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Mobile Learning in Context Christoph Pallasch Institute for Computer Science RWTH Aachen Aachen, Germany [email protected] Esra Yalcin Institute for Computer Science RWTH Aachen Aachen, Germany [email protected] ABSTRACT Mobile learning is the new kind of learning method researchers superimpose onto. It breaks through the restrictions of tra- ditional learning and enables a new possibility for learners to gain knowledge. In this paper we do not just focus on general mobile learn- ing but also how the learning process can be broaden if we take the learner’s context into account. We will define the term context, discuss what kind of information belongs to the context, and examine the advantages for the learning process to include a user’s context. Another aspect that is covered is to explore which learning theories are used. We will see how they are transformed into mobile learning in context and discuss the advantages and disadvantages of these theories. We will also have a close look at some approaches that en- able mobile learning and consider a user’s context. The fo- cus will be on what kind of information is used to generate a user’s context, which new functionalities have been possi- ble by integrating the context, and if learners conceived the approaches as helpful or not. 1. INTRODUCTION The most distributed learning method is still the teacher- centered learning, although there have been a lot of re- search proving the inefficiency of this way of learning. It is obvious that learning within a classroom depending on a schedule and disturbing classmates restricts the learning process enormously. The learner is bound to a certain lo- cation, time and people neglecting his current motivation to learn. These circumstances decrease the possible learn- ing effect of the learner since this way of learning is not tailored to his personal needs. There have been a lot of research how to improve this way of learning and how to support ”classroom-learning” . What is getting established is computer-supported learning. Nowadays in schools comput- ers are integrated into the learning process. This approach is more student-centered but still not flexible enough. Stu- dents are bound to the location to work on a desktop com- puter or have to carry a notebook with themselves. Mobile learning in context combines different learning theo- ries and systems. In Section 4 we will introduce and discuss about theories that are applied as non-formal learning, situ- ated learning, technology-enhanced learning, lifelong learn- ing and self-organized learning. Furthermore we want to ob- serve which aspects of these theories are converted to mobile learning in context and which advantages these integrations offers. The propagation of smart phones within the last years led to a new possibility for learning called mobile learning. The idea is to overcome the mentioned limitations by facilitating learners to learn anywhere and anytime through a portable device that one always carries on one’s person [24, 39, 9, 34]. Learners shall be able to gain knowledge whenever and wher- ever they want to. That means mobile learning takes place when learners are motivated so that they probably reach a higher learning effect. Another advantage is that everyone carries his device always with himself. This way students are not aware of their learning device but are always ready to start learning. Thereby one possibility is to give the user access to learn- ing materials, so that he can review slides or read uploaded literature. That is a general approach which shall fit to ev- eryone. Another approach is to take the context of a user into account to enable personal learning. The context of a user concerns any kind of information that describes the user himself and his current situation [19]. This includes in- formation about the user’s identity, his knowledge level, his location, and his device’s capabilities. If the system knows the user, it could provide only information of courses the user is participating at. Being aware of a user’s knowledge level, helps to offer exercises suited to his knowledge. With- out this information, everyone would get the same exercises which could be too simple or too difficult for some of the students. Applications that are location-aware can offer a lot of additional features exceeding the functionality of a typical learning management system. The application can notify the user about other learners that are close to him to organize learning groups or notify about additional informa- tion sources about topics the user is currently learning like libraries with appropriate books or certain exhibitions. The device capabilities are also a major issue for efficient learn- ing. The system must be aware of the capabilities of the connected device. For the correct representation of the in- terface, the system must know the screen size, for example. The system should also be aware about the possible input techniques of the device to execute the user’s commands cor- rectly. Although the consciousness of the device capabilities plays an important part in context-aware learning, this topic wanders off the subject of mobile learning. We are aware of the difficulties that occur when running the same applica- tion on devices with different capabilities [10, 41, 2], but in this paper we will neglect this research area. We want to put an emphasis on the new opportunities that emerge by

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Mobile Learning in Context

Christoph PallaschInstitute for Computer Science

RWTH AachenAachen, Germany

[email protected]

Esra YalcinInstitute for Computer Science

RWTH AachenAachen, Germany

[email protected]

ABSTRACTMobile learning is the new kind of learning method researcherssuperimpose onto. It breaks through the restrictions of tra-ditional learning and enables a new possibility for learnersto gain knowledge.In this paper we do not just focus on general mobile learn-ing but also how the learning process can be broaden if wetake the learner’s context into account. We will define theterm context, discuss what kind of information belongs tothe context, and examine the advantages for the learningprocess to include a user’s context.Another aspect that is covered is to explore which learningtheories are used. We will see how they are transformed intomobile learning in context and discuss the advantages anddisadvantages of these theories.We will also have a close look at some approaches that en-able mobile learning and consider a user’s context. The fo-cus will be on what kind of information is used to generatea user’s context, which new functionalities have been possi-ble by integrating the context, and if learners conceived theapproaches as helpful or not.

1. INTRODUCTIONThe most distributed learning method is still the teacher-centered learning, although there have been a lot of re-search proving the inefficiency of this way of learning. Itis obvious that learning within a classroom depending ona schedule and disturbing classmates restricts the learningprocess enormously. The learner is bound to a certain lo-cation, time and people neglecting his current motivationto learn. These circumstances decrease the possible learn-ing effect of the learner since this way of learning is nottailored to his personal needs. There have been a lot ofresearch how to improve this way of learning and how tosupport ”classroom-learning”. What is getting established iscomputer-supported learning. Nowadays in schools comput-ers are integrated into the learning process. This approachis more student-centered but still not flexible enough. Stu-dents are bound to the location to work on a desktop com-puter or have to carry a notebook with themselves.

