20101108 - Trifonova, ..Hoarding Content in Mobile Learning..

Trifonova, A. (2006). Toward Hoarding Content in M-Learning Context. University of Trento, Italy. My Interest: 1) Hoarding the learning content. 2) Offline access of learning content. 3) Mobile learning. 4) MobileELDIT. 5) Developing the prototype of mobile learning. Action: To read the entire Dissertation in future. Introduction M-learning is a very new but rapidly expanding domain. Provoked by the fast advances of mobile technologies different applications and systems are developed continuously. Many new re-search topics are emerging in various areas, including technological issues, pedagogical and methodological ones, problems related to content, context, user interfaces, adaptation, etc. Research Goal The main goal of this thesis is to address the hoarding problem, which has been previously weakly explored but is a particularly important issue in the mobile domain and whose solution should be included in every system with a large quantity of data. Problem For e-learning systems which are being converted/adapted for accessing the content through mobile devices it is generally the case – the learning material is often of big size, especially compared with the locally available memory of the device. Comments: I concur with Anna Trifonova. For mobile learning to be truly ubiquitous, it is important for learning content to be accessed online as well as offline. Hence, hoarding learning content and pre-downloading learning content is crucial to enable offline, ubiquitous learning. Solution Hoarding is the process of automatically selecting learning content which has to be prepared and pre-fetched on the mobile device's local memory for the following offline-session. Hoarding is highly needed in the m-learning context for two main reasons. On the first place is the demand to support what is called "any-time, any-place" education. This means that on the mobile device (e.g. a PDA – the kind of device often used in m-learning), which might be often disconnected from the Internet, the needed learning content should be available locally for allowing access during the offline periods. On the second place comes the desire to hide from the student the technologies that lie behind this ubiquitous learning. We would like to free the user from tedious operations of manual preparation and planning his/her next study session. Moreover often we cannot even count on the student's own judgment for his/her knowledge and future needs. In order to attack the main problem the full context around the hoarding had to be constructed and is described throughout the thesis. In this sense the thesis appears to be multidisciplinary as it treats also important questions about the construction and evaluation of an m-learning application. Methodology We have started with the choice of a concrete area for experimenting in mobile learning and hoarding. The chosen field was language learning and a prototype of a mobile language learning system was built. We discuss the general and concrete approaches to develop and build it. Motivations for our choices are given on every step. We describe in details the hoarding problem and the strategy to solve it with the goal to provide an efficient hoarding solution. Experimental results are presented, together with the practical experiences gathered from the interactions with the users. Finally suggestions for improvements and further research issues are given. 2. MOBILE LEARNING STATE OF THE ART 2.1. DEFINING M-LEARNING 2.2. M-LEARNING RESEARCH 2.2.1 Infrastructural Research 2.2.2 Accessing Content 2.2.3 Communicating and Interacting with People 2.3. GUIDELINES FOR M-LEARNING APPLICATIONS 3. THE RESEARCH CONTEXT 3.1. SURVEY ON THE READINESS FOR MOBILE LEARNING 3.1.1 General Information 3.1.2 Availability of devices, their usage and attitude to prices 3.1.3 Ways of usage and attitude to e-learning platforms 3.1.4 What about m-learning? 3.1.5 Deductions 3.1.6 Related Work 3.1.7 Conclusions 3.2. GENERAL MOBILE LEARNING ARCHITECTURE 3.2.1 E-learning 3.2.2 M-Learning 3.2.3 The Architecture 3.2.4 Related Work 3.3. MOBILE ELDIT - A REAL-WORLD SYSTEM 3.3.1 What? /Description of ELDIT/ 3.3.2 Why? /Motivations for the Mobile ELDIT/ 3.3.3 How? /Details on Mobile ELDIT development/ 4. HOARDING: OUTLINE OF THE SOLUTION 4.1. MEASURING THE QUALITY 4.2. DEFINITION OF SESSION IN THE MOBILE LEARNING CONTEXT 4.3. HOARDING ON THE FIRST ACCESS TO THE SYSTEM 4.4. PREDICT THE STARTING POINT 4.5. GENERATE 'CANDIDATE' SET 4.6. PRUNING 4.7. PRIORITIZING 4.8. USER MODELING 5. CONTEXTUALIZATION OF THE SOLUTION AND EXPERIMENTAL OUTCOMES 5.1. METHODOLOGY FOR LOOKING AT THE OUTCOMES 5.2. AUTOMATIC EXTRACTION OF KNOWLEDGE ABOUT THE USER 5.2.1 Approach 1: using the online desktop system 5.2.2 Approach 2: using the mobile system 5.3. HOARDING RESULTS 5.3.1 One User Hoarding 5.3.2 User behaviour observations 5.3.3 Hoarding with 'Critical Set' 5.3.4 Combined Hoarding 5.3.5 Association Rules 5.4. OTHER OUTCOMES FROM THE MOBILE LEARNING SYSTEM 5.4.1 Positive Outcomes 5.4.2 Problems Found

20101009 - Niazi's Dissertation - part 5 - proposed Mobile Learning Platform

