essential like conditions for they to start digital learning so that's a big challenge and teacher education has a main focus so when we look back to teacher education it may be the most efficient and beneficial rewarding approach as a leading one there are nearly some reasons short of ict equipment teaching resources professional instructional community support here are the works i do with my organization um we have the webinars and online courses and training programs for teachers to enhance the ict and teacher skills and especially the digital literacy about how if i baked it i will have a future in higher education and here are the three main sections obtl that is online blended learning at the front and then for leaders decision makers policy makers they need to discuss uh about uh the agreements about the higher education digital future and then for especially for stem subjects engineering education as well um in also offering some additional resources such as the evaluation tools in however we also like do some research i have been like fully engaged in this project i utilize all the knowledge i have learned from the master science program and i lead this i like this project about to to just deliver to research and deliver the uh higher education the competency framework for the higher education workforces well maybe it's a very good summary of what i've learned throughout the master of science engineering program so you can see the horizontal and okay there are double sides in uh including a lot of learning science and taxonomies like bloom tax only knowledge models and then uh you can see some of the work we do and i would especially like to mention that because today is that engineering uh is about uh higher education in ai or big data engineering i would like to specially mention about and express my thinking thanks to our course leaders and program directors we have organized the ioe global webinar about engineering education at the special series you can see ebola there and jay have delivered the learning and innovation session and to become the continued we will be very lucky to have professor david val and the final session as female in engineering education um engineering education i believe that it is the heart of the digital transformation today so the final part um it would be i think if you are a student trying to apply for the master science program you might be interested in this page because this is what i have chosen for my master of science courses it's not a recommendation just my own experiences and how they have benefited me to go further and apply all the knowledge and skills i have received from this program and to continue my my like work another stage of life in my professional work um okay so finally i would like to quote something from bill gas so most people over uh wrestling made worldly country in a year and underestimate what it can achieve in 10 years i think it could be like similarly applied in engineering education so finally the past and current systems should not limit our imagination of what is good engineering education in age of ai i just look forward to discovering embracing and changing all the possibilities with your in engineering education and in our continued lifelong studies thank you oh thank you olanyan really a lot of time have some difficulty managing the time that's my information i i really really enjoy i think i was looking at we do have some of our students here and some were thinking of the msc tend to be some academics from ucl as well i was really looking at him uh ai how it is advancing of course i do know quite a little bit but i never quite anticipated the amount of change that is currently taking place and that you are actually at the forefront of applying or thinking about how ai can actually be utilized to deliver education my my question is always this one when it comes to ai is there any chance that uh individuals like myself educators might actually be replaced in the students just to engage with the ai system what are your thoughts on that well that's the ultimate question isn't it so at the end of the tracks the running tracks so this side human these are ai so who will win um that's the question we all care about uh especially in education so what would be your answer i think everyone will be aware that and we hope that teachers will not be replaced so why i think um first of all from the technical level we have mentioned in the presentation that ai uh you know its capacity is about like for example image recognition is great and it's like crazily increasing it seems to outperform humans but it's only about yes or no it's about they are making the decisions very fast but for humans i think we also discuss this very meaningful uh problem in um in one of one of our master science courses without humans we also we always have the uncertainties kept in our minds to allow for possibilities and to generate um like um like opportunities that are never likely to happen that all the things just came out to be a surprise but also as human uh we uh innovation um we may not be able to reframe innovation but we will be able to uh like the care and tangential support and individualized learning plans for the students not only from the data or not only looking at data or technological side but from our hearts and to exchange shoes and or to to just draw our own experiences i think yeah ai is good right it can predict the future but you just have to not have the certain experiences to be impressed in a certain way to motivate students inspire their students so i think that is one of the that is those of the great values that the teachers can do in engineering and also i think in the future engineering um it is a technology at first and also now but in the future there is a trend that engineering is more and more related to nature to philosophy to education itself into humanism to ethics and that is the right age for human teachers to be more professionalized to be upgraded and using better ai just as a tool for education to advance learning and teaching and uh learning also a question from uh chanchuan g uh he says as a computer major student student is it a good option to courses you were