Mobile learning in context combines different learning theo-ries and systems. In Section 4 we will introduce and discussabout theories that are applied as non-formal learning, situ-ated learning, technology-enhanced learning, lifelong learn-ing and self-organized learning. Furthermore we want to ob-serve which aspects of these theories are converted to mobile

learning in context and which advantages these integrationsoffers.The propagation of smart phones within the last years ledto a new possibility for learning called mobile learning. Theidea is to overcome the mentioned limitations by facilitatinglearners to learn anywhere and anytime through a portabledevice that one always carries on one’s person [24, 39, 9, 34].Learners shall be able to gain knowledge whenever and wher-ever they want to. That means mobile learning takes placewhen learners are motivated so that they probably reach ahigher learning effect. Another advantage is that everyonecarries his device always with himself. This way studentsare not aware of their learning device but are always readyto start learning.Thereby one possibility is to give the user access to learn-ing materials, so that he can review slides or read uploadedliterature. That is a general approach which shall fit to ev-eryone. Another approach is to take the context of a userinto account to enable personal learning. The context ofa user concerns any kind of information that describes theuser himself and his current situation [19]. This includes in-formation about the user’s identity, his knowledge level, hislocation, and his device’s capabilities. If the system knowsthe user, it could provide only information of courses theuser is participating at. Being aware of a user’s knowledgelevel, helps to offer exercises suited to his knowledge. With-out this information, everyone would get the same exerciseswhich could be too simple or too difficult for some of thestudents. Applications that are location-aware can offer alot of additional features exceeding the functionality of atypical learning management system. The application cannotify the user about other learners that are close to him toorganize learning groups or notify about additional informa-tion sources about topics the user is currently learning likelibraries with appropriate books or certain exhibitions. Thedevice capabilities are also a major issue for efficient learn-ing. The system must be aware of the capabilities of theconnected device. For the correct representation of the in-terface, the system must know the screen size, for example.The system should also be aware about the possible inputtechniques of the device to execute the user’s commands cor-rectly. Although the consciousness of the device capabilitiesplays an important part in context-aware learning, this topicwanders off the subject of mobile learning. We are aware ofthe difficulties that occur when running the same applica-tion on devices with different capabilities [10, 41, 2], but inthis paper we will neglect this research area. We want toput an emphasis on the new opportunities that emerge by

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using context-aware mobile learning methods. That is whywe will introduce approaches that enable new possibilities tomobile learning and mainly concentrate on user-awarenessand location-awareness.

In Section 2 we will shortly discuss the main characteristicsof mobile learning. In Section 3 we will talk about contextand the opportunities of context-aware applications in moredetail.In Section 4 the learning theories that occur in mobile learn-ing are introduced and their advantages and opportunitiesare discussed. In Section 5 some approaches using context-awareness for mobile learning are introduced to get an ideaabout the current state-of-the-art in this research area. Ashort summary and conclusion will follow.Finally, we will introduce our own approach, GonnaSeeYa,regarding mobile learning in context.

2. MOBILE LEARNINGIn the past years the technology progress in broadband com-munication evolved in such a manner, that it is possible touse network connections at nearly all places. Additionally,data rates evolved in a positive way such that using networkconnections which provide a huge amount of data is onlya minor problem in our days. Moreover, technology pro-gresses in mobile devices lead to more and more shrinkinghandy devices which can be ported by everyone everywhere.Although their size get smaller their computational powerincreased leading to small powerful devices which are capa-ble of solving hard computational tasks and moving moreand more in direction of ubiquitous computing where suchdevice are used in an unobtrusive way. The mobile revo-lution indeed changed the everyday life. All these factorsgive users a new way of interacting with network connec-tions and thus giving a new way of using mobile learningplatforms or thus developing new mobile learning platformswhich make use of these new technological advances. Firstof all it is important to understand what mobile learningis in general. As stated out in [9] mobile learning is “anyactivity that allows individuals to be more productivewhen consuming, interacting with or creating informationmediated through a compact digital portable devicethat the individual carries on a regular basis, has reli-able connectivity and fits in a pocket or purse ”. Sogenerally spoken mobile learning is an interaction or activ-ity of an individual which uses a mobile device, capable ofhaving a reliable connection to communicate with a mobilelearning platform, with the main goal to handle informationin a consumerist, interactive or creative way. Furthermore,mobile learning has some properties depending on the user,the user’s environment and the used technology. Mobilelearning is a very time-constrained task, delivering context-oriented content. As the smart phone is used in betweentwo tasks by the user the time interval where he can cap-ture information is very short and should not overload hiscognitive load. Learning is normally done on-the-fly, thismeans very fast and mostly during tasks where the user ismoving somewhere or has to wait for something to happen.So the provided information has to be personalized to hisneeds. Moreover, mobile learning is a multimodal interac-tion using several technologies located on the mobile device,

like speech recognition, sound, touch gestures and so on.Lastly mobile learning can also be used in a collaborativeway where the user contacts others who can also help him(e.g., friends, fellow students or even experts) [34, 30, 40].

But to accomplish mobile learning in a satisfiable way, alsothe properties of the mobile device have to be consideredvery precisely. Nowadays, mobile devices are not only usedfor telephoning, but also for computing, messaging and themajority usage is the processing of a huge amount of multi-media load, of course. As already mentioned, mobile devicesare mostly always carried everywhere and everyday. Thismakes mobile devices a perfect learning medium which canbe used in many situations [30, 40]. But it has also be keptin mind that these devices also have some deficits, which canbe overcome easily if the architecture of the mobile learningplatform is developed thoroughly. A mobile device has onlya specific amount of battery power which discharges veryquickly when it is used together with network communica-tion. The limited bandwidth is also one gap which has tobe considered very well, as huge amounts of data cannot betransferred so easily and also in time. Data has to be trans-ferred in time as the usage intervals of the mobile learningplatform are frequent but very short, thus the user cannotwait that long for incoming information. Furthermore, amobile device is not as powerful as a personal computer. Dif-ficult computing operations have to be made on a server orother technology which provides enough computation powerto solve hard computation tasks. The mobile device shouldonly process the presentation of the computation results.But also the presentation is another point which comes inmind as the possibility to display graphical elements on thescreen depends on the resolution and the screen size of themobile device. Last but not least, mobile devices lack onresources. It has to be assumed that the amount of possibleresources is low, because also other applications running onthe smart phone share them, too.