Reading & blogging this while inside the aircraft flying BTU-KUL…evening of Sat 9 Oct 2010. Chapter 4 Proposed Platform 4.1 Goals and Platform Specifications Our approach is the integration of formal education into our daily lives. In other words, we want to design and develop a mobile learning platform which supports both learners and educators. Using this platform, learners are able to manage their courses, take quizzes, access course materials, labs, assignments and view their scores, messages and notifications from any target device. In addition, our platform provides tools for educators to create their educational materials for both PC platform and mobile device platforms. Technically, we provide some strategies for device-independent delivery of the educational materials. Target devices in our platform include cell phones, smart phones, PDAs, tablet PCs, laptops and PCs. Comments: Plus point is the mobile learning platform is meant for a variety of mobile devices. This is important so that learners using mobile phones to computers Basically, we consider our platform with the following characteristics: • Creating educational materials We believe that creating educational materials including course materials, quizzes, and labs should be done once by the instructor. Then the same content should be transformed into the various target devices in the compatible formats just by clicking a button. • Delivery of materials Our platform supports both offline and online learning. This means our platform is able to deliver educational materials online as well as offline. In the case of online learning, delivery of materials to mobile devices is done in XML format which is a standard and universal data format. On the other hand, for offline learning there are some challenges, including the variety of cell phones. Students have different brands of cell phones with different capabilities and constraints. Our platform is able to support this variety. In other word, our platform provides device-independent delivery. In both cases of offline and online learning, it is necessary to use the minimum bandwidth as well as the minimum memory usage that consequently leads to less power consumption. Hence, in design and development of our platform, we have considered these three factors to keep them at a minimum. • Tracking and evaluating students' progress This part provides some facilities to give feedback to student's works such as displaying correct answers when a student submits his/her quiz, analyzing, grading the quiz, and sending the result back to the instructor (optional). Also, students are able to try a quiz "n" time depending on the trial number defined by an instructor. • Learning Management System (LMS) LMS is a Web-based learning management system which allows all educators to access, assemble, package and redistribute educational materials including content, labs information, quizzes and assignments. Also, it enables students to manage their courses, access the content and educational materials generated by instructors. In addition, a mobile version of LMS (mobiLMS) available for online learning is supported in our platform. This mobiLMS which is deployed on mobile phone devices enables learners to connect to our server and uses educational materials online. • Making educational materials knowledge-based It offers instructors the opportunity to share their quizzes with other instructors. When instructors create their learning materials like quizzes, they have a chance to make their quizzes knowledge-based. If they take this opportunity; their quizzes will be saved in a knowledge-based database. This capability gives other instructors the chance to create their quizzes from this knowledge-based database randomly with respect to their keywords and topics searched, although they still have a chance to provide their quizzes from scratch. • Supporting Learning Metadata All educational materials are saved as XML files managed by the file management. Also, the platform has the capability to keep track of courses, content materials, labs, assignments, quizzes and their relationships for each instructor as metadata in the XML format. • Content distribution capability This capability offers instructors the ability to create their educational materials like lecture notes, labs, quizzes once, then generate and distribute them in different formats including XML, HTML, XHTML, WML, J2ME Midlet for Java-enabled devices and Blackberry API code for Blackberry devices. Comments: The turbulence has been really bad. I am feeling slightly dizzy and groggy. Pilot is descending the aircraft searching for better flying condition. I suppose we are flying over South China Sea. …Now getting better. Thank God. Praise the Lord. 4.2 Proposed Platform Architecture We divide our proposed architecture into two levels (Mobile Learning Management System and Electronic Learning Management System) and 4 different layers (storage layer, management layer, logic layer and presentation layer). Figure 4.1 shows the architecture of our proposed platform: mobiLMS is a platform to support online mobile learning. Its responsibility is to manage courses, discover educational materials for each course, display scores, messages, notifications, grade quizzes, and render educational materials adaptive to mobile devices. Technically, we summarize the mobiLMS into the following units: • Mobile Learning Content Management: it is used to manage courses. • Mobile Learning Content Presentation: it is responsible for presenting educational materials adaptive to mobile devices. • Context Discovery: its responsibility is to discover the context including the available courses, lectures and quizzes. • Coursework Analysis: it analyzes coursework, assigns grades, displays correct answers, and sends results to instructors. eLMS is a Web-based Learning Management System categorized into the 4 following layers: • Presentation Layer: this layer is responsible for converting generated learning materials to the Web browser adaptive form. In this layer, we use stylesheet, XSL, to convert these materials in the XML format (generated in the logic layer) to the HTML. • Logic Layer: this layer mostly provides and performs functions to generate, compile, pre-verify, pack and deliver educational materials in different formats including XML, WML, XHTML, J2ME