Using knowledge engineering for Modeling Mobile Learning Systems

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Using Knowledge Engineering for

Modeling Mobile Learning Systems

Thèse

Mahmoud Mohanna

Doctorat en informatique

Philosophiae doctor (Ph.D.)

Québec, Canada

© Mahmoud Mohanna, 2015

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Résumé

En éducation, on constate un besoin de mettre à profit l’évolution continue des technologies de l'information et des communications pour développer de nouvelles applications. Ainsi, un nouveau type d'apprentissage à distance a été créé. Il s'agit de l'apprentissage mobile qui peut fournir aux apprenants l'autonomie d'apprentissage maximale. De plus, il offre aux autres acteurs du processus d'apprentissage, comme les enseignants et les gestionnaires, des méthodes plus souples d'enseignement et de gestion.

Malgré sa croissance rapide, il existe de nombreux problèmes qui doivent être résolus afin que cette forme d'apprentissage puisse prendre sa place dans les systèmes de formation utilisant la technologie. L'inconvénient majeur de l'apprentissage mobile est l'absence de standard ainsi que le manque de prise de conscience sur la façon dont il peut être bien intégré dans le processus d'apprentissage. Le défi le plus critique est la formulation d'un standard qui décrit le développement d'un système efficace d'apprentissage mobile et la définition précise de ses acteurs et de ses composants.

L'objectif principal de cette thèse était de formaliser un modèle global et générique pour l'apprentissage mobile afin de bien comprendre ses divers composants et aussi pour guider les chercheurs ultérieurs dans le domaine de l'apprentissage mobile. La méthodologie d'ingénierie des connaissances, CommonKADS, a été employée pour aider à réaliser les objectifs de recherche. La modélisation proposée consiste en trois étapes consécutives, contexte, concept et artefact, et est illustrée par une expérience réelle d'apprentissage mobile au niveau universitaire. Les résultats montrent comment appliquer les modèles proposés pour concevoir une application d’apprentissage mobile et permettent de vérifier la possibilité d’intégrer une telle application dans un processus d’apprentissage formel. Cette thèse fait le lien entre la description théorique d’applications d’apprentissage mobile et leur mise en œuvre. Chaque modèle proposé peut être considéré en soi comme un exemple. Leurs descriptions génériques peuvent servir de point de départ pour de plus amples recherches, pouvant facilement s’adapter aux futures évolutions des appareils mobiles.

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Abstract

In education, the need to get the maximum benefit from recent development of computer and telecommunications technologies arises. A new kind of distance education mode i.e. mobile learning has been emerged. Mobile learning can provide learners with the maximum learning autonomy. It can also provide the other players in the learning process such as instructors and learning administrators with more flexible teaching and managing methods.

Despite of the fact that m-learning is a fast growing technology, it faces many problems which have to be solved in order to allow it taking its rightful place in the field of technology-based learning. The main m-learning drawback is the absence of standard in addition to the lack of awareness about how it can be well integrated in the learning process. The most critical challenge facing us is the formulation of a standard describing how to develop an efficient m-learning system and how to define its actors and components precisely.

The principal objective of this dissertation is to formalize a generic comprehensive model for m-learning in order to understand the m-learning different components and also to guide subsequent researchers in the m-learning domain. CommonKADS knowledge engineering methodology is employed in order to help in realizing the research objectives. The proposed modeling process goes through three consecutive stages; context, concept, and artifact modeling. Afterwards, it is illustrated by a real m-learning experience at higher education level. Results show how to apply the proposed models in order to design an entire mobile learning system and to verify the possibility to integrate that system in a formal learning process. This dissertation constructs the link between the theoretic description of mobile learning and its implementation. Each model can be considered as a standalone reference. Furthermore, the generic description of the proposed models represent a good starting point for further research, and can also be adapted with future evolutions in mobile and telecommunication technologies.

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11.2 Variant Aspects ... 106 11.2.1 Structure ... 108 11.2.2 Process ... 109 11.2.3 People ... 110 11.2.3.1 Administrators ... 111 11.2.3.2 Education experts ... 111 11.2.3.3 Instructors ... 111 11.2.3.4 Technical staff ... 112 11.2.3.5 Learners... 112 11.2.4 Resources ... 113 11.2.4.1 Software resources ... 113

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11.2.4.2 Hardware resources ... 116

11.2.5 Knowledge ... 117

11.2.5.1 Learning material ... 117

11.2.5.2 Knowledge produced by learning process ... 118

11.2.5.3 Administrative documents ... 118

11.2.5.4 Learning regulations, rules, and obligations ... 118

11.2.5.5 Technical support documents and operation guides ... 118

11.2.5.6 Learners data and information ... 119

11.2.6 Culture and Power... 119

11.3 Process Breakdown ... 120

11.3.1 Learning process administration ... 122

11.3.2 Teaching ... 122

11.3.3 Development and implementation of learning application ... 123

11.3.4 Operation and system maintenance ... 124

11.3.5 Technical support and troubleshooting ... 124

11.4 Knowledge Assets ... 124

11.5 Checklist for Feasibility Decision Document ... 125

11.5.1 Business feasibility ... 130

11.5.2 Technical Feasibility ... 130

11.5.3 Project Feasibility ... 130

11.5.4 Proposed actions ... 131

Chapter 12 : Task Model ... 133

12.1 M-learning teaching task analysis ... 133

12.1.1 Adapt subject material to mobile environment ... 135

12.1.2 Present subject material ... 136

12.1.3 Communicate effectively with students ... 138

12.1.4 Encourage inter-students discussions and teamwork spirit ... 141

12.1.5 Assess students learning ... 143

12.2 Knowledge item worksheet ... 145

Chapter 13 : Agent Model ... 149

13.1 Learning expert ... 149

13.2 Instructor ... 150

13.3 M-learning application ... 150

Part III conclusion ... 153

Part IV : M-Learning Concept Modeling ... 155

Chapter 14 : Knowledge Model ... 159

14.1 Differences between databases and knowledge bases ... 159

14.2 Knowledge model components ... 160

14.3 Middle-in and middle-out approaches ... 162

14.4 Domain Knowledge ... 164

14.4.1 Domain schema ... 164

14.4.1.1 Concepts ... 164

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xi 14.4.1.3 Class Diagram ... 173 14.4.1.4 Rule Types ... 174 14.4.2 Knowledge base ... 177 14.5 Inference Knowledge ... 182 14.5.1 Inferences ... 183 14.5.2 Knowledge roles ... 183 14.5.3 Transfer functions ... 184 14.6 Task knowledge ... 185 14.6.1 Task templates ... 186