The aspects explained above are one of two dimensions.This dimension is the technical dimension which concernsthe used technologies in a mobile learning context. Anotherdimension is the user himself. This mainly depends firstlyon the background knowledge of the user. The more theuser knows, the more precise the information can be. Fur-thermore, the concentration level of the user plays also avery important role in mobile learning scenarios. The levelof concentration determines how much information the usercan capture while being distracted by the environment orhis personal mood.

So, as one can see mobile learning has to consider severalchallenges concerning the user and the used technology. Aswe will show in further sections the user himself can be di-vided into two states: the user intrinsic state and the userextrinsic state. The user intrinsic state depends on the userhimself and his personal mood, while the extrinsic state de-pends mainly on his environment. Mobile learning has tohandle the specificity of the mobile device with respect toits constraints. Furthermore, the presentation layer has tobe adapted to it. Backward compatibility to existing sys-tems has to guarantee, as although the technology evolves,the majority of mobile devices and also the majority of theused technology does not. Lastly mobile learning has to

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align to the used pedagogy.

3. CONTEXT-AWARENESSAlthough the communication and hardware technology al-lowed to introduce a new way of using mobile learning, it isnot always possible to use the complete spectrum of possi-bilities given. This is because the efficiency of using a mobilelearning platform strongly depends on the individual’s envi-ronment, his mental state, the communicative possibilities,and current capabilities of the mobile device used by the in-dividual, in other words this is meant to be the context [15,40]. In general, the context is an information which charac-terizes the situation of an entity [38]. An entity is a resourcewhich participates in mobile learning processes, e.g., the mo-bile device, the user himself or any object that is importantfor the interaction between user and application [24, 12, 26].To make it even more clear: context can be any kind of in-formation to determine, specify, or clarify the meaning of anevent [32]. To give all this information context consists ofmany different aspects. The main goal of mobile learningis to let the user achieve the most efficiency of using a mo-bile learning platform in certain scenarios, it makes sense tocharacterize context by limitations which provide the rangeof realistic possibilities to fulfill this goal. These limitationscan be summed up to three categories: a user’s extrinsicstate, his intrinsic state and the technologies he uses (Fig-ure 1).

3.1 Extrinsic StateThe extrinsic state deals with a user’s current environment.That contains the user’s current position (location), time ofthe day and the interval in which the user learns (time), andthe object the user currently deals with and how this infor-mation can support his learning (analog-digital).The location offers a lot of information that is useful to sup-port the learning progress. That is probably why it is of-ten used synonymously with context [28]. If an applicationknows where the user currently is, it could advise the user tovisit a library which is close to him and which offers booksabout the topic the user is studying right now. It also candraw his attention to an exhibition that could be interest-ing for him. Another possibility of location-awareness thatis often mentioned is to show people of your learning groupwhen they are close to you, so that you can meet with themand chat about current topics so that you get a deeper un-derstanding [7, 16, 28, 33]. Moreover, the place determinesthe frequency of distraction. E.g., the user is much moredistracted on a bus station than in a train. So this informa-tion even helps to define the concentration level of the user.Furthermore, time plays an important role as when the userhas to change locations it is often impossible to continueusing the mobile platform because the user has to focus onprocessing his environment. So the time interval betweenchanging locations is important as the information presentedto the user should not exceed the time limits because thenthe user is not able to use the information efficiently any-more [24]. For collecting information about the user it is alsoof interest at which time of the day the user learns usually,what is next on his timetable and how long the interval is inwhich the application is used by the user [24, 19]. This wayhis individual pace and his habits can be known to improvepersonal learning.

The last mentioned aspect here to capture user’s extrinsicstate is called analog-digital. It deals with the possibility tocombine digital information and analog/real world objects.That means to an object the user sees in reality the applica-tion provides him multimedia data. The application on thedevice has to detect the object, which can be everything likea building or a painting, and download related data from aserver [19, 14]. For example, Bob is visiting London for thefirst time. Every time he sees an interesting building like theWestminster Abbey or Big Ben, he focuses with the cameraof his mobile device on the building and gets informationabout how the building looked like and what purpose it had.In a museum he gets informed about the exhibits when fo-cusing on them with his mobile device. Thereby the datacan be text, audio or video. The limitation analog-digitaldelivers very important context information since the user ishighly motivated in that situation and the probability thathe really learns is higher. At the moment, the connectionbetween analog and digital objects is mostly realized in thearea of augmented reality.

3.2 Intrinsic StateThe second category, user’s intrinsic state, deals with theinside of the user. This contains the user’s knowledge level,his concentration level, and also his motivation level.Learners have different knowledge levels. It depends on theirconcentration when getting in touch to a topic, their previ-ous knowledge, their knowledge about related topics, andtheir given skills. In the development stage of a learning ap-plication it is important to adjust the system to these differ-ences. The less the user knows about a given topic the morebasics have to be provided to the user to let him understandthe information step by step. Having more knowledge aboutan information leads to providing more deep and more pre-cise details about the information for the user. The systemmust inquire the user’s knowledge to provide him with suit-able learning material and to be able to decide what the usershould learn next. In [24] an approach is introduced whichshows alternatives to take the knowledge level into account.When a user joins the system for the first time, he is askedgeneral questions to measure his knowledge. Depending onthe evaluation, the system offers the user personal learningmaterials. Every time a user finishes a topic he has to par-ticipate in a small test where he has to answer several topicspecific questions. Depending on the results, he has to re-peat the topic or is unlocked for the next level. Followingthis idea and adding the knowledge level to the context sup-ports learning since learners get suitable materials so thatthey learn without being discouraged because of too difficultquestions.Another aspect in this category is the concentration level.It has a great impact on the success of learning. If the con-centration is low, the user will hardly learn and needs a lotof repetitions. If the system knew about the user’s currentconcentration level, it could react, for example, by providingmaterial via different channels to obtain the user’s attention.But measuring the concentration is very difficult because itis hard to capture and it changes during the usage of thesystem. Just asking the user, if his concentration level islow, medium or high [24] does not add further informationto the context because the user could simply lie, he mightnot be aware of his real level, or the level changes during

