WEI Xuefeng & ZHANG Yonghe
This interview has been published in Open Education Rearch,18(1):4-8.
To cite this article:
WEI Xuefeng & ZHANG Yonghe（2012）. Transition from e-learning to u-learning[J]. Open Education Rearch,18(1):4-8.
Dr. Kinshuk is NSERC/iCORE/Xerox/Markin Industrial Research Chair for Adaptivity and Personalization in Informatics, Associate Dean of Faculty of Science and Technology, and Full Professor in the School of Computing and Information Systems at Athabasca University, Canada.
He has a PhD from De Montfort University, United Kingdom. His work has been dedicated to advancing research on the innovative paradigms, architectures and implementations of learning systems for individualized and adaptive learning in increasingly global environments. Areas of his research interests include learning technologies, mobile, ubiquitous and location aware learning systems, cognitive profiling and interactive technologies. With more than 300 research publications in refereed journals, international refereed conferences and book chapters, he is frequently invited as keynote or principal speaker in international conferences (22 in past 5 years) and visiting professor around the world (16 in the past five years in China, Finland, Germany, Italy, Japan, Taiwan and Ukraine). He was awarded the prestigious fellowship of Japan Society for the Promotion of Science in 2008. He has also been invited as guest editor of 12 special issues of international journals in the past five years, and continues to serve on a large number of editorial boards of prestigious journals and programme committees of international conferences.
He has also served on review panels for grants for the governmental funding agencies of various countries, including the European Commission, Austria, Canada, Hong Kong, Italy, the Netherlands, Qatar, Taiwan and the United States. He also has a successful record of procuring external funding over 11 million Canadian dollars as principal and co-principal investigator.
In his on-going sustained professional activities, he has initiated professional movements at international and national levels. At the international level, He is Founding Chair of IEEE Technical Committee on Learning Technologies, and Founding Editor of the Educational Technology & Society Journal (SSCI indexed with Impact Factor of 1.067 according to Thomson Scientific 2009 Journal Citations Report). At the national level, he is Founding Chair of the New Zealand Chapter of ACM SIG on Computer-Human Interaction, and Past President of the Distance Education Association of New Zealand.
Interviewer: Your report is titled “Transition from e-learning to u-learning: innovations and personalization issues”What is U-learning? And what are the differences between e-learning and u-learning?
Prof.:E-learning is something that nowadays almost every university is doing, which is basically about accessing content and providing certain interaction through internet. E-learning is something that does not have any requirement for knowing what student is doing and also has nothing to do with student’s current situation. E-learning means that every student accesses the same content regardless of where they are, when and what they are accessing and so on.
U-learning actually takes advantage of learner’s context and learner’s situation. It also takes advantage of the real objects that are available near the learner that can be used to provide learning. And therefore it matters where the user is.
U-learning provides learning everywhere.
But it provides learning by checking what can be provided that student can effectively use from his or her own environment. So if the student is in a certain location and certain situation, U-learning would take into consideration that location, that situation and will check how the learning could be provided the best. So the same learner in different location will get different kind of material, different kind of interaction, different kind of learning experiences, depending on where he/she is and in what situation he/she is.
Interviewer:Why this transition didn’t hanppen before?
Prof.:The thing is we have to start from somewhere. We start from something simple. Technology is also advancing. Technology has had a very strong growth in last few years particularly in mobility aspect. For example, ten years ago, not many people had cellphones, but now everybody has it.
Another thing to consider is that E-learning simply requires computers and the internet. However U-learning requires a lot of information about the learners and learners’ environment, which means we have to have sensors and integration of information from different sources which requires both technological infrastructure and software solutions. You need appropriate mechanism to mine a lot of information which is something that was not possible before. Technology has developed very fast in recent years, the kind of technology that can actually access information, things like radio frequency identification tags or RFID (一种传感器技术), reliable triangulation of location through intensity comparison of several network base station data, and Wi-Fi. Technologies now a days can also provide pictorial detection of information, for example, through image processing. Even if you want to check QR code (二维码) you do need to process that image. And those kinds of things (technologies) have come up more recently, so that is the reason why we started with E-learning, then we went for M-learning, and now we are going to U-learning.