14.6.2 M-learning teaching reasoning tasks ... 187

14.6.2.1 M-learning course design ... 188

14.6.2.2 Subject material presentation ... 192

14.6.2.3 Learning assessment ... 196

Chapter 15 : Communication Model ... 201

15.1 Basic elements of m-learning communication model ... 201

15.2 Communication plan ... 202

15.2.1 Communication plan control... 204

15.3 Individual transactions ... 206

15.4 Information exchange specification ... 208

Part IV conclusion... 212

Part V : M-Learning Artifact Modeling ... 213

Chapter 16 : Design Model... 217

16.1 Design of system architecture ... 218

16.1.1 Decomposition of the system into subsystems ... 218

16.1.2 Description of control model ... 218

16.1.3 Decomposition of subsystems into software modules ... 219

16.2 Specification of software and hardware platforms ... 219

16.2.1 Knowledge representation ... 220

16.2.2 Interaction protocols ... 221

16.3 Detailed architecture specification ... 222

16.3.1 System controller ... 222

16.3.2 Tasks and task methods ... 222

16.3.3 Inferences and inference methods ... 223

16.3.4 Dynamic and static roles ... 223

16.3.5 Views ... 224

16.4 Detailed application design ... 224

Chapter 17 : M-Learning Experience ... 227

17.1 Mobile application design ... 228

17.1.1 Primary application design ... 228

17.1.2 RSS news feed technology ... 229

17.1.3 Final application design ... 230

17.2 Implementation and deployment ... 231

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17.4 Advantages of using RSS feed technology ... 234

17.5 Discussion and future work ... 235

Part V Conclusion ... 237

Chapter 18 : Discussion ... 239

18.1 Literature review and research contribution ... 239

18.2 Research methodology and outcome ... 241

18.3 Future work directives ... 243

Bibliography ... 245

Appendixes... 251

Appendix 1 : Mobile application screenshots ... 253

Appendix 2 : Mobile application survey questions and results ... 257

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List of Figures

Figure 1. Development timeline of computing, audio, and mobile technology ... 13

Figure 2. Scope of mobile learning ... 16

Figure 3. Various types and branches of e-learning ... 19

Figure 4. M-learning as a subset of both d-learning and e-learning ... 22

Figure 5. Terminology used by m-learning and e-learning ... 24

Figure 6. The three learning spaces ... 28

Figure 7. Cell phones shape and size evolutions ... 45

Figure 8. GSM network structure ... 50

Figure 9. Evolution path from 2G to 3G wireless networks ... 53

Figure 10. Market trends of wireless standards between 2009 and 2020 ... 54

Figure 11. Final version of TAM model ... 58

Figure 12. UTAUT model... 59

Figure 13. M-learning research model ... 60

Figure 14. M-learning education utilities ... 61

Figure 15. An m-learning framework model ... 63

Figure 16. ADL ISD framework for m-learning ... 64

Figure 17. Low cost mobile devices ... 66

Figure 18. Location aware system architecture ... 68

Figure 19. Location aware application block diagram ... 69

Figure 20. CommonKADS historical evolution timeline ... 92

Figure 21. Building blocks of methodological pyramid ... 93

Figure 22. CommonKADS model suite ... 96

Figure 23. M-learning organization chart ... 109

Figure 24. M-learning process specified through a UML activity diagram ... 110

Figure 25. M-learning teaching task breakdown and suggested actions ... 134

Figure 26. Course design data flow diagram ... 136

Figure 27. Course presentation data flow diagram ... 138

Figure 28. Instructor-students communications data flow diagram ... 140

Figure 29. Inter-students communications data flow diagram ... 142

Figure 30. Learning assessment data flow diagram ... 144

Figure 31. Middle-in and middle-out approaches ... 163

Figure 32. M-learning-course – Instructor binary relation ... 168

Figure 33. M-learning-course – M-learning-application binary relation ... 169

Figure 34. Learner - M-learning-course binary relation ... 170

Figure 35. M-learning-course – Assignment ... 171

Figure 36. Assignment – Workgroup binary relation ... 172

Figure 37. Workgroup – Learner binary relation ... 172

Figure 38. M-learning class diagram ... 173

Figure 39. enrollment-rules rule type ... 174

Figure 40. pass-the-course rule type ... 175

Figure 41. membership-rules rule type ... 176

Figure 42. Knowledge base example of m-learning domain schema ... 178

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Figure 44. Dynamic role symbol ... 183

Figure 45. Static role symbol ... 184

Figure 46. Transfer function symbol ... 185

Figure 47. Task decomposition diagram ... 186

Figure 48. Original CommonKADS method for syndissertation task ... 191

Figure 49. Modified method for syndissertation task ... 192

Figure 50. Original CommonKADS method for scheduling task... 193

Figure 51. Modified method for scheduling task ... 194

Figure 52. Original inference structure of assessment task template ... 197

Figure 53. Inference structure of the altered assessment task template ... 198

Figure 54. The overall dialog diagram ... 204

Figure 55. Communication plan control through UML state transition diagram ... 206