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Figure 1: Aspects of context

learning. So other techniques are required. One could useother state information like the location or the time to mea-sure the concentration. For example, if you are standing atthe main train station with a crowd of people around you,you will probably be not highly concentrated since there aremany distractions. So the location contributes to the con-centration, but also the time of the day, which could be asign for your tiredness, and the time available for learning.In [32, 31, 36] they suggest to use sensors to capture eye gazeshifts and algorithms to evaluate and interpret the findings.But they also say that it is difficult to accomplish the rightinterpretation so far.It is even more difficult to measure the current motivationlevel of a user. Although it is an important context infor-mation the motivation level is rarely part of the context ofapproaches nowadays. The main reason is that it is hard tocapture. There are methods of detecting facial expressionswith algorithms ([36]) but interpreting them does not worksufficiently yet. One possibility of understanding low moti-vation could be to use the information the system gains outof knowledge testing. If the user cannot answer the questionsat the end of a topic correctly, he was probably not moti-vated. In this case the system should be able to provideinformation about this topic in other ways like using audiosources, videos, or learning games to motivate the learnerand thus gaining his attention.

3.3 Used TechnologiesThe other limitations concern the hardware and technolog-ical properties of mobile devices and the currently availablecommunication medium. The physical constraints are:

• Bandwidth

• Communication technology

• Display size

• Memory

• Sensors

• Peripherals

• Battery

• Operating system

Bandwidth is a very limited resource. Depending on thegiven bandwidth, the type of data which should be sentfor a requested information must be adapted to, otherwisethe user is not able to process the information adequatelybecause of traffic problems. Moreover, the used communi-cation technology gives hints about the mobility and thequality of the connection (or the frequency of connectionlosses). E.g., using WLAN provides much more stabilitythan using mobile connections, because the data can be splitin much larger packets. The quality of mobile connectionschanges depending on the current provider and available sig-nal strength on a location. Another point is the display sizewhich limits the spatial allocation and size of GUI elementsof the provided content. Application developer must thinkof a design that enables easy, intuitive, and fast navigationindependent of the screen size. Memory is another limita-tion which affects how many data can be cached or stored ona mobile device. Applications should not claim much mem-ory because this will deter learners from using it. Therefore,one could offer storage within a cloud, for example. Anothervery important limitation is the availability of sensors. Themore information can be retrieved from a mobile device, thebetter is the estimation of user’s context. An available gy-roscope gives the information, that the mobile device is ableto change the display between portrait and landscape modewhich additionally affects the spatial allocation of GUI ele-ments of the provided data. An accelerometer can be usedto determine whether the user is in move or not. Geoloca-tion can be used to estimate the type of room the user isactually in (e.g., bus station, museum, lecture hall).

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Further information to various sensors and the possibilitiesthey offer can be found in [22, 31]. Peripherals give informa-tion about the types of input and output peripherals. Forexample, the usage of a touchscreen differs enormously tothe usage of a keyboard, because of the possible range ofinteraction techniques, like gesture recognition and so on.The available battery power which determines the type ofprovided data content of an information is also important.Applications that use much of this resource will not willinglybe used by learners since their mobile device is not just theirlearning medium but also cell phone and PDA. Another issueis having different operating systems for which applicationshave to be developed. Applications should be installed eas-ily, run correctly and equally on every system. So that thetarget group is not restricted by technical misdetermination.

3.4 Benefits of Context-AwarenessWhen learning in class the teacher can see and interpret thefacial expressions of the learners easily and can offer helpexactly at that part of the topic that is not understood cor-rectly. But computers or smart phones are not able to see allexpressions and understand each of them correctly. That iswhy mobile learning without context is not really beneficialfor the learning process. It is the same material for everyonein every situation. Thus, it has no personal aspect. Learnerscould feel discouraged by this kind of learning because thelearning level could be inappropriate for them, they couldmiss a teacher’s support, and feel isolated. Taking the con-text into account changes the situation entirely. The contextcan identify and characterize a user quiete percisely and of-fer personal learning by providing material that fits exactlyto the learner’s knowledge level. With the use of sensorsand algorithms that translate the findings to reactions ofthe learner, mobile learning enters a new level of providingaccurate personal learning. If the learner has problems atsome point, sensors could capture this and algorithms couldinterpret it, so that the system offers support. Moreover, bytaking the learner’s environment into account, applicationscould suggest to visit locations that are related to the cur-rent topic to motivate the learner and keep him interestedby using different sources for teaching. Another possibilityis to suggest other learners to support collaboration. Thisis often done by locating the user and informing him aboutclass mates close to him. In section 5 we will analyze currentapproaches on how far they are using context information formobile learning applications and see in section 6 on whichaspect of context the emphasis will lie on in research in thefuture .

4. LEARNING THEORIESIn this section we want to discuss learning theories on whichmobile learning in context is based on. So that thereis a better understanding of the requirements, the benefitsand the drawbacks of this kind of learning.

When learning in class, there is a given timetable when stu-dents have to be in class and learn. So no matter if theyare motivated or not, they attend the class and learn differ-ently intensive. But when using a mobile device as learningmedium, the student is not bound to a specific time and lo-cation. On the one hand students learn just if they are reallymotivated and learn consequently deeper, but on the other

hand there is no guarantee for their motivation. So it is anobligatory requirement for mobile learning applications thatthey are used by intrinsic motivated learners. Theseare people who are interested in the topic itself and enjoyworking on it. This kind of learners do not need additionalstimulus because there is a strong relationship between thelearner’s goals and interests and so these learners are highlymotivated [35]. This leads to a deeper learning. In most ap-proaches this kind of learners are assumed so that studentsuse the application without any forces.