Interviewer:What do you mean by “Technology enhanced knowledge research”?
Prof.: Knowledge management has been a topic of research for a long time.However, now because of technology, we have lots of information coming up. We have more information than we can handle, which is happening everywhere. For example, we receive far more e-mails everyday now than any time before.
Our expectations have also gone much higher. We want real-time information. Before e-mails, we used to write letters. It would typically take two weeks for a letter to arrive to someone, another week to write a response, and another two weeks for return post. Now we write to somebody an e-mail at 9 o’clock at night, and before we go to bed, we check email just in case the person may have replied. Our expectations have changed and we expect fast answers. Similarly we want very up-to-date, real-time information in news, in social affairs, and also in learning. And therefore how do we mine, how do we make sense of all that information? Technology can help us in that. Actually, technology enables us to get all the information and to make sense of it.
Interviewer:So technology can help in the transformation from information to knowledge
Prof.:Yes, technology can make lot more information and data converted into knowledge much faster than ever before.
Interviewer:Why do you divide this research into three sections in your report?
Prof.:This is particularly about what kind of research we are doing and what areas we have. Technology Enhanced Knowledge research involves many areas. The main reason why our research group started with these three aspects is that we have experts in these three areas. We started the three areas about two years or two and a half years ago. At that time we found what we can start with, and created three major clusters. But now things have changed a lot. We have more expertise. For example, we have recently started major focus on learning analytics research in our university. We are also focusing on semantic technologies, design based research and open educational resources.The increased amount of information makes knowledge management more difficult.Technology enables us to make sense of a lot of information. So we need technology to enhance knowledge research.
Interviewer: What is Immersive learning? How to support Immersive learning?
Prof.:When we generally learn using books, or talking to somebody what we are learning or have learned, we are not involved in the environment because we are not experiencing it. Now think about it, when you are doing an experiment physically, you are involved in it. How do we create such an environment which can replicate the real one? Because when we are learning we are not in a company, not in a lab, unless we actually use those processes, our learning will be superficial. How can we provide more realistic learning without having to, for example, disturb the production process in a company? Students are not experts and they make mistakes during learning. Therefore we cannot ask students to go to work in companies and learn there. Immersive learning environments allow students to experience more or less the real environments, and still provide possibilities to make mistakes, to do things many times without paying too much cost and allow more or less real experience. Those environments can be used for many times just like a toy, but of course, for learning. Immersive learning does not provide the environments which are exactly same as what is in the textbooks. It focuses on what happens in real life and provides more realistic environments with joy, pleasure, frustration, problem-solving and so on. If used properly, immersive environments can be very effective.
No doubt that we can’t have exactly the same environment as what is in real company. But we start from real life. We are better than books and dialogues although we are not as good as real life. However technology is developing and now we have 3D monitors coming. With 3D we can actually provide 3D effect, which can be applied in classroom or outside classroom. Many companies are fighting to promote the most advancing technologies. This kind of competition is good for us. By the end of this year, many other technologies are expected to be released. For example, you will see in another couple of years that we do not have to wear glasses with 3D televisions and 3D screens.
Our research contribution in this area is not about technology, but also the framework that goes behind it. When you are dealing with complex systems, you need to have lots of different inputs, processes, and outputs decisions going at the same time; you have to negotiate many other aspects because you have to work in group. How do you manage all this? How do you understand all this? For that we are using multi-agent system approach. Different agent think all different thing, they represent different users and different system, and work together. And that is a strong component to provide adaptive learning in immersive environments.
Interviewer: What do you think of Overall Research direction of “Technology enhanced knowledge research”?
Prof.: The overall research direction is making learning more effective and more meaningful for more people. How do you do it？Not everyone can learn every time, particularly if they have other commitments, such as work. People nowadays have to change their skills very fast according to the development of the society. We have jobs now which were not even heard ten years ago. So if you don’t know what kind of jobs will come up in ten years, how do you teach students now? Because you are preparing for something you don’t even know. What technology does is to provide as effective learning experience as possible of whatever is coming up. So the more technology is advancing the more possible it is to get you into the real context, which reflect the changes in the skills needed, changes in the market and all those kind of things.