Figure 56. Mobile application start-up screen ... 253

Figure 57. Mobile application authentication screen ... 253

Figure 58. Mobile application main screen ... 254

Figure 59. Course actualities module... 254

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List of Tables

Table 1. Convergence between new learning and new technology ... 17

Table 2.Comparison between e-learning and m-learning ... 23

Table 3. Differences in terminology between e-learning and m-learning ... 24

Table 4. Main features of each generation of mobile wireless networks ... 56

Table 5. Difference between data, information, and knowledge ... 83

Table 6. Problems and opportunities: Worksheet OM-1 ... 105

Table 7. Variant aspects: Worksheet OM-2 ... 107

Table 8. Overall process breakdown: Worksheet OM-3(A) ... 121

Table 9. M-leaning process breakdown: Worksheet OM-3(B) ... 123

Table 10. Knowledge assets: Worksheet OM-4 ... 125

Table 11. Checklist for feasibility decision document: Worksheet OM-5 ... 126

Table 12. M-learning course design recommended adaptations ... 136

Table 13. TM-1 worksheet for m-learning course design task ... 137

Table 14. TM-1 worksheet for subject presentation task ... 139

Table 15. TM-1 worksheet for instructor-students communications task ... 141

Table 16. TM-1 worksheet for communications encouragement task ... 143

Table 17. TM-1 worksheet for m-learning assessment task ... 145

Table 18. TM-2 worksheet for learning material and references ... 146

Table 19. AM-1worksheet for learning expert ... 150

Table 20. AM-1 worksheet for m-learning instructor ... 151

Table 21. AM-1 worksheet for m-learning application ... 152

Table 22. Description of m-learning domain concepts in CML2 code ... 165

Table 23. List of domain schema constructs in the knowledge base ... 177

Table 24. Classification of m-learning teaching tasks and their task templates. ... 188

Table 25. Classification of design requirements ... 189

Table 26. Basic elements of m-learning communication model ... 202

Table 27. CM-1 worksheet for access-request transaction ... 207

Table 28. CM-1 worksheet for access-acknowledgment transaction ... 208

Table 29. CM-2 worksheet for access-request transaction ... 210

Table 30. CM-2 worksheet for access- acknowledgment transaction ... 211

Table 31. Mobile application architecture worksheet DM-1 ... 231

Table 32. Mobile application target implementation platform worksheet DM-2 ... 232

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Abbreviations

ITU : The International Telecommunication Union PDA : Personal Digital Assistant

LTE : Long Term Evolution

ICT : Information and Communication Technology CBL : Case-Based Learning

PBL : Problem-Based Learning SMS : Short Message Service

MMS : Multimedia Messaging Service OS : Operating System

GPS : Global Positioning System TAM : Technology Acceptance Model

UTAUT : Unified Theory of Acceptance and Use of Technology model ADL : Advanced Distributed Learning

LMS : Learning Management System GUI : Graphical User Interface

KADS : Knowledge Analysis and Design System KBS : Knowledge Based System

CEO : Chief Executor Officer OM : Organization Model TM : Task Model

AM : Agent Model

CM : Communication Model

ODBC : Open Database Connectivity

CORBA : Common Object Request Broker Architecture DM : Design Model

PDF : Portable Document Format

RSS : Rich Site Summary or Really Simple Syndication XML : Extensible Markup Language

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Dedications

“To my parents, my wife, and my kids”

“To all victims of the bloody coup in Egypt: The martyrs, the wounded, the

detainees, and their families”

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Acknowledgements

Foremost, I would like to express my sincere gratitude to my reseach advisor Mrs. Laurence Capus for her sincere support, cooperation, patience, and comprehension. In addition, I would like to thank my reseach co-advisor Mr. Ronald Beaubrun for his support and guideness. Many thanks also to my teammates in the Artificial Intelligence lab (ERICAE) and to all members of the Computer Science and Software Engieering Department in Laval University.

Finally, thanks a lot to all my familly members for their love and endless support. Mahmoud Mohanna Laval University, Quebec, Canada

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Chapter 1 : Introduction

It is estimated that the total number of mobile phone subscriptions worldwide is over 6.8 billion as estimated by ITU (The International Telecommunication Union) in 2013 [1]. Usage of mobile phones becomes popular in all modern societies and most of people can afford its cost. In addition, the exponential growth of wireless and mobile networks has brought vast changes in mobile devices, protocol development and standardization, network implementation, and user acceptance.

With the help of wireless technology and mobile devices, a ubiquitous learning environment can easily be constructed to support the m-learning mission, i.e. “learning anywhere, anytime, and in any form” which are not possible to be achieved in traditional learning classrooms. We can certainly consider mobile learning as a further expansion of the scope of e-learning and d-learning as will be explained in detail later. However, it is also considered as a new distinct technology-based learning due to its special technical and pedagogic characteristics.

M-learning is enabled by integrating various hardware and software technologies into multimedia applications facilitating the communication of educational content in a number of different formats (e.g. quizzes, games, short messages, and multimedia contents) to deliver formal and informal education for different purposes. On the other hand, m-learning can be applied in a variety of subjects in primary, secondary, higher, lifelong, community, and professional education. The end-user terminal of most m-learning applications involves an ordinary mobile phone, a smart phone, a Personal Digital Assistant (PDA), or even a portable media player (such as Apple’s iPod), or a tablet computer. The applications are usually supported by the latest wireless telecommunication infrastructure e.g. 4G and 4G LTE telecommunication networks, and Wi-Fi networks. It is believed that emerging wireless and mobile networks and mobile devices will provide new applications in m-learning.

Despite of the fact that m-learning is a fast growing technology, it is important to mention that it faces many problems which have to be solved to allow it taking its rightful

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place in the field of technology-based learning. The main m-learning drawback is the absence of standard in addition to the lack of awareness about how it can be well integrated in the learning process. The most critical challenge facing us is the formulation of a standard describing how to develop an efficient m-learning system and how to define its actors and components precisely. Consequently, this research is motivated of the m-learning opportunities, limitations, and challenges.

Before going through the different parts of this dissertation, we introduce some terminologies which are frequently used in this dissertation and might seem unclear or confusing. Some of these terms are used interchangeably. Moreover, we explain the small differences between some of these terms that are used interchangeably.

1.1 Terminology

Before going through the different dissertation parts, we need to clarify some confusing terms and to explain the differences between them. Some of these terms seem to be identical but this is not accurate. They may be completely different or even having opposite meanings. Some of used terms in this dissertation are also subsets of others. In this section, we reveal the confusion.

1.2.1 Learning vs. education

The two words learning and education do not have the same meaning. The main difference in that learning is a continuous process which is related directly to the individual himself and it is not necessary to be associated with the obtainment of a certain degree or qualification. Learning is a continuous process starting from the birth to the death, whereas education always takes place during a certain period of life [2].

In brief, education is the formal process, while learning is actual outcome of it. Somebody may memorize the information for just doing well in the exam and may get eventually the high school or the university degree without learning anything. On the other hand, somebody may go through self-study and training in a certain field and becomes well-learned without obtaining any degree in that field.