The learning theory that is mainly mentioned in the con-text of mobile learning in context is situated learning [5,18, 17, 24, 26, 39]. It is based on Cognitivism and above allon Constructivism. In Cognitivism the learner is seen asan individual who processes stimuli, thus the information,on his own. That means that the process of understand-ing does not solely depend on external stimuli as knownin the theory of Behaviorism.The Constructivism’s mainidea is that knowledge emerges by an individual construc-tion of ideas and concepts [4]. That means learning is theprocess of constructing an own understanding and this de-pends on the learner’s social context. In situated learningthe current learning situation, thus the context, plays an im-portant role in knowledge construction [4]. The idea is thatstudents learn within the same context they have to applythis knowledge at [24, 39]. Another aspect of this theory isthat it takes learning as a situated activity and that learn-ing happens by practicing [18, 17]. So it is all about activelylearning combined with communication and the direct pos-sibility to apply the newly learned topic. Applications thatsupport mobile learning in context obviously take the user’scontext, thus the situation, into account. Since the majorityof the approaches consider the location, they can notify theuser about classmates or on-topic objects like museums [7,16, 28, 33]. To fulfill the other demand of practicing andapplying the learned knowledge, applications provide a testat the end of each topic. This way users can apply theirknowledge immediately and get response about their per-sonal learning success.

Many plain learning applications have characteristics of pro-grammed instruction. It is based on Behaviorism whosecentral idea is that everyone learns the same way and thatlearning itself must only be adjusted by reward and punish-ment [4]. Of course, nowadays researchers know that everyindividual learns on his own way and above all there aregreat cultural differences to consider when creating a learn-ing program [23]. But still programmed instruction is of-ten used since it is easy and fast to develop. Applicationsbased on programmed instruction start with easy tasks andincrease the complexity. The idea thereby is to generatequestions the way that the probability is quite high to beanswered correctly to motivate students to continue. Theadvantages are that students can start and stop at any po-sition, they get immediate feedback on their input, and stu-dents just progress if they have understood the chapter be-forehand correctly. The drawbacks are that questions oftenare too simple and one dimensional. There are just questiontypes like multiple choice or text to be filled out. Studentshave no influence on the order of learning materials, so theyfeel controlled. Additionally, since the questions are alwayson a quite simple level, there is too little challenge for the

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students. So this kind of learning is not efficient for deeperlearning.

There are a couple of other learning theories which can befound in mobile learning in context. The most obvious onesare multimedia enhanced learning and technology en-hanced learning which both describe learning that is sup-ported by technologies. The main idea is to overcome thelimitations (e.g., location and time) of normal learning liketeaching in class [19, 29]. Learning via a mobile device over-comes these limits and offers knowledge by different multi-media like written text, visual or audio.Another theory that must be mentioned in this context isself-organized learning. Here, learners must take respon-sibility for their own learning and put this into successfulaction to acquire knowledge [37]. That is exactly what is re-quired by the users of mobile learning. They are responsiblefor theirselves to use the provided services and materials.The decision when and where to learn is left to the user ofmobile learning services. That means he has to organize hislearning actions on his own. So this kind of learning can-not be managed or forced. The only way to interfere in thelearning process is to provide a beneficial environment whichmotivates users to learn.In [24] the system offers each user adaptive learning mate-rials based on their demands by evaluating learner models.This is a characteristic of adaptive learning.Until now mobile learning is not used solely. That means itis used as a supportive method. Usually it is applied nextto the teacher-centered teaching. So the theory of blendedlearning is fulfilled because it is a mixture of face-to-faceand multimedia learning [19].Non-formal learning occurs when someone has the goalto learn about a specific topic and learns self-initiated. Thiskind of learning requires intrinsic motivated learners, of course.Here, the user learns whenever he finds time, e.g., at thebus station, during lunch or at night. It does not matter be-cause the learner is sufficiently motivated to acquire a deepknowledge. There are a lot of applications offering this kindof learning for the mentioned type of learners like languagelearning applications.Mobile learning does not only address pupils and studentsbut rather people of all ages. This follows the idea of life-long learning which covers all learning activities in one’slife [6]. Thereby it can be formal learning in school or non-formal learning in one’s spare time with the aim to gain orimprove knowledge, skills and competence.

5. APPROACHES FOR LEARNING IN CON-TEXT

In this section we present four state of the art approachesand stress out the idea, the realization and a tabulary sum-mary for each of the approaches compared to the followingcontext-aware criteria:

• Time

• Location

• Analog-Digital

Theory Main idea Relation

Cognitivism Learner is an individ-ual who processes in-formation on his own

Learning material isadjusted to individ-ual needs by usingcontext

Constructivism Knowledge emergesby an individual con-struction of ideas andconcepts

Learning depends onthe social contextwhich can be offeredby mobile learning incontext

Behaviorism(ProgrammedInstruction)

Everyone learns thesame way

Such applications areeasy and fast to de-velop and thereforewidespread

SituatedLearning

Learning happens bypracticing

Direct possibility toapply learned knowl-edge

Self-OrganizedLearning

Learners must orga-nize their learning ontheir own

Since mobile learningis not limited to time,users must organizelearning actions ontheir own

LifelongLearning

All learning aci-tivities undertakenthroughout life

Mobile learning canbe applied for all ar-eas and for all ageclasses

Multimedia& TechnologyEnhancedLearning

Learning is sup-ported by technolo-gies

Enables learning ev-erywhere and -timeand provides knowl-edge by differentmultimedia

Non-FormalLearning

Self-initiated learn-ing

Users learn becauseof their own interest

AdaptiveLearning

Providing personalmaterials by evaluat-ing learner models

User gets learningmaterials dependingon own needs

BlendedLearning

Combination of face-to-face and multime-dia learning

Mobile learning isapplied as support-ive method nextto teacher-centeredteaching

Table 1: Relation of theories in regard to mobilelearning in context

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Figure 2: Goggle hardware architecture of MARS

• Concentration

• Knowledge

• Motivation

• Technology

There were many approaches which used contextual infor-mation for mobile learning purposes. From all selected ap-proaches which can be found in [17, 33, 40, 26, 1, 27, 8, 25,20, 11, 13, 21, 14, 38, 3, 24] we took the last four [14, 38,3, 24] because these four used the most interesting contextinformation and differed from the standard.

5.1 Mobile Augmented Reality System

Idea. The Mobile Augmented Reality System (MARS) is anapproach for continuous autonomous instructions for learn-ers. The learner should be able to be flexible in his move-ment. The system should realize the environemnt and fur-ther parameters to provide context-aware information. Fur-thermore, the user should be able to use multimodal mediaand animation which supports his learning abilities. Espe-cially the usage of graphics should enhance the user’s con-centration. Finally, MARS was designed to support the useras life-long learning technique and adapts to various environ-ments [14].