Technology enhanced learning is aiming to provide more effective and joyful learning experience using real-time context of the learner. There are people who can’t go to school to have face-to-face education because they either live far in remote areas or have to support their families. By not providing means for education for them, we are cutting a large proportion of population who are actually very intelligent .Technology enhanced research finds ways of how to include them into education, and how learning can take place outside classroom.
Interviewer: How many factors have impact in realizing U-learning?
Prof.: This depends on what do you mean by u-learning. Everything can be very complex. If you start something very complex, it will never even start because you can never reach that. So it is better to start small and slowly grow. In our research we started with only three parameters (learners’ performance, cognitive abilities and learning style). Actually there are lots of things we should learn about learners, but we should start somewhere. What we are doing is very simple that we just want to know about their situation, in what kind of environment they are in, and what is their surroundings. Once the research is progressing, you can add more and more parameters. So let’s start with something useful and then make it more useful.
Interviewer: What is the role of resources in u-learning? How to construct learning resources to meet the demand of U-Learning?
Prof.: In classroom learning, the learning resource is mostly either what teachers write on the blackboard or the materials teachers brought with them. Literally there is no actual hands-on experience by students themselves. Then students can go to library, but time limitation is very high. What they can do is what teacher always told them to do. In e-learning, more and more internet-based information is available from different resources, which are very useful in addition to what teachers provide. You can do what teacher tells you to do and you can do your own research. Even further, many universities, organizations and institutions have started to create meaningful learning objects, so you have more authentic information on the Internet. But those are still pieces of information and not actual experience. That’s where U-learning came up, where actual hands-on experience within the learner’s environment is possible. So, in terms of resources, e-learning can also take place through Mobile devices, so there is not much difference in terms of resources needed for e-learning and m-learning. Resources remain the same.
Now U-learning starts to take advantages of real objects, and it actually does enhance experience. Resources in u-learning are not any more just the virtual information. You have no limitation in what information and objects you can get and when and where you can use them. You can learn in the way that suits you. So that’s the difference in the role of resources that has happened. What teachers provide is mostly for academic learning and not for actual use. And, in library you may find something but again that is limited. In e-learning and m-learning you have only the web-based access. U-learning now brings real experiences. So the role of the resource has changed. The resources themselves have changed. The use of the resources has changed in the way that it has more impact on learners.
U-learning now is more about contextualized experience, it is not just any content, you have to find what suits the individual students. It is about providing students with what they really need at that moment, with that kind of object that is right beside them.
Interviewer: Would you please introduce the outcome of your research group in this direction?
Prof.: There are two kinds of outcomes I would like to talk about. One is the relevancy of learning. As you know I came from Athabasca University which is an open university. So, we do not have any face-to-face students. We want to provide them with better learning and more realistic learning. Most of our students are working. Therefore unless we can relate learning to their work environment, to their lives, to their living environment, it is difficult to engage them and motivate them. Learning for our students is not the most important priority, because they have got families and jobs. That means we compete with other factors they have. Thus the only way to motivate our students is to provide more realistic and more relevant learning to them. That is one of the aims of our research that how can we customize learning to those students.
Another aim is that we believe authentic learning is the key for better learning. Authentic learning is quite near to the real things that happen in real life, in real companies or in real factories. Learning in classroom does not provide that. Therefore, we want to provide learning outside of the classroom, in the field wherever students are. We can provide learning in their working environment so that they can make use of the objects there. So we are not only trying to provide learning to the students who cannot come to school but also to more and more students, and educate much more population by this strategy of realistic learning.
Interviewer: Would you please introduce the recent work under the “Mobile Adaptation Framework ”? (See Fig.1)
Fig.1 Mobile Adaptation Framework
Prof.: This framework actually has been developed for quite some time. What we are doing is extending this framework as our research progresses. This framework provides adaptive learning by fusing different combinations of parameters. You got four different perspectives. One is the user. Who is our user? What do we know about them? In every environment in our daily life, not everything is available all the time. For example, sometimes you have no information about users’ location because they do not have the device or the device (GPS) is not working well. At another point, you may have no information about the operating system the learner has. At another time, you have no idea of how much did the learner know about this particular topic. So at different times you may have some information and some not. You have to make decisions based on whatever there is. How do you do that? You need the framework. You do your best to combine whatever information there is to provide customized learning. And then you wander how the student is reacting and you make real-time changes. If the student reacts badly, you may want to do some changes.