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3 This fact explains why we are always talking about learning is our research instead of education. This is because we are focusing on the actual and the real acquisition of knowledge through technology, not only the official use of technology in education.

1.2.2 Formal vs. informal learning

Formal learning is the knowledge gained during a formal education process. In other words, formal learning takes place while being enrolled in a formal discipline to obtain a certain degree or certification [3]. In the light of the former definitions for learning and education, we can conclude that formal learning is the intersection between education and learning.

On the other hand, informal learning does not have a formal frame or any obligation on the learner. It is the learning which takes place unofficially without being enrolled in an education program. As we see later, certain informal learning courses may be provided by the official authorities in order to aware the public about some vital information such as the first aids, the prevention from a certain disease, how to react in case of fire, etc.

1.2.3 Learner vs. student

It is now easy to understand the difference between a learner and a student. A learner is anybody who acquires knowledge whether formally or informally, while a student is anybody who is officially enrolled in an education discipline. Indeed, the set of students is a subset of the set of learners as each student is a learner while not all learners are students. The term learner is wider and more generic than the term ‘student’.

1.2.4 Teacher, professor, and instructor

In the literature, there are many different definitions for the person who provides learning or education to learners. Many terms are used in the field of education such as teacher, processor, tutor, instructor, principal, educator, trainer, etc. Each term has a different meaning from the others. However, there is no global definition for each word. The meanings of some of these words differ according to the geographic location and the

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scholar level. Here we introduce only three terms that represents the most common used terms among the former ones. These terms are : Teacher, professor, and instructor.

A teacher is the person who teaches. The verb teach is defined in oxford dictionary as “Impart knowledge to or instruct (someone) as to how to do something” [4], while the word ‘processor’ in North America is usually used to refer to the person who provides education in the college or university level. On the other side, in Britain, the word ‘professor' is used to refer to a high-ranking university teacher, especially the one who is head of a department [3].

The word ‘instructor’ also has different meanings. In the university level, it is usually used to refer to the person who carries out teaching tasks without having a permanent position. In addition, some dictionaries define an instructor as “someone who teaches a sport or a practical skill such as swimming or driving” [3]. However, the word ‘instructor’ is used generally to refer to anyone who educates anywhere. Thus, it is more generic that the word ‘teacher’ and ‘professor’. Therefore, in this dissertation, we have chosen to use the word ‘instructor’ to refer to the person who provides the learning material regardless the learning type or the learning level.

1.2 Research question and objectives

The main problems related to the development of m-learning systems can be summarized in:

1. The absence of a global m-learning standard;

2. The presence of technical, pedagogical, social, administrative obstacles prohibiting m-learning from contributing efficiently in the learning process; 3. The blurring image about the roles of different actors involved in an

m-learning process.

In the literature, these topics are not well covered. Researches in m-learning from information systems sides are inconsistent, incoherent, and overlooked a lot of important details. This is shown in details along part I, and particularly in chapter 7.

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5 Therefore, our research question arises nearly collecting all the mentioned problems in one statement can be defined as How to formulate a robust analysis and development model for a typical mobile learning system and how to identify system concepts as well as involved agents and their roles ?”

Thus, we can define our main research objective as the construction of a comprehensive model of the learning process including the definition of different m-learning components, tasks, and agents with keeping the feasibility and the generality of the proposed model. The produced model provides a detailed understanding for m-learning in order to allow subsequent researchers and specialists to analyze and develop m-learning systems that are capable to contribute efficiently in the pedagogic process.

1.3 Methodology

In our research, we consider a typical m-learning system as a knowledge system rather than being an ordinary software system. The hypodissertation depends on the fact the an m-learning system is supposed to be formed of several modules dealing with different data sources in addition to the presence of the integration between information and telecommunication technologies. This hypodissertation allowed us to employ a knowledge engineering methodology to guide our research.

In order to realize our principal research objective i.e. the establishment of a generic comprehensive model of m-learning, we follow a reliable, verified, well-constructed knowledge engineering methodology called the CommonKADS methodology for knowledge engineering and management. CommonKADS provides a model suite composed of six models forming three consecutive modeling stages; context, concept, and artifact modeling.

1.4 Main contributions

Following the CommonKADS methodology, we introduce six general models for m-learning :

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1. Organization model : describes the m-learning organizational aspects. In this

model, we describe the detailed specifications of a typical organization providing m-learning services.

2. Task model : identifies the m-learning teaching tasks with relevant examples and

suggestions.

3. Agent model : describes the m-learning agents (actors) and identifies their

required competences.

4. Knowledge model : Identifies the concepts a typical m-learning system and their

inter-relationships. It provides also a generalized conceptual representation for m-learning domain, inferences, and tasks.

5. Communication model : describes the communication aspects and constraints

between system agents while carrying out their tasks.

6. Design model : provides a generalized technical description for a typical

m-learning system based on the previous models with relevant examples and alternatives.

The mentioned six models explain m-learning domain from different viewpoints. This entirely satisfies the research objectives identified earlier. In addition, these models are good examples to be followed by subsequent researchers in the field of m-learning [5].

1.5 Dissertation classification

This dissertation is composed of five parts as follows :  Part I - The state of the art

The first part is composed of the six chapters from chapter 2 to chapter 7. It discusses the m-learning state of art, different definitions of m-learning, how it differs from e-learning (electronic e-learning) and d-e-learning (distance e-learning), m-e-learning unique characteristics and challenges, technological aspects of m-learning including a brief overview of evolutions and characteristics of mobile devices and telecommunication networks. Finally, in the last chapter of part I, we present a look at actual research status in the field of m-learning and its categorization.

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7  Part II - Research question, objectives, and methodology

The second part is composed of three chapters; chapter 8, 9 and 10. In chapter 8, we define the research question and the research main objective and sub-objectives in the light of the state of art discussed in part I. Next, in chapter 9, in the light of knowledge engineering terms and the nature of learning, we justify our assumption to consider m-learning systems as knowledge systems instead of the conventional consideration as regular information systems. In chapter 10, we present the two main classes of knowledge engineering methodologies accompanied with explanation of the convenience of the employing CommonKADS methodology to conduct our research. Afterwards, we introduce a historical overview of that methodology as well as its modeling suite and basic terminology.