Realization. MARS comes with two main components. Thefirst one are goggles which are used by the user in his learningprocess. Goggles consist of a see through heads-up display,allowing to project graphical objects on top of the goggles’glasses to augment the perceived reality by overlaying per-ceived environment with rendered graphical content. Thesegraphical objects could be objects representing old buildingsin the environment of the user. For receiving informationand displaying them, these goggles have a built-in antennaand a wireless communication device for intercommunica-tion with the base station. The user gets his informationeither visual or acoustic via the built-in speakers. It is pos-sible to interact with the system by speech recognition. Forthis, the goggles have a small microphone. Furthermore, torecognize the environment thus to be more precise in order

to recognize objects seen by the user, the goggles have also abuilt-in camera which looks always in the direction the useris facing to. Finally, the goggles have a pair of lithium ionbatteries to supply all the hardware with enough power.

The other component of MARS is the base station withthe computation software running on it. A virtual instruc-tor plays the role as pedagogical agent. It personalizes thelearning according to user’s needs. Information is delivereddepending on the user’s location and the environmental con-text. To facilitate the user’s learning process, the learningtask is scaffold. This means every learning task is decom-posed into smaller components and for each component alink is created to the user’s knowledge. Scaffolding is doneas long as the user himself is able to fulfill the task on hisown. The guidance in the scaffolding process is decreased foreach component of the task which was accomplished success-fully by the user. Lastly the complete system uses OpenCVfor object recognition and filtering of the received image ofthe camera. For speech recognition the Java Speech APIwas used.[14]

Tabulary Summary.Criterion Description

Time Satisfied (base station is connected to theinternet)

Location Satisfied (position of the user can be com-puted by antenna)

Analog-Digital Analog and digital are satisfied viaaugmented reality and information flowthrough wireless communication

Concentration Satisfied (due to graphical overlay)Knowledge SatisfiedMotivation Not satisfied - no information or clue in-

cluded in description of MARS

5.2 Context-aware learning services

Idea. The basic idea of this technique is to provide thelearner with the right learning services and the right rep-resentation of information at the right time and place. Thecontext of the user is therefore very important. Further-more, a situation, in which the user is in, is classified intoprivate, public and driving. Private situations are situationsin which the noise level can be as high as at home. Pub-lic situations on the other hand are situations in which thenoise level must be quieter than in private situations (e.g.,in the cinema). Lastly, driving situations are all situationsin which the user himself is driving. According to the cur-rent context, the learning services are chosen and adapted.For example, while driving a car and perceiving informationabout a documentary report, the system turns-off the videosequence but keep playing the audio sequence [38].

Realization. The main realization is done via a self madeP2P tool in which search queries can be feed in. The systemis driven by keyword search via a keyword thesaurus com-bined with a personal user specific thesaurus. For semanticsearches, a concept map is created and each keyword conceptis mapped to a specific related concept [38].

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Tabulary Summary.Criterion Description

Time Not satisfied - or this criterion could notbe derived from the dscription

Location Partially satisfied, because the location isclassified into three categories

Analog-Digital Only digitalConcentration Partially satisfied as this criterion is de-

rived from the locationKnowledge SatisfiedMotivation Not satisfied

5.3 Ontology-based framework

Idea. The main idea behind this technology is the filteringof a mass of information and reducing it to a small subset ofthe whole information which still fits into the user’s needs.The technology provides an ontology for a given topic (e.g.,for digital cameras) with all available subtopics and infor-mation about the subtopics (including all terms). The on-tology is built up according to rules similar to UML (e.g.,a camera consists of a lens, a memory card and a zoominginterface, etc.). According to these rules topics are chosenor not in a search query. When providing a search query, asmall subset is selected according to the rules. This subsetis a lightweight ontology. Then this ontology is comparedagainst the learner profile, this means this lightweight ontol-ogy is then filtered furthermore to fit into the profile. Lastly,the information is displayed to the user and adapted to thespecificity of the user’s mobile device.[3]

Realization. For the ontology a knowledge base has to becreated first, so users can send queries. When a query arises,a set of rules is fired and the result of this firing is given forfurther processing. According to this smaller ontology, thisresult is furthermore filtered according to the user’s profile.At the end a search agent takes the target ontology, createssmaller learning objects of the topic terms or found terms ofthe ontology and seeks for information in a learning objectsrepository. This repository can be local or the search agentcan make use of the internet to find appropriate informa-tion.[3]

Tabulary Summary.Criterion Description

Time SatisfiedLocation Not satisfied - or not mentioned in descrip-

tionAnalog-Digital Only digitalConcentration Not satisfied

Knowledge Satisfied due to given learner profileMotivation Not satisfied

5.4 Supporting foreigner learning English

Idea. This system was designed to support foreigners tolearn English to prepare for tests, for example, the Test OfEnglish as Foreign Language (TOEFL). The basic idea be-hind this system is to decompose all learning tasks for a

language into many little subtasks. These subtasks are fur-thermore grouped under certain language specific areas (e.g.,grammar topics, slang, pronunciation, etc.). Afterwards, alltasks are ordered according to a difficulty level. Becausethe learner should be able to learn in all possible situations,the system also detects his environmental context to adaptthe information and the tests which are delivered to the user.All in all, the system tries to teach a user English by sensingthe context of the user and by adapting information for test-ing according to the user’s knowledge and the technologicalabilities of the user’s mobile device.[24]

Realization. The whole system is built up of five compo-nents. The first one is the context detection layer. Themain goal is to extract information from the user’s mobiledevice to determine the context. The next component is thedatabase layer. This layer consists of the content database,the learner’s profile and the context data. The contentdatabase holds all information for providing necessary in-formation to the user. This database is structured into atree. Every node stays for a certain topic which has to besolved by the learner. A node can also have subnodes whichthen are subtopics of the current topic. These subtopicscover all relevant information of the parent topic for thelearner. The context model determines the concentrationlevel, the knowledge of the user, the interval of time and thelocation of the learner. The location and all other issues arescored by a point system. The points are then summed up.The higher the points, the higher the possible learning effi-ciency and ability of the learner (compared to the contextof course). Finally, the learner’s profile is created from thecontext information. Based on the learner’s profile the rulesand questions for a certain task are chosen and deliveredto the user via an adaptive engine. The engine choses anadequate representation of the data. This representation isfitted to the mobile device of the user.[24]