Let’s say, a student is using a cellphone with Android platform, and suddenly the Internet connection went off. So the last information the central system has about the student’s mobile device platform is Android, and in the meantime the student shuts the cellphone and starts to use iPad. So, the system still keeps sending that student Flash content targeted for Android. But now obviously the content does not work. So you have to monitor what is happening at the user’s end and what type of content is supported by the technology available, and you have to make these decisions on the fly. How do you do that? You need certain framework for that. This framework can do it. Although this framework was initiated long time ago with my then PhD student from New Zealand, and I think the first version of it came out sometime in 2005. But that time, it was really focused on Mobile devices. And now this framework is adapted for u-learning. We want to learn more and more things about users, like the platform, the communication and the content. The Content is changing too. A lot of different types of content is coming soon, such as many Flash content that allows interaction. The framework remains the same, but more and more parameters ought to be added. For example, location, which includes many parameters. How can we find the user? There are many ways. Every time your devices is connected to your cellphone provider, it actually connects to multiple network base stations, even though you are actually communicating with only one. That is the reason why you can talk to a person and do not lose the connection even when you are riding a car. By calculating the intensity of the signal from different network base stations, precise location of the student can be determined. Wi-Fi is another example, but to connect to another wi-fi access point, you have to disconnect from previous one. Different types of sensors behave differently, and new technologies have been coming up. Now Google is working on another technology called NFC (Near Field Communication). What NFC is going to do is have touch-less communication which is something similar to what we already have in the subways. We just use the card very near to the device of the gate and we can pass. This technology is being transformed to cellphones. You would not have to carry different cards or other methods to pay for different thing. You just grab your things in a supermarket and go to the checkout; then just pull out your cellphone and payment will be made instantly. If we can do that, it will give identify another usage of the cellphones. When new technology comes up, the question is how we can take advantage of it and what is the most proper technology that one should use at that particular instance. If there is more than one technology available, can they be used together to make more precise calculation of the adaptation requirement?
Interviewer:In this background, what is the difference between user and learner?
Prof.: No, there is no difference. Basically, these are all information about the user, the platform, the communication. This information changes in real-time. But this particular “coordination” component of the framework, based on information from all of these other components, decides what content should be given to the users. So user and learner is the same thing in this context.
Interviewer: Now many researchers in china have engaged in designing and developing Educational Games, and your research team proposed “5R Adaptive Model and Process”（See Fig.2），can you interpret this model?
Fig.2 5R Adaptive Model and Process
Prof.:This model and education games are two different dimensions. This model can be realized within a game or without a game. This model is about how we can provide better u-learning to learners. It focuses on a learner, in a particular location, at a particular time, on a particular device to provide right kind of content. The five parameters interact with each other, and if any of them changes, the outcome will change. So one learner at certain location with certain device at a time will get certain content. Another leaner at the same location with the same device at the same time will get different content because the learner is different. What we are trying to do is to see what the interaction is between the five parameters. The problem is that in u-learning so much information you get that sometimes it is very difficult to do real-time adaptation which requires a lot of processing of data. So we want to do this processing as much as possible in real-time but also identify patterns because when you have patterns, you can make process faster, you can do a lot of probability. How can we do that? This model. We are still working on it. The location part has already been done, and the content part is still under research. How we can provide content from different resources, such as formal content from classroom what teachers provide, content from different social sites, content from repositories such as Wikipedia and also reusable learning objects repositories. How can we combine them in real time, we are still working on it. We do not have the overall solution yet. I think things will keep blooming. This (model) can be done using games; this can be done using different kind of approaches. There are many kinds of applications of the model and one could be educational games.
Interviewer: Learning styles is a component of Learner awareness, How to Track learners behavior to infer learning style?