 Part III - M-learning context modeling

In this part, we present the context modeling of m-learning which is the initial stage of CommonKADS modeling. As this stage is composed of three models (organization, task, and agent models), this part is also composed of three chapters: 11, 12, and 13. One chapter is dedicated for each model.

 Part IV - M-learning concept modeling

This part represents the middle stage of the modeling process. In this part, based on context models, we perform the concept modeling through the construction of the two concept models: knowledge and communication models in chapter 14 and chapter 15 respectively.

 Part V- M-learning artifact modeling

This part is composed of two chapters, chapter 16 and chapter 17. In this part, we discuss the m-learning artifact modeling. As usual, we present the model structure with m-learning domain-related examples and pertinent alternatives. Afterwards, in the last chapter, we discuss a real m-learning experience in the university level that has been already applied in a higher education level course in the Computer Science and Software Engineering Department in Laval University. We discuss the results of this experiment. Finally, we present the overall conclusion accompanied with a brief discussion about future m-learning-related research directives.

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Part I

State of The Art

Chapter 2 : Definition of M-Learning ... 13

Chapter 3 : M-Learning vs. E-Learning & D-Learning ... 19

Chapter 4 : Characteristics of M-Learning ... 27

Chapter 5 : Limitations of M-Learning ... 35

Chapter 6 : Technological Aspects of M-Learning ... 43

Chapter 7 : Actual M-Learning Research Status ... 57

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11 Before going through our research, we should briefly discuss the state of the art of mobile learning. The main objective of this part is to familiarize the reader with the domain of research from all its aspects and to allow her/him to understand our research motivations.

This part of the document is composed of six chapters. In chapter 2, we introduce the definition of m-learning from both technical and pedagogical viewpoints. Afterwards, in chapter 3, we discuss how m-learning differs from e-learning (electronic learning) and d-learning (distance d-learning), and how it is considered as a new distinct type of d-learning in spite of the fact of being a natural evolution of them. In the next chapter i.e. chapter 4, the special characteristics giving the m-learning its distinction are discussed. These characteristics are classified into technical and pedagogic characteristics.

As expected, m-learning has several limitations and faces numerous obstacles. In chapter 5, those limitations and obstacles are discussed in detail to some extent. As usual, m-learning obstacles are classified into technical and pedagogic ones.

The two technological wings of m-learning i.e. mobile devices and wireless networks have special importance. Mobile devices are the tools through which m-learning services are provided, while wireless networks represent the medium through which the m-learning contents are transmitted. M-m-learning technological aspects have their share of discussion through chapter 6. The objective of this chapter is to allow the reader to imagine how the specifications and the capabilities of mobile devices and wireless mobile networks can influence greatly quality, contents, and opportunities of m-learning.

In the last chapter of part I, chapter 7, we discuss the actual researches taken place in the field of learning. We present four main perspectives of learning researches; m-learning acceptance, m-m-learning framework, m-m-learning implementation, and m-m-learning experiences.

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Chapter 2 : Definition of M-Learning

As a result of the mobile era and the explosion in the growth of mobile communications, m-learning plays a fast growing role in the field of education. However, this fast growing type of technology-based learning is not strictly defined in learning communities as they have defined m-learning based their particular experiences using their own backgrounds. Figure 1 shows the development timeline of computing and audio technology until the appearance and wide spreading of mobile technology.

Figure 1. Development timeline of computing, audio, and mobile technology

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In consequence, this has led to various definitions of m-learning from different points of view. In addition, the unique nature of m-learning is still difficult to be characterized.

Furthermore, as our engagement with technology increases with time and the continuing evolution in telecommunications, m-learning becomes not only a function of time, but also a function of the dynamic changes of technology. As a result, there is still some dispute amongst industry advocates in how m-learning should be defined: in terms of devices and technologies, in terms of the mobility of learners and the mobility of learning, or in terms of the learners’ experience of learning with mobile devices. In this chapter, we illustrate briefly the various attempts to in order to define m-learning from both technical and pedagogic sides.

2.1 M-learning from the technical side

Scientists and researchers agreed that the appearance of mobile phones has launched a major revolution in the human life evolution and life style. Although the term ‘mobile’ is widely used to refer to mobile phone, this is – indeed – an over simplification because it leads to a lack of attention to a lot of other mobile technologies that can be offered farther than the cellular phone technology such as iPods, MP3/4 players, tablets, etc.

As mentioned earlier m-learning is a new type of learning where learners can follow up their education “anywhere, anytime, and any form” using their mobile devices. These devices must respond to learners requests and provide them with all required information effectively. Moreover, they should provide – in most cases – interactive communications between all actors of the learning process: learners, instructors, and education administrators.

During the past years, i.e. after the wide spreading of mobile technology and its emerging applications in the field of educations, researchers tried to formulate a definition for m-learning, here are some of these definitions :

“Mobile learning is e-learning through mobile computational devices : Palms, Windows CE machines, even your digital cell phone” [6].

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15 “According to software vendors, it's the point at which mobile computing and e-learning intersect to produce an anytime, anywhere e-learning experience” [7].

“The term mobile learning (m-learning) refers to the use of mobile and handheld IT devices, such as PDAs, mobile phones, laptops and tablet PCs, in teaching and learning” [8].

Many trials have been done to formulate a precise definition to m-learning, one of them defines m-learning as “any educational provision where the sole or dominant technologies are handheld or palmtop devices” [9].

The last definition widens the scope of the previous definition as it means that m-learning could include: mobile phones, PDAs, smart-phones and may also include tablet PCs and laptops, while it excludes desktop computers and the similar solutions.

Although the former definition is generic enough to address other mobile devices even if they are not equipped with the wireless communication technology such as iPods and game consoles, such definition or description of m-learning is considered techno-centric and it is not very stable and based around a set of hardware devices.

As it is evident from the above definitions, the employment of mobile technologies that differentiates mobile learning from other forms of learning. Therefore, if learning happens through or with a mobile device away from a person’s usual learning environment, then it is mobile learning. However, such definitions merely treat mobile learning as an extension of e-learning’s spectrum and also draw attention to its technical limitations rather than referring to its unique pedagogic advantages and characteristics.