Tabulary Summary.Criterion Description

Time SatisfiedLocation Satisfied

Analog-Digital Only digitalConcentration Satisfied

Knowledge SatisfiedMotivation Satisfied (can partially be extracted by the

context)

5.5 DiscussionAs one can see all approaches have one in common: thecontext of the user. But the information which can bederived by the context are used differently. Also the de-rived information is not the same. MARS and the for-eigner English language support approaches are in the areaof context-awareness the best examples of how to applycontext-awareness to user’s need. The context is used tofilter, sample and provide information to the user adaptedto the device the user is carrying. MARS takes a lot of con-textual information like the user’s environment, his positionand his knowledge to determine which learning material hasto be provided to the user. Another very good advantage is

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the fact, that everything is done via augmented reality. Allinformation can be displayed through the google and thusinformation can be overlayed over the reality. But a disad-vantage is that the user has to use this google. It’s not a realsoftware application and thus at the moment not every useris able to use this. Although it is a kind of mobile learning,it is not possible to use it on a smart phone. Furthermore,the only way for the user to interact with the system is viaspeech recognition. And at this moment the recognition ofspeech is not as satisfactory as it is needed to interpret usercommands correctly. The next system, which is used to sup-port foreigner learning English, has the advantage that it di-vides the learning material into several categories of differentdifficulties. Furthermore, the learning material is well struc-tured into smaller pieces which cover one topic. This canbe used to adapt the learning material for the user depend-ing to his knowledge and additionally to his concentrationlevel. The system asks the user to classify his concentrationlevel. Additionally to this the concentration level is also de-termined by the location of the user. E.g., a busstop or acafe etc.. Also the representation of the delivered materialis adapted to the mobile phone. But not all contextual in-formation is completely derived by the phone. As alreadymentioned the user has to classify his concentration levelhimself. This classification may not always be correct andthus the delivered information may be to complicated or notadapted correctly for the user. The ontology-based frame-work is an interessting approach to mobile learning, as anontology is formed for a certain topic (e.g., camera). Forthis ontology all subtopics and terms are stated and relatedtogether via rules. Then depending on the user’s needs theterms and subtopics are filtered out based on the links be-tween the terms. Finally concrete information is seeked ina database or the internet with search buddies. But a prob-lem in the description of the system was, that it was notclearly stated out, how the user is learning. Only the ap-proach of using ontologies and displaying the informationthe user needs was discussed. The context in this approachis the main topic or the main terms the user wants to know.Finally the last system which was descripted, is an approachfor providing context-aware learning services. The contextof the user is determined by the user himself. The userchooses between three types of environment. This kind ofcontext detection is poor, as for a given environment typethere can be several other criteria for subdividing the cat-egorization. Furthermore, when the context is detected alllearning services which fit into this context are enlisted andcan be used. Also in this system it is difficult to understandhow it works in detail as the description is only provided ona superficial level.

An overview of all advantages and disadvantages is providedin Table 2 to contrast all approaches.

As we have seen many researchers talk about location whentalking about integrating the context. Many approachesconcentrate on a user’s current location as only context in-formation. Because of that this research field grew and be-come quite precise and widespread. Additionally, it is alsoeasy to integrate in existing applications what promotes itsusage.

Now that this single context information works adequately,research moves further to other aspects of context. As wehave also seen in section 5, nowadays approaches also con-centrate on other context information. These are usuallyinformation dealing with the user’s extrinsic state and usedtechnologies like analog-digital.In the future the concentration of researchers will be onthe user’s intrinsic state [33]. The information which isextracted here contributes highly on the learning success.Just if the knowledge level is known, suitable material canbe provided. Equally, the user’s concentration and motiva-tion decides about deep learning.The problem is that the intrinsic state is not that easy todetect and to interpret like the extrinsic state and used tech-nologies. But nevertheless there are attempts to measure it.In [36] Yuan-Kai Wang talks about sensors to catch facialexpressions and eye gaze shift and about algorithms to an-alyze and interpret the data. But no further informationis given how to realize it. It is the future work of this re-search area to concentrate on methods to integrate contextinformation gathered of the user’s intrinsic state.

6. FUTURE WORKIn this section we will have a short outlook to see in whichdirection the trend in this research area goes.As we have seen in previous sections many researchers talkabout location when talking about integrating the context.Many approaches concentrate on a user’s current locationas only context information. Because of that this researchfield grew and become quite precise and widespread. Addi-tionally, it is also easy to integrate in existing applicationswhat promotes its usage.Now that this single context information works adequately,research moves further to other aspects of context. As wehave also seen in section 5, nowadays approaches also con-centrate on other context information. These are usuallyinformation dealing with the user’s extrinsic state and usedtechnologies like analog-digital.In the future the concentration of researchers will be onthe user’s intrinsic state [33]. The information which isextracted here contributes highly on the learning success.Just if the knowledge level is known, suitable material canbe provided. Equally, the user’s concentration and motiva-tion decides about deep learning.The problem is that the intrinsic state is not that easy todetect and to interpret like the extrinsic state and used tech-nologies. But nevertheless there are attempts to measure it.In [36] Yuan-Kai Wang talks about sensors to catch facialexpressions and eye gaze shift and about algorithms to an-alyze and interpret the data. But no further informationis given how to realize it. It is the future work of this re-search area to concentrate on methods to integrate contextinformation gathered of the user’s intrinsic state.