Midlet and Blackberry API code. Technically, the functions in this layer are available to instructors. The folio wings describe these functions: o Content Generator: it has the responsibility for converting lectures provided in Microsoft Power Point into the WML, XHTML, XML, J2ME Midlet, and Blackberry API compatible source code. o Quiz Generator: it has the responsibility for converting quiz instructor-specified inputs into the WML, XHTML, XML, J2ME Midlet, and Blackberry API compatible source code. o Compile Engine: it has the responsibility for compiling Java source codes to Java bytecode class files. Our architecture supports two kinds of compiler; J2ME compiler and Blackberry API compiler. o Obfuscator function: it improves the size, performance and security of J2ME mobile applications. o Pre-verification function: in order to enable J2ME bytecode class files to be run on mobile phone devices, they should be valid bytecodes. For this purpose, pre-verification function must be applied. Preverification function converts J2ME bytecodes to valid bytecodes. This function only acts on J2ME CLDC application bytecodes. o Packing function: in order the generated codes be able to run on mobile phone devices, it is necessary to pack bytecodes and the relevant information to a special format such as jar or cod files. o Delivery function: as mentioned earlier, it is responsible for delivering educational materials in different formats on mobile devices. o Semantic Search: it is a tool to query the Knowledge-Based quiz database. It is responsible for searching and finding the relevant quizzes which are matched with entered user's keywords. • Management Layer: management layer is responsible for managing courses, users, and files. This layer provides and performs functions available to both educators and learners. The following shows a brief description of each function: o Authorization: it is used to authenticate and authorize users, o Course Management: it is used to mange courses for both instructors and learners. It enables students and teachers to add, delete and edit courses, o File Management: it provides facility to manage copy and delete generated files into the user directories and the relevant subdirectories. o Learner Tracking: instructors are able to keep track of students' progress by receiving students' coursework feedback and quiz result through email or SMS. • Storage Layer: our platform includes tables for user profiles, students, instructors, courses and other relevant information. In addition, it includes the other table for knowledge-based quizzes. There are other repository formats other than tables like XML files and metadata as well. Metadata are used to keep track of instructor's activity. The following explains a brief description of each repository: o Knowledge-bases Database explained earlier. o User Profiles hold information about learners' profiles, instructors' profiles, courses, instructors' courses, and students' courses, o Metadata in an XML data format, keep track of quizzes, courses and their relationships for each instructor. They are stored in the instructor's directory managed by the file management, o Educational materials and quizzes are stored in XML data formats. source: Design and implementation of a deviceindependent platform for mobile learning by Niazi, Razieh, M.Sc., University of Guelph (Canada), 2008

20101008 - Niazi's Dissertation - part 4 - Literature Review

Read this while watching Transporter 3 and League of Extraordinary Gentlemen ...at Bintulu...evening of Thu 8/10/2010. 2.1.2 MLE MLE (Mobile Learning Engine) [20] enables students to use cell phones as a medium for learning. It is used in combination with a learning-platform (MLP) which is an Internet-based server. MLP is a learning management system (LMS) in the e-learning field which hosts the available learning objects and offers several functions. MLE communicates with the learning platform over HTTP and XML. In other words, MLE and MLP communicate together over HTTP and XML. Comments: I read about MLE somewhere….can't remember the details. 1. It uses a smart phone (a mixture between a mobile phone and a personal digital assistance) as a device of choice. MLE does not support a broad range of mobile devices. 2. It is possible to reuse existing learning management systems to support elearning. 3. Users are connected to the server (online) and download the learning objects from the server. If the learning objects have been downloaded before, they can be used without a new connection to the server (offline). 4. The supported data format is XML. Learning objects are written in XML format making it possible to present many kinds of learning content. It needs, however, the author of learning objects to spend time planning and designing these objects, otherwise the result will be a vast frustration to students. In fact, the authors of the learning objects are responsible for quality of their works. They determine the success and the acceptance of the MLE [20]. 2.1.3 Mobile ELDIT Mobile Eldit (m-Eldit) [21] is a system under development at the University of Trento, Italy. This is a mobile version of an existing online language learning platform that can be accessed from mobile devices like PDAs and Pocket PCs. In the Web-based version of this application, there are two types of data: a searchable words dictionary in German and Italian, plus a set of text in both languages. The texts have specially been designed to prepare learners for the examination in bilingual capability. The user can search for a particular word in the dictionary or browse the texts to study. In the mobile version, however, searching is not supported, because the raw data of m-Eldit is beyond the capacity of available memory on mobile devices. Technically, data are in XML file format. The Web server transforms data from XML into HTML and Java-Script. The learner then can browse the HTML files by clicking on hyperlinks. Comments: M-Eldit has been mentioned in at least a few research papers and/or journal articles. Heard about M-Eldit previously. 