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2.2 M-learning from the pedagogic viewpoint

When we look at learning from the perspective of the learners or the users, the definition of mobile learning becomes much clearer. When considering the concept of mobility from the learner’s side, researchers argued that mobile learning is such type of learning which takes place as long as the learner ‘moves’ from a place to another. However, this type of learning cannot take place in the absence of the mobile technology. In addition, if the learning activity takes place in the traditional classroom where the learners are not moving but in the same time they are using mobile devices such as mobile phones or PDAs as learning tools, we cannot exclude this learning activity from being considered as a ‘mobile learning’ activity.

As a result, we can conclude that mobile learning includes any wireless technology-based learning even if it takes place in classroom as well as any learning activity depending on a mobile device even if it does not employ the wireless technology. The gray area in figure 2 represents the scope of mobile learning according to the former definition.

Figure 2. Scope of mobile learning

Moreover, there is another point of view for defining m-learning depends on the learning environment and experience. As learners learn together with their teachers and their peers, their learning style depends on competition and collaboration. Simply, we can conclude that they learn in a well-defined learning environment.

In the past, this learning environment was restricted within classrooms and the teacher was the primary source of knowledge (instructor-centered learning), this is

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17 changed by the concept of mobility which allows the learners to overcome the place restrictions and learning process is influenced by the surrounding environment (learner-centered learning).

Furthermore, mobility not only increases the learner’s capability to learn on the move but also it changes her/his surrounding learning environment. Consequently, learning material can be suited to be adapted with the learning environment. M-learning which takes into account learning context is called “contextual mobile learning or context-aware mobile learning” [10]

The momentary access to the learner’s surrounding learning environment (which is constrained by the mobile device in hand) imposes requirements as to what type of learning might be advisable, possible or appropriate (contextual learning). We thus deduct that a socially and educationally responsible definition should view that learner does not move alone with his learning tool (mobile device) but the whole learning environment is moving with her/him as well.

Furthermore, there is now a well-known convergence of mobile technologies related to the functions of mobile phones combining the computer-communications functions which are known as ICTs (Information and Communication Technologies). Another important convergence should be taken in concern between the new concepts of learning resulting from the concept of mobility and those which are related to that new type of learning [7].

Pedagogy Technology

Personalized Personal Learner centered User centered

Situated Mobile Collaborative Networked

Ubiquitous Ubiquitous Lifelong Durable

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2.3 Conclusion

We can conclude here that here are three different opinions for defining the m-learning in the academic community, which are as follows :

1. M-learning is a new form of distance learning (d-learning);

2. M-learning is an expansion of e-learning. Some authors simply define m-learning as “e-learning that uses mobile devices” [12];

3. M-learning is a new technology and a new way of learning as it has new features and characteristics and offers new pedagogies.

In the next chapter, we briefly explain the definitions of e-learning and d-learning, and how m-learning intersects with them and differs from them in the same time.

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Chapter 3 : M-Learning vs. E-Learning & D-Learning

In this chapter, we compare between the mobile learning and the two earliest technology-based learning techniques; electronic learning (e-learning) and distance learning (d-learning). The purpose of this comparison is to explain to the reader the featured characteristics of m-learning as a normal evolution of its predecessors and also to clarify its added values and valuable contributions in the learning field as well as the opportunities provided by it.

3.1 What is e-learning ?

E-learning comprises all forms of electronically supported training and teaching [13]. It is principally based on computer and network-enabled knowledge transfer. The application of e-learning includes both web-based learning and computer-based learning. Learning contents are transferred via Internet, intranet, video/audio tapes, TV channels, CD-ROM and DVD as shown in figure 3.

Figure 3. Various types and branches of e-learning

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E-learning can be live ‘synchronous’ learning, this means that students communicate with their peers and instructors in real-time, and also it can be completely self-paced ‘asynchronous’ learning. We can simply define e-learning as “all kinds of learning where learning is supported by electronic media”.

The wide spreading of the Internet usage has extended the importance of e-learning and increased its role in learning as a new concept of virtual classrooms has emerged. Furthermore, the network-based learning has established a new learner-oriented environment instead of the teacher-centered environment in traditional classrooms. This transition is considered a revolutionary change in the pedagogic patterns [11].

3.2 Differences between d-learning and e-learning

In the literature, the two terms e-learning and d-learning are usually used interchangeably to refer to the same thing i.e. learning through digital media. However, there is a slight difference between both definitions. Whereas e-learning refers to any digital learning, the condition of d-learning is the presence of Internet and/or intranet connection between the learner and the instructor like that in the case of virtual classrooms [14].

More specifically, self-studying using CDs or DVDS or video tapes is e-learning not d-learning, and also the digital classroom where learners and their instructor exist physically in the same place (computer-aided learning), this type of learning is e-learning but cannot be considered d-learning because of the absence of the network connection. It is evident that d-learning is a subset or a special case of e-learning. Thus, the two types of learning are almost identical in their features and characteristics.

Consequently, in the rest of this chapter, we compare only between m-learning and e-learning as the latter is the earliest, the widest, and the most generic type of technology-based learning.

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3.3 M-learning as a natural extension of e-learning

In the short period between 1995 and 2000 e-learning became the state of the art for the use of technology in education. Communities predicted that it was the final technological solution for corporate training. However, by the 2000s wired phones and wired computers were beginning to be replaced by wireless ones, and a new type of technology based learning (m-learning) has been developed as a normal evolution of e-learning but with new and unique technical and pedagogic specifications.

Because mobile devices have the power to make learning even more widely available and accessible, m-learning are widely as a natural extension of e-learning using mobile devices [16]. Most researchers and educators probably view m-learning as the immediate descendant of e-learning [17], for example, defines e-learning as “learning supported by digital ‘electronic’ tools and media”, and by analogy, m-learning as “e-learning that uses mobile devices and wireless transmission”.

Another definition of m-learning which illustrates more clearly the inheritance relation between m-learning and e-learning defines m-learning as “the intersection of mobile computing (the application of small, portable, and wireless computing and communication devices) and e-learning (learning facilitated and supported through the use of information and communications technology)” [6].

Figure 4 shows how m-learning is a subset of both d-learning and e-learning. However, this does not negate the special characteristics of m-learning as a new, unique, and special type of technology-based learning as will be explained later.