Prof.:Learning styles are the tendencies students have. There is a lot of literature out there that suggests various clues that tell us if the learner is doing a certain kind of thing for lots of times, and he or she is not doing certain kind of thing for most of the time, then you can say that the learner has this kind of learning style tendency. We did a lot of literature review to identify those clues. We have created algorithms, with the leadership of my colleague Dr. Sabine Graf, to link different students actions to different styles based on the clues. The More combinations you have, the better result you get. That is the way we use to identify students’ learning styles.
Interviewer: Is there a change in monitoring the track of learners’ behavior?
Prof.:This (tracking of learners’ behavior) is not what we started on our own; we started it from the literature. So, from literature, we already identified what actions we need to monitor. Problems happen when you don’t know what to look for. You are tracking while you don’t know what you are tracking for. We don’t do it that way. We first identify a series of actions, and then we track our learners. Our problem is people behave differently. It means somebody may have certain style but is doing nothing, and then we have nothing to observe. While you are reading, you don’t touch or do anything. This is the thing we have to tackle. So, we adopted mixed-initiative approach for our system. This system doesn’t rely solely on users’ initiatives. It actually forces students to do certain things. If you are not doing anything even then, that itself tells us something. So we use mixed-initiative system in which user’s action and user’s responses to the system give us information.
Interviewer: How do you create such mixed-initiative system?
Prof.:Mixed-initiative system approach is not something we created, but we rather adopted it. We did not create strategies for it, we took strategies from the literature. Our interest is on providing adaptivity to the learners, not creating the mixed-initiative system. So we just took what can be applied here and made use of it.
Interviewer: What do you mean by “mixed-initiative”?
Prof.:Mixed-initiative means initiatives from both the users and the system, and we are especially interested in the initiatives from the system side. The system also makes inferences based on the actions of users. There are lots of strategies used in different situations.
Interviewer: In adaptivity, do you pay attention to learning process or the cognitive process?
Prof.:Both. Especially about the cognitive model. In learning styles and actual adaptivity, learning process has a very strong focus. Quite a lot of focus is also on the negative side of it; we want to know why it doesn’t work if that is the case. One of the problems with adaptive system is basically that: they are adaptive. Adaptive systems provide adaptive content. It can happen that the system provides only a few links which suit to the learbers, out of many available. Learners would have no clue what other links are. So they have no way to tell you their feelings if the links provided by the system were wrong, since they have nothing to compare them with. So this is a problem of adaptive systems. A good adaptive system has means for students to check everything. They recommend the content but never remove things. So the system can also check the negative side of learner’s action, what are the impacts of this kind of adaptivity in the process. So pedagogy matters most, technology the second. Is the learner following the pedagogy and is he/she learning or not. So learning process is the key in adaptive system, and the cognitive process is one factor in the overall process.
Interviewer: Your research team has developed some edudational game, such as “Context-Aware Mobile Educational Game —Query based learning”, Can you introduce this “Educational Game” and the effects of Educational Game in classroom in Canada?
Prof.:One big idea behind educational games is that they should be based on context. First of all we have to decide where the learners are, what kind of things they want to do, what kind of preferences they have, and how we can use all these to provide learning. We have lots of content; we have lots of aims that can match with the content. Then based on the information available about the learner, we can create sequence of curriculum, using different content and activity. Most important, it’s not only content, its content and activity. We have done a lot of research in this area, under the leadership of my colleague Dr. Maiga Chang. I give an example here, for a system developed for the Palace Museum in Taipei. Learners first indicate that they want to know certain item in Qing Dynasty or Ming Dynasty, and then based on that we use the context-aware system. Based on where they are, what kind of things they want to do, context-aware system proposes something for the learner to select. Based on the selections, the system creates an internal sequence of activities for the learner to do inside the museum. Now you are here, these are the things you want to do, based on the selection you did, the system then give you certain tasks to do in the form of challenge and competition with other learners. The way you do the task can change the whole sequence of further content. The more successes they get the more rewards they get. The rewards can then be used to get help tips, e.g. at times when they don’t know something what they need to find, they can use those point to get help. Learning is not only about being able to solve, but also motivation. So as long as students are actually learning from it, the system keeps tracking of what they are learning, how they are learning, which thing they did not learn, and what they did not learn is then provided in another form. So the aim of the game is to keep learners motivated in order to ensure learning.