1. It uses some particular mobile devices like PDAs and Pocket PCs. It does not support a broad range of mobile devices such as cell phones or smart phones. 2. It supports e-learning. In fact, if mobile devices used are laptops, the hardware and software characteristics are the same as e-learning. 3. M-Eldit supports online access to educational materials. It can connect to the Internet through GPRS, WAP, WiFi and browse HTML files. It also supports offline accessibility. For this purpose, m-Eldit uses caching technique and in the case, when the data is bigger than the device available memory, it uses Hoarding technique. Hoarding technique is a technique for automating selection and caching of the data needed by the user in offline periods. 4. This system only supports HTML files plus Java Script. This format of file is not supported by all mobile devices. In Mobile Eldit, in order to support content adaptation, context discovery should be done. For this purpose, m-Eldit adds contextual information including hardware and software limitations (such as screen size in pixel, color resolution, CPU, supported language, operating system and etc) to the HTTP request message. In the proposed solution, however, it is not clear, given the wide varieties of mobile devices, how the contextual information will be provided. 2.1.4 MOBILE MOBILE [34] is a MObile-Based Interactive Learning Environment which aids elementary school English Learning. This system consists of a server and a set of mobile learning tools which supports in or outdoor learning activities. It is composed of the following components: • MMS (Mobile Management System): it involves content management, course management, dictionaries, and learning records. • MAS (Mobile Assessment System): it supports online assessments. • MIS (Mobile Instruction System): it provides services for browsing material, bulletin board, learning community, chat, quiz, notebook, and FAQ. • MLDB (Mobile Learning Database): students' learning statuses and records are stored in this database. • LCMS (Learning Content Management System): it handles storing and managing the digitized teaching and assessment materials. Comments: This sounds like a comprehensive Mobile LMS….with extensive features. In this system, each student uses a PDA to send and receive learning materials from the mobile learning system. In addition, teachers are able to download the teaching and assessments materials from LCMS through Internet to the MLDB while conducting indoor or outdoor activities. 1. It supports mobile devices including PDAs and notebooks. It does not support a broad range of mobile devices. 2. No information has been provided to support e-learning. 3. It supports online as well as offline access to educational materials. In fact, educational materials can be downloaded to be used for offline learning. 4. It supports HTML-based educational materials for diverse learning activities. In this system, the teacher has access to a notebook and each student uses a PDA that is provided by the school. In fact, MOBILE does not support a wide variety of mobile devices, and thus does not face many of the obstacles described in Section 1.4. 2.1.6 MobiLP MobiLP (Mobile Learning Platform) [22] is a Web-based learning system which supports access from both mobile and non-mobile devices. It aims to provide educational materials and communication services to teachers and students any time, any where. Totally, MobiLP functions are classified into three groups: • User functions available to students are designed for mobile devices access. They include the display of Web materials specified by the teachers, online chat rooms and online quiz systems. • Teacher functions include input of teacher-specified Web materials, online quiz management, online chat and user profile management. These functions can be accessed either by mobile devices or non-mobile devices or both. • Administrator functions include general system management functions such as access control and user account management. All of these functions are to be accessed by non-mobile devices. This system does not support offline access to educational materials and quizzes. In addition, it supports browser-based technology and the supported data format is XML. No information has been provided on customization process of XML data on the supported browsers. 2.1.5 An Adaptive Mobile Learning System In [35] an adaptive mobile learning system is proposed. It suggests an architecture and prototype quiz system based on XML/XSLT technologies. The prototype consists of five dimensions as follows: • The content dimension: it represents the actual content containing course modules, content and multimedia representation of the content (audio, video, animation and so on) sub-dimension. • The user model dimension: it contains two sub-dimensions including learning model and user preference. Learning model dimension includes attributes such as module completed, weight, score and time taken. User preference contains attributes like learning style and preferred difficulty level. • The device dimension: it includes attributes such as the device types, audio, and video capabilities as well as memory, bandwidth, and operation platform. • The connectivity dimension: it includes four operating sub-dimensions as follows: o A real-time online mode: some attributes like throughput determine representation of text or multimedia. o Pre-fetching capability: it specifies how much the pre-fetching depth should be? It completely depends on the device capability, network reliability and connection type. o Offline synchronization mode o Channel mode: it represents the actual mode of the connection between the user and the server. For instance, a user can experience a longer delay in a satellite connection than a cable connection. • The coordination dimension: it represents the logic and algorithm subdimension of the application. In the development of the quiz system, the multi-dimension framework has been applied. This system is capable of adapting to the device and the user profiles. It works on both PC and mobile Platforms. 