talking about the case study which which is recruiting the best students for university and then they are studying university courses what i'm going to do is i'm going to allow a chance to to talk so that the question is not quite clear and then we hear from i suppose it's a yeah can you go ahead with your question enabled you to speak yes transgender muted uh just admit asked of me yes um are you able to add muted to talk uh i'm not on neighborhood i'm not uh i i've tried to and mutiny oh she said she uh transgender doesn't have the microphone oh yeah okay um so all right so i think that's asking is a computer major student is it a good option to pay soon i think she might have been talking about the program you were talking about in in china the ai program what do you think about it is it a good program for students to pursue in china okay thank you transgender maybe i i would like to uh i hope to see you more of your elaboration on this problem are you talking about uh the course when you see the courses are you referring to the master science program at ucl or you want to talk about the uh curriculums in iowa big data curriculums in china technical cases just to type it you know yeah yeah just just type it for us please maybe i can like start talking about yeah something related to using our program first if transgender will have further questions you know we will yes or no yeah because uh if we are going to talk about user programming i think a lot of uh the audiences today will be interested in this program in this program well i would say if you are a computer science student or any other engineering subject students if you want to apply for this program you have to consider following uh like questions um first of all like what do you want to achieve uh let's say if you if you're still like passionately interested about technologies um or you want to be a scientist or something in the future it will be a good option but it's not a destination it will help you it will help you just develop more sensitiveness about how you can learn a science a science program engineering or computer science it will also help you broaden your horizons about what is happening in the future and so if you are if you if you were an engineer if you are engineering students you know only graduate studies uh if you attend this course and you will be uh able to learn cat engineering from a social science perspective and even further you'll be able uh you will you will you will gain the capacities of metacognitive skills to plan your learning better and you will know uh you will learn about how to learn engineering i think that is quite important so it's like if you still want to focus on engineering and you want to apply for this program i think it will foster all of your learning capacities as a whole and to help you achieve better in your future program still in the field of engineering but if you like me you're confused about the future engineering or you face like any kind of obstacles in current job market uh or you're just uncertain about your professional development thinking oh my characteristics so personalities not fit into engineering i do not i do not like to deal with the engineering problems if you're like me you can try you can give yourself a chance to uh to try if this program fits your expectations don't set expectations too high but i think if you have interest in psychology especially in psychology learning sciences and you have a care for others um you you will you can because if you can just switch your roles it will be i suppose from my experience it would be easier for you to accept the core uh philosophies and the strategies in uh introduced in in this program such as the ppl because this student's centered and you need to just just have a good foundation yourself to connect your own characteristics your potential because following this program if you want to be a social scientist you might uh hope to develop their potential in social science research so you better like you enjoy reading uh enjoy uh learning about psychology and also uh don't forget to don't forget uh that don't throw away your uh intrinsic passion about technology and if you're a sci-fi lover i think absolutely you will benefit so much from this program and you enjoy it very much and that's my answer thank you for promoting the program but i i still remember the many arguments we used in two years because it was free because yeah and i'm so pleased that um you accepted to become our very first speaker in our very first msc engineering and education program and it's a very uh strong topic because ai uh is currently at the forefront of everything and it's so nice and pleasing that we have one of our own with actually developing strategies championing those strategies and training other engineering educators educators worldwide to master the technologies and out on behalf of uh my colleagues i were teaching on the msc i would also like to thank uh everyone who came today and to remind you again that tomorrow at 12 o'clock we are going to have another one of our students um that's uh summer elsa ed she is still a student she hasn't yet graduated but she is already developing a education uh training curriculum for people in renewable energy industries uh in the i think it's the in the united arab emirates so we would we would like to welcome you again to be with us tomorrow to see how people are actually utilizing their knowledge of engineering education to deal with pressing issues face facing engineering education in very different contexts and hope you have a lovely day thank you everyone we slightly overshot but i think it was well worth it also on that regard i'll bring this show to a close thank you thank you so much thank you bill thank you everyone [Music] i have sent my contact email if you would like to view connections or if you have uh problems that care uh queries um i would like to uh answer that yes um so the the email link is in the chat and if you haven't taken it and you want it um just send me an email and i can give you london's details so on on that note you have a good day and thank you everyone for coming bye bye thank you goodbye have a good day good night
2022-03-01