Personalised mobile learning content delivery: a learner centric approach

2009 ◽  
Vol 3 (1) ◽  
pp. 84 ◽  
Author(s):  
Ty Mey Eap ◽  
Dragan Gasevic ◽  
N.A. Kinshuk ◽  
Fuhua (Oscar) Lin
Keyword(s):  
Mobile Learning ◽  
Content Delivery ◽  
Learning Content

Devised Mobile Learning System Based on Campus

2011 ◽  
Vol 271-273 ◽  
pp. 1160-1163
Author(s):  
Yan Xin Hu
Keyword(s):  
Mobile Learning ◽  
Learning System ◽  
Learning Content ◽  
Function Module ◽  
Basic Features ◽  
Mobile Learning System

Introduced the mobile learning content, analyzed the basic features of mobile learning, designed mobile leaening system based on campus, and each function module of mobile learning system.

A Mobile Learning Content-independent Versatile Ubiquitous System (CiVUS)

2012 ◽  
pp. 21-36
Author(s):  
Joel J.P.C. Rodrigues ◽  
Diogo Videira Sousa ◽  
Isabel de la Torre
Keyword(s):  
Mobile Devices ◽  
Mobile Learning ◽  
Engineering Students ◽  
Learning System ◽  
Study Group ◽  
Multimedia Contents ◽  
Learning Content ◽  
Ubiquitous System ◽  
Collaborative Activities ◽  
The University

Mobile learning (m-learning) introduces the idea of learning from virtually anywhere, regardless of the in-motion learner. This paper presents the development and impact of m-learning system capable to deliver personalized contents to the learner, called Content-independent Versatile Ubiquitous System (CiVUS). This solution promotes communication between learners and their teachers by encouraging learners to share self-made multimedia contents. Enabling interactivity makes mobile devices suitable for the development of collaborative activities amongst engineering students. CiVUS intends to offer support for engineering subjects study. It can be used inside or outside classrooms by learners and teachers, due to the mobility of these devices, at the time they find more suitable. The system has been validated and evaluated through a real usage. The study group collected answers from 10 teachers and 87 engineering students of the University of Beira Interior, Portugal and the University of Valladolid, Spain. The results demonstrate that the majority of the inquired people totally agree (all items over 72% for professors and 74% for students).

Support for Cloud-Based Mobile Learning

2016 ◽  
pp. 225-246 ◽  
Author(s):  
Kritika Verma ◽  
Sonal Dubey ◽  
M. A. Rizvi
Keyword(s):  
Cloud Computing ◽  
Information And Communication Technologies ◽  
Mobile Learning ◽  
Communication Technologies ◽  
Information Resources ◽  
Learning System ◽  
Learning Content ◽  
The Future ◽  
Information And Communication ◽  
Current Scenario

Cloud based mobile learning (m-learning) is emerging as one of the most important branches of cloud computing, and is still in its infancy. These days, there are two emerging archetypes in Information and Communication Technologies (ICT) for learning. The first one is the anytime, anywhere, on-the-move, to be called the mobility archetype, and the second one is the cloud computing. Both archetypes are radically transforming the way we learn, communicate, access, and utilize information resources, and connect with peers and colleagues, thus affecting all aspects of education. This chapter delivers an introduction of the evolution of cloud based m-learning, benefits and characteristics of cloud based m-learning. It also canvasses the current scenario of m-learning utilizing the cloud, various challenges for implementing the m-learning system on the cloud. It further confers technologies used for cloud based m-learning. It also considers a brief look at methods for creating m-learning content and experiences, suggested by various researchers and concluded with the future aspects of the cloud based m-learning.

Adaptive Content Delivery in E-Learning Systems using Mobile Agents

2012 ◽  
pp. 148-166 ◽  
Author(s):  
S. R. Mangalwede ◽  
D. H. Rao
Keyword(s):  
Mobile Agents ◽  
Educational Background ◽  
Content Delivery ◽  
Case Based Reasoning ◽  
Distributed Computing Systems ◽  
Learning Content ◽  
E Learning ◽  
Networking Technologies ◽  
Adaptive Content Delivery ◽  
Adaptive Content

The e-Learning refers to the use of networking technologies to create, foster, deliver and facilitate learning anytime, anywhere. This chapter discusses our research on personalization of e-Learning content based on the learner’s profile. After justifying the feasibility of using mobile agents in distributed computing systems for information retrieval, processing and mining, the authors deal with the relevance of mobile agents in e-Learning domain. The chapter discusses the proposed Case-Based Reasoning (CBR) as an approach to context-aware adaptive content delivery. Different parameters like technological, cultural and educational background of a learner are taken as the basis for forming the case-base that determines the type of content to be delivered. Along with the CBR, a diagnostic assessment to gauge an insight into the student’s current skills is done to determine the type of content to deliver. The implementation observations of such implementation vis-à-vis traditional e-Learning are also documented.