1. It supports a variety of mobile devices including hand phones, PDAs and Pocket PCs. 2. Probably supports e-learning. 3. It is a dynamic quiz system which does not support offline learning. The current prototype has been tested only for PC users, PDA (iPaq) users, and mobile phone users with Openwave browser. Comments: Whose does this Adaptive Mobile Learning System belong to? Niazi's? source: Design and implementation of a deviceindependent platform for mobile learning by Niazi, Razieh, M.Sc., University of Guelph (Canada), 2008

20101007 - Niazi's Dissertation - part 3 - Literature Review

Chapter 2 Background Just a bit of reading up while watching Star Movies @ Bintulu…evening of Thu 7 Oct 2010. 2.1 Related Work Due to the variety of current mobile learning systems, we consider them from two perspectives: first, what capabilities and services they support, and second, how they address the issues discussed in Section 1.4. According to the capabilities and services, we evaluate them using some of the indicators specified in [18], among others, as follows: 1. The supported kind of mobile devices: Quinn states that m-learaing solutions must work for a broad range of devices, not only for a set of devices [23]. We adopt this specification. Thus, in this critic we specify what kind of mobile devices these systems support. For instance, some of the current m-learning systems work only in PDAs or Tablet PCs. 2. Support of e-learning: we consider them whether they support e-learning or not. 3. Availability of content: whether the educational materials are always available or not. In other words, whether they support online as well as offline access to content materials or they support only one method. 4. The type of data they support: For instance, some current systems only support flash type. Comments: He reviewed the applications in 4 aspects: supported mobile devices, support for e-learning, availability of content, and type of data supported. 2.1.1 WELCOME WELCOME (Wireless E-Learning and Communication Environment) [17] is a project at the University of Regensburg which aims to support both students and teachers by providing services that facilitate teaching, learning and education- related administrative tasks. This system has been built based on existing experiences in the field of e-learning from VUR (Virtual University Regensburg). VUR is the Internet-based e-learning, widely accepted and used in the university. It is also the fundamental software architecture for all VUR wireless learning and administrative services. Selected features of this platform such as news, distribution of learning materials and personalization are available for mobile devices. 1. The supported kind of mobile devices: Basically, PDAs are selected as a device of choice. In attempt to remain platform independent, PDFs, RealVideo streams and Flash animations are used. These formats are often not fully supported by all mobile devices or supported with limitations. 2. WELCOME does not support e-learning specifications and standards [18]. 3. It is possible to have both online and offline access to Audios and Videos just on PDAs. In fact, it uses AvantGo, a Web page / file synchronization service for PDAs and smart phones. AvantGo [19] consists of browser client software running on the PDA, a synchronization server, and (optionally) an Internet-connected PC to transfer Web pages into the PDA. Using AvantGo, users are able to synchronize. In other words, Web pages, information and data can be stored on their device during synchronization and, later stored pages can be read using the built-in Web browser without reconnecting to the Internet (offline). 4. The supported information types are PDFs, Audio, Video, Flash animations and WML. The WML content format is supported by the WAP protocol. The mobile learning content materials are mostly generated by adapting third-party Web sites such as the Cafeteria page and so on. The content are as HTML which can be rendered on PC without any problem. However, on the mobile devices they must be displayed in an adapted form. For this purpose, WELCOME converts and compiles the content. The basic procedure of translating Web content for mobile devices begins by parsing several HTML pages at regular intervals using PERL programs and extracting the information contained there in. Then the extracted data is stored in a relational database. On the other hand, mobile users request WML pages which are dynamically filled with the data stored in the database. The downside is that content adaptation requires a long process to parse HTML page, store in the database, restore data from database and then make WML page. In addition, in this way the quality of data should be evaluated. The other problem is maintaining content in the database. Data are extracted from HTML Web pages: a complicated strategy is needed to keep up to date these data. source: Design and implementation of a deviceindependent platform for mobile learning by Niazi, Razieh, M.Sc., University of Guelph (Canada), 2008