You see, game is something you can play even after a whole day of exhausting work. Why, because it gives you excitement, and gives you joy and relaxation. That’s game and we want to do it with real context. And it can work in or outside classroom depending on what you mean by a classroom. In museum, the whole class is in the project and they have to do interactions with each other.
Interviewer: Educational games improve students performance?
Prof.:It is an ongoing assessment. The problem is that you can’t generalize educational games. Just because I create a game and I find it to be improving performance doesn’t mean all games do. What we can say is that, the research shows that games can be developed in a way that can improve performance. You cannot say all games can do. How can learning be provided more interesting using a game approach is the challenge not for students but for teachers.
Interviewer: What do you think is the important components during designing Educational Game?
Prof.:There is a talk in TED.com by Tom Chatfield about educational games which is excellent. I would highly recommend watching it to anyone who intends to develop educational games.
Interviewer: What do you mean by “Causal learning analytics”? and why do you propose this term? what is the causal model?
Prof.:Causal learning is focused on identifying the causes of learning. What factors are affecting learning? That is causal learning. This research in my group is headed by my colleague Dr. Vive Kumar.
In u-learning, the students are not with the teachers at the same geographical location. Even if they were, it is not easy for teachers to find out what made the learning happen. Let us take an example of learning programming. What teachers see is the final program. What they cannot see is how the student wrote it and what the student was thinking at that time. Students have their own thinking pattern. While writing a program, one has to see what the dependencies are, declare the variables, and then variables can be used. That’s the right sequence. But in practice, student often forget this and go back to the beginning of the program to add declarations of variables when the compiler complains about errors. But teachers didn’t see this. Then teachers will not understand that the student may not have learned because the mistakes are corrected by the tips given by the compiler software. Causal learning allows seeing these causes. What you have to do in the first place is to get all the data while student are actually writing the program – every keystroke, every movement of the cursor. You have to analyze all the actions that are happening. Then you have to identify the causes. That’s the causal models. After that, based on the student’s actions and his/her causal models, you can identify where the student is likely to make mistakes or identify patterns of student’s actions that are causing problems. If every time the student didn’t declare, that’s the pattern you have to identify. Based on those patterns, you have to do instructional design. Then you use technology to implement. Because in u-learning, teacher is not everywhere, that means everything has to be done independently. That’s causal learning. We have done it in two different subjects, one is computer programming and another is learning of English, basically English writing.
Interviewer: what is learning analytics？
Prof.: Learning analytics means analyzing all the data coming from the learner to make some meaningful patterns.
Interviewer: The goal of it?
Prof.: Aiming to identify where the learners need help and how we can help. Learning analytics allows us to identify what actions students are taking that we should consider in order to improve learning process.
Interviewer: What is your research work towards future?
Prof.: What we want to do is to provide better learning. How do we do it? Learning relates to numbers of different factors. One is community. In Canada, we have natives and minorities and immigrant communities from different countries. We want to provide learning to different communities. Then we also want to develop partnerships, with industries, with different institutions. Because we can’t do everything ourselves, and we don’t have everything we need. We know what we have and then go ahead to look for what we don’t have. Next is about the projects we choose. Our focus is Application-oriented research. Unless we can see that there is real benefit to people, there is no need doing it. We don’t do things just because we like, there has to be meaning to it. Then the funding for it. Different funding have different requirements. If they have the money but their requirement we can’t agree with, we can’t accept it. For example, if they say you have to hide your research for next five years, we can’t accept it, because research has to be open for everyone. And then the HQPs (highly qualified personnel): masters\PhD students and postdocs. Because these are the people who will be the future researchers. So we have to focus on training better HQPs. We also do interactions with other groups and exchange lots of different things. And then our capacity to do all those. We don’t want to work on things we would not be able to do. We start simple depending on what capacity we have and how much we can do. And then we grow. So that’s called sustainable research. Research that continues.
Thank you very much!