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Figure 4. M-learning as a subset of both d-learning and e-learning

3.4 Differences between m-learning and e-learning

Although m-learning is a natural evolution of e-learning with a new component added to it (i.e. the wireless component) as explained earlier in this chapter, in this dissertation and along of our research, we will follow the third point of view because the wireless feature of m-learning and other features inherited from it can lead to revolutionary changes in the learning style and context.

3.4.1 Different learning style

As mentioned earlier, e-learning can be real-time or self-paced, also known as ‘synchronous’ or ‘asynchronous’ learning. Additionally, e-learning is considered to be ‘tethered’ (connected to something) and presented in a formal and structured manner (d-learning). In contrast, m-learning is often self-paced, un-tethered and usually informal in its presentation. Table 2 shows the differences between e-learning and m-learning from the learning perspective.

3.4.2 Different devices

Mobile devices such as mobile phones, tablets, and iPods (m-learning devices) are quite different from desktop computers, laptops, and CD/DVD players (e-learning devices). Consequently, the two learning styles are not similar although the m-learning is

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23 an extension of e-learning as indicated earlier. It is important to indicate that there is some uncertainty about whether laptops and/or tablets can deliver mobile learning. However, we consider in our research that laptops are e-learning and d-learning devices but not m-learning devices because of their technical specifications such as their weights, operating systems, applications, and battery lifetime. Contrarily, tablets are considered as m-learning devices. In the market, the manufacturers and the specialists consider tablets (starting from iPad 1 and beyond) are no more than mobile devices with larger display and sometimes with higher processing power.

E-Learning M-Learning

Access to learning material only through a fixed workstation in a

private location: classroom, computer lab, or at home

Learning takes place anywhere, anytime (no boundaries)

Travel time to reach to Internet site No travel time required

Table 2.Comparison between e-learning and m-learning according to the learning style

3.4.3 Different terminology

The transition from e-learning to m-learning can also be characterized by a change in terminology of learning environment. Table 3 illustrates the changes in terminology resulting from the transition from e-learning to m-learning.

Furthermore, a new variety of words is used to describe the nature of learning when it is mobile (m-learning). Many of these words or terminologies are the core of what distinguishes m-learning from e-learning as shown in figure 5. Therefore, we are now able to see the emergence of new and distinct m-learning community.

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24 E-Learning M-Learning Computer Mobile Bandwidth Bluetooth, GPRS, 3G Multimedia Objects Interactive Spontaneous Hyperlinked Connected Collaborative Networked Media-rich Lightweight Distance learning Situated learning

More formal Informal

Simulated situation Realistic situation Hyper-learning Constructivism, situationism,

collaborative

Table 3. Differences in terminology between e-learning and m-learning [12]

Figure 5. Terminology used by m-learning and e-learning [9]1

1_{The question marks representing the intersection between e-learning and m-learning terminology refers to}

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3.4.4 Different time and context

Two other great differences between m-learning and e-learning should be explained i.e. time and context. Time and context represent the major differences between e-learning and m-e-learning. In e-e-learning, learners have plenty of time to get the e-learning material. In addition, the availability of sufficient display and required disk storage provides an e-learning course designer the opportunity and the tolerance while preparing the required material. On the other hand, in m-learning, there are many restrictions which limit the designer’s job such as small screen size, short duration of learning sessions, inadequate storage, and short duration of learning sessions.

3.5 Conclusion

Although learning is much recent and advanced than e-learning and the fact that m-learning is inherited from e-m-learning with newly added features, this does not mean that m-learning is always better than e-learning. In fact, each learning style is suitable for certain situations. In certain cases, the two learning styles complement each other, some modules of a particular learning course could be delivered through e-learning and other modules could be delivered through m-learning according to their context. In many cases, m-learning plays a supportive role to e-learning.

In the next chapter, we explain the unique characteristics of m-learning from both technical and pedagogic sides. This will clarify why it is considered as a new and revolutionary type of technology-based learning instead of being considered as just an extension of e-learning.

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Chapter 4 : Characteristics of M-Learning

As explained earlier, m-learning has special and unique characteristics from both pedagogic and technical sides. These characteristics force the scientists and the researcher to consider it as new way of learning rather than being just an extension of e-learning or d-learning. In the chapter, we present these featured characteristics.

4.1 M-learning pedagogic characteristics

There are four fundamental elements in m-learning; learners, instructors, teaching contents and the teaching methods.

The US National Research Council produced in 1999 a syndissertation of research into educational effectiveness across ages and subject areas [16]. It concluded that effective learning should be :

1. Learner centered : it should focus on building the required skills and knowledge

of students, and enables them to reason from their own experience.

2. Knowledge centered : the curriculum is built from sound foundation of validated

knowledge, taught efficiently and with inventive use of concepts and methods.

3. Assessment centered : the assessments should be matched to the ability of the

learners, and offer them diagnosis and formative guidance.

4. Community centered : the success of the learning process leads to

well-developed knowledge community through sharing of knowledge and inter-students support.

M-learning has several features allowing and supporting a successful learning process satisfying the former conditions for an effective learning process. As shown in figure 6, with regard to the learning spaces, m-learning offers the needed possibilities for the three learning spaces; individual, social, and situated learning.

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Figure 6. The three learning spaces [18]

4.1.1 Constructive (individual)

By the launch of personal computers in the 1980s, various capabilities for presenting the information have been offered such text, graphics, and videos as well as different direct manipulation interfaces provided such as keyboards, mice, and joysticks which enable the computer user to actively interact with it. These new opportunities offered by the personal computer resulted in the shift of teacher-centered to learner-centered approach. The concept of Constructivism has emerged as the learner is actively constructing his own knowledge [18].

Seymour Papert stated that “The general notion of constructivism that by actively trying to create something concrete (either physical or computational) to solve a problem the learner naturally had to make their thinking – that which was implicit and/or explicit” [19].

The term Constructivism refers to a type of learning theory that explains human learning as an active attempt to construct meaning in the world around us. Constructivism divides learning into two types : accommodation and assimilation. The focus is on the individual’s desire and ability to learn, and the role of the teacher or the instructor here is to help and guide this self-directed learning.