7. CONCLUSIONIn this paper, firstly, we defined mobile learning and dis-cussed characteristics of it. Moreover we had a look at thecurrent trend of used mobile devices, the technologies theyoffer, and their advantages and disadvantages to improvelearning. Afterwards, we introduced learning theories onwhich mobile learning, especially mobile learning in context,base on. Which aspects of the main learning theories likeCognitivism, Constructivism and Behaviorism has been used

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Approach Advantages Disadvantages

MARS

• Augmented Re-ality

• Life learning

• Informationdisplayed di-rectly in usersview

• Google isneeded

• Speech recogni-tion only wayfor user input

Providingcontext-awarelearningservices

• Dynamicchange ofdelivered infor-mation

• Learning ser-vices depicteddepending oncontext

• Poor detectionand categoriza-tion of context

• Usage of sys-tem not clearlystated

Ontology-based frame-work

• Amount of in-formation is re-duced to userneeds

• Informationare concretizedbased on gener-alized database

• Search agentseeking forinformationthroughoutthe web or arepository

• The process oflearning is notclearly handled

System forsupportingforeignerlearningEnglish

• Ranking of con-text of the user

• Structuring oflearning mate-rial

• Representationadapted tomobile device

• Context isonly semi-automaticallydetected

Table 2: Comparison of the approaches

and which advantages this contains have been discussed indetail.Since learning contains highly context-sensitive activities [36],we put great emphasis on this topic. What is context, whichkind of information belongs to it, and how can this in-formation be gathered have been the main aspects whichhave been considered here. When analyzing the benefits ofthe integration of the context into the learning process, oneclear result was ” to provide the appropriate support for thelearner, it is important to be able to establish a learner’scontext so that appropriate and contextualized support canbe provided for the learner” [28].In section 5 three approaches have been introduced. Theirkey idea and the way of realization have been shown. Addi-tionally, as it is most important for this paper, each approachhas been examined which context information they includeto get a precise picture of the user’s current situation.All in all, there is much research on mobile learning and es-pecially on integrating the user’s context into the learningprocess. But most of the research concentrate on the user’senvironment and the technologies he is using. Researchersare aware of the importance of knowing the user’s intrinsicstate, still there is just a few development in this area.

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8. GONNASEEYA!8.1 IdeaGonnaSeeYa! is an app for Android OS which should beused as a learning app for tourists. Users should get an im-pression of the city and learn about places which lay on theroute of a tour. Depending on the place, there are differentmedia which are offered for the user. These media shall helpthe user in enhancing his knowledge about the given place.As a self-control the user can check his knowledge with anoverall test about the city. This test also is used to deter-mine the knowledge of the user. In the following sectionsthe architecture and the development process of the app isexplained.

8.2 ArchitectureThe architecture is divided into a client side and a serverside, whereas the client side is the app itself and the serverside is comprised of several modules. An overall picture ofthe architecture is given in the appendix. In the follow-ing the components of the overall architecture are explainedmore in detail:

a The mobile device takes all context information andretrieves then learning data from the server via tokens.Depending on the data of the tokens the mobile devicechooses then which media should be downloaded anddisplayed.

b The communication is done via tokens. Every tokenhas a certain information request or response. Thereare five main tokens, which are explained later.

c The server is a normal webserver with a PHP modulerunning on it. It contains a PHP-API which allows themobile device to retrieve information from the server.

d The token interpreter moudle receives all tokens andprocesses the information. Then it calls, for a specifictoken, its corresponding token module which then con-tinues processing the received information in detail.

e The token modules processes the information deliveredby a request in detail.

f The access to the database is decoupled, so that alother modules does not have direct access to the database.his database access layer guarantees, that the type ofthe database does not have to be bound to a specifictechnlogy (e.g. SQL). But for performance reasons aSQL database was chosen.

Tokens. For exchange of information the mobile device andthe server communicate via tokens. A token specifies whattype of computation should be done on the server side.There are four main tokens used by the server:

• Media requirement token (MRT): This token specifieswhich media is available for a given latitude and lon-gitude. It returns all types of media, their file sizesand their extensions, so that the mobile device is able

to decide which media should be downloaded and dis-played. Example media can be video or audio files,text files or even files for displaying tasks to supportthe learning effect for users.

• Authentication token (AT): This token is used for loginand registration of users. Furthermore, it checks if agiven user is in the database.

• Data request token (DRT): This token tells the server,that the mobile device wants to download the contentof a media file. The response is the concrete contentof the media.

• Search request token (SRT): This token was designedto faciliate search tasks e.g. for finding the next restau-rant or other places.

• Computation request token (CRT): This token tells theserver to start a computation. Computations whichare too complex or too time consuming for the mobiledevice are transfered to the server side so that the mo-bile device can fully concentrate on the user input andthe more app specific issues.

It must be kept in mind, that latitude and longitude are notvery precise for every device. For this reason for every to-ken request the mobile device must also specify the distancetolerance. The distance tolerance tells the server the epsilonvalue of the proximity for a given longitude and latitude.Furthermore, all responses are returned as JSON strings tofaciliate the interpretation of the response as there are al-ready available libraries for reading and interpreting JSONstrings.

Database. For the database the approach of a data accessobject is used. A general interface is designed which specifieswhat has to be retrieved from the database. With this in-terface now arbitrary database accessors, which implementthis interface, can be used. For this app a SQL accessorwas implemented, but it is not mandatory to use this. Forexample a database in XML could also be created and used,but for performance reasons of course a SQL database waschosen. The response of the database is then formatted toJSON in higher layers.

Used context information. As the target group of the apphas a wide age spectrum and the app can be used everyday of the year, the following context information is used toadapt the behavior of the app:

• GPS

• Age of user

• Time

• Season

• Day of the week

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GPS is mandatory, as the user has to be navigated throughthe city. The age of the user can be used e.g. to present abetter choice of restaurats in the city which fit best to theuser’s age. The current time can also be used to check whichgastronomical establishement is open at the current momentof usage. The season specifies what type of gastronomicalestablishement is open and which one fits best. Finally, theday of the week can be used to draw attention to the userabout certain events which take place in the city weekly.

Mobile device side. On the moble device side the graph-ical user interface play a very important role. As the sizeof the screen is limited it is very important to design an in-terface a suitable GUI which can intuitively be used by thetarget group. For this first a prototype has to be developedin order to check if the idea is applicable on the target deviceand usable for the target group. For the app a prototype forall activities of the app was created and was attached in theappendix.

8.3 Appendix

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Figure

3:Overa

llarchitectu

reofGonnaSeeYa-A

pp

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