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29 In the last few years, with the invention and the wide spreading of mobile and wireless telecommunications technologies and the emergence of mobile learning, m-learning provides the possibility to combine learning with moving, field education with ICT, personalized and learner-enhanced learning material.

As m-learning can take place everywhere and during the whole duration of the learner’s life, it is believed that it can bring institutionalized learning closer to learning in the fullest sense. M-learning can also provide the individual services according to the learner’s needs and his individual learning style and the features of the subjects in particular, it can be suited and adapted according to the needs and requirements of the learner himself (Individualism). In other words, m-learning can be ‘personalized’. For this reason, the term ‘personalized’ is often used in the literature when talking about m-learning.

The two most prevalent models of constructive learning offered by m-learning are case-based learning and problem-based learning [20]. Here is a brief definition for each of these two models :

 Case-Based Learning (CBL) : it depends on providing case studies such as stories or story lines to the learners to read or explore interactively. Learners can be directed toward a conclusion, or be provided the resources and context to discuss and debate issues dynamically. It is common in business and law schools.

 Problem-Based Learning (PBL) : it is quite similar to the former approach. PBL is also a learner-centered pedagogy in which learners learn about a subject in the context of complex, multifaceted, and realistic problems. It is widely used in business administration, nursing, and medical education.

4.1.2 Collaborative (social)

Collaborative learning is generally perceived as being beneficial to learners. Creating a community of learners will be beneficial to students’ experiences and this can be done by good utilization of communication tools provided by the new technologies.

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M-learning takes the advantage of the mobile communication devices it uses as its basis (e.g. mobile phones, Wi-Fi-enabled PDAs, and tablets) and promote collaborative learning as much as possible. In addition, the collaboration can be achieved through the use of SMS (Short Message Service) or e-mail.

The term community of practice describes the informal network or group of people who exchange tips, best practices, and solutions to real problems [21]. A community of practice is described as “peers in the execution of real work. What holds them together is a common sense of purpose and a real need to know what each other know” [22].

Using wireless devices, a community of practice can contribute to a forum or threaded discussion. Questions and answers posted to the discussion forum can be accessed from the field. As the rapid evolution of telecommunication networks and the increase of their bandwidth and capabilities in addition to the wide spreading of smart phones and easiness of Internet access through them, web forums and discussion boards are also good examples for virtual learning communities which can be offered using modern mobile devices. In addition, mobile devices can also be used to download different useful files such as word templates, sample letters, spreadsheets, and other documents that the team has developed over time.

A simple example of this type of collaborative learning is the sharing of field photos among learning team members. By using a cell phone with a camera, a team representative in the training field can send images to his colleagues and start a discussion board via SMS among team members around these collected photos.

4.1.3 Situated (contextual)

M-learning provides the support for situational learning. Learning takes place in the true and natural social context, realize the real ‘living learning’.

Situation learning is the potential for location-based learning. This means that the phone can alert the person when he is located near a potential learning experience based

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31 in the context in which the learning will be used, – which potentially can help retention and return on investment.

M-learning which takes into account the learning context is called “contextual mobile learning or context-aware mobile learning” [10]. For example, a visitor for a museum can get information about the location and the contents of the museum and its history on his mobile device. Another example is an English learning course: learners can get new words and expressions related to their locations such as being in the train station, in the market, in the restaurant, and so on.

Furthermore, mobile devices equipped with accessorial sensors, such as GPS receivers, digital cameras help in acquiring learning context information such as location, activity, and connectivity. This helps in improving and assisting the learning activities.

Learning context is a very great advantage of mobile learning as the activities of the learner and his surrounding environment are central and effective in determining the learning objectives and educational contents.

4.2 Technical characteristics of m-learning

Using of mobile devices provides some features that have large effect on the learning process driven by mobile learning. The following technical factors result in the unique and special nature of m-learning. They should be taken in concern during the design and the development of any mobile-based learning process:

4.2.1 Mobility

As long as learner is covered by the telecommunication network, he has access to the learning material anytime and anywhere within the coverage area. Although this feature provides the m-learning its highly important property, any time the learner loses his connection he loses his access to the learning material unless it was formerly download to his device. The learning applications should keep the learner up-to-date as soon as he restores his connection to the network.

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4.2.2 Real time

M-learning is a real time learning method as it allows the learner a continuous and instantaneous access to the learning material. All required communications between peers or learner-instructor discussions can be driven using messaging applications installed in their mobile devices as well as SMS.

4.2.3 Virtualization

Mobile devices with cameras allow instructors to create virtual classrooms. In addition the ability of performing video calls provides high degree of interactivity and interrelationships among learners and also between them and their instructors.

4.2.4 Digital bit-sized stream

It is evident that all elements of any m-learning system are entirely digitized. Digital multimedia, wireless network system, mobile devices, transmitted messages either text, voice, or images. All are signs of mobile learning digitization

As the traffic of wireless networks has a great effect on the interconnection between the different components of the m-learning systems, the educational contents should be relatively short and comprehensive. In addition, applications used for m-learning should be light in size and does not require large bandwidth or need long time duration to start. M-learning applications should minimize and simplify the needed interaction between the user and the network.

4.3 Technical evaluation of m-learning handheld devices

There are certain technical criteria should be followed to evaluate the capability of the mobile device to be used to follow an m-learning education and/or training course [23]. They can be stated in brief and short items under different categories as follows :

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4.3.1 Performance

 Processor;  RAM ;

 Expansion Storage;

 Communication technologies such as Bluetooth, Wi-Fi, GPS, Telephony, GPRS, Infrared IrDA.

4.3.2 Input / Output peripherals and devices

 Display screen;

 Audio, Photo and Video recorder and player;  Microphone and speakers;

 Touch screen, Keyboard, direction pad;

 RFID sensors, smart card reader, data probes, bar code reader, scanner, etc.;  GPS navigators.

4.3.3 Compatibility

 Support open source software;  Operating systems;

 Browsers;

 Variety multimedia format support.

4.3.4 Security

 Security Certificates;  Encryption, Cryptography;  Anti-spam, anti-virus, etc.;  Password;

 Touch-screen or Keyboard lock;  Block incoming/outgoing.

Using knowledge engineering for Modeling Mobile Learning Systems