Map-based Visual Analytics of Moving Learners

2016 ◽  
Vol 8 (4) ◽  
pp. 1-28 ◽  
Author(s):  
Christian Sailer ◽  
Peter Kiefer ◽  
Joram Schito ◽  
Martin Raubal
Keyword(s):  
Mobile Learning ◽  
Visual Analytics ◽  
Temporal Patterns ◽  
Behavior Patterns ◽  
Usability Engineering ◽  
Learning Content ◽  
Potential Problems ◽  
Spatio Temporal

Location-based mobile learning (LBML) is a type of mobile learning in which the learning content is related to the location of the learner. The evaluation of LBML concepts and technologies is typically performed using methods known from classical usability engineering, such as questionnaires or interviews. In this paper, the authors argue for applying visual analytics to spatial and spatio-temporal visualizations of learners' trajectories for evaluating LBML. Visual analytics supports the detection and interpretation of spatio-temporal patterns and irregularities in both, single learners' as well as multiple learners' trajectories, thus revealing learners' typical behavior patterns and potential problems with the LBML software, hardware, the didactical concept, or the spatial and temporal embedding of the content.

Empirical Research on Learners’ Thoughts About the Impact of Mobile Technology on Learning

2011 ◽  
Vol 3 (1) ◽  
pp. 73-88 ◽  
Author(s):  
Gábor Kismihók ◽  
Réka Vas
Keyword(s):  
Empirical Research ◽  
Mobile Learning ◽  
Mobile Technology ◽  
Research Study ◽  
Content Delivery ◽  
Learning Technologies ◽  
European Countries ◽  
Positive Attitudes ◽  
Technical Issues ◽  
The Impact

Mobile learning is gaining attention in Europe. Researchers are examining both pedagogical and technical issues regarding mobilized content delivery; however, little is known about current learners’ thoughts toward mobile learning. In this article, based on an empirical research study, the authors show what learners think about mobile learning and related learning technologies. Data consisting of 300 learners’ thoughts and experiences in connection with mobile learning (living in five different European countries) have been gathered and analysed. Results indicate that current positive attitudes toward mobile learning may be negatively influenced by experience, if previous patterns with other learning technologies are repeated.

A Methodology for Enhancing Mobile Learning Through Content Semantics

2013 ◽  
Vol 5 (1) ◽  
pp. 21-38
Author(s):  
Glaroudis Dimitrios ◽  
Manitsaris Athanasios ◽  
Kotini Isabella
Keyword(s):  
Mobile Learning ◽  
Web Sites ◽  
Mobile Users ◽  
Learning Material ◽  
Learning Tools ◽  
Learning Content ◽  
Increasing Demand ◽  
Web Experience ◽  
Educational Portal ◽  
Content Semantics

Mobile learning is becoming increasingly popular. Educational web sites can be used as supporting learning tools for students who wish to supplement their knowledge without restrictions of time and place. The continuously increasing demand for enhanced remote and mobile services, as well as the difficulty in easily incorporating current learning services for mobile users, renders essential the adaptation of educational material for these requirements. The objective of this work is to present and evaluate a methodology for producing content semantics from learning material. The proposed approach results in recommending links, which are relevant to the mobile users’ interests, by exploiting the recorded usage of an educational portal and the semantics of the learning content. The implementation results reveal enhanced capabilities in mobile learners’ web experience and usability.

Accessing Learning Content in a Mobile System

2007 ◽  
pp. 198-215 ◽  
Author(s):  
Anna Trifonova
Keyword(s):  
Mobile Devices ◽  
Mobile Learning ◽  
Learning System ◽  
Personal Digital Assistants ◽  
Learning Material ◽  
Mobile System ◽  
Learning Content ◽  
Clear Idea ◽  
Mobile Learning System

This chapter has the aim to point out an important functionality of a ubiquitous mobile system, and more specifically, its application in the learning domain. This functionality is the possibility to access the learning material from mobile devices, like PDAs (personal digital assistants) during their off-line periods and the technique to approach it, called hoarding. The chapter starts with the overview of a concrete mobile learning system—Mobile ELDIT, so as to give a clear idea of when and how this problem appears and why it is important to pay attention to it. Later, a description of the development approaches for both general and concrete solutions are discussed, followed by more detailed description of the important hoarding steps.

Accessing Learning Content in a Mobile System

2009 ◽  
pp. 1367-1380 ◽  
Author(s):  
Anna Trifonova
Keyword(s):  
Mobile Devices ◽  
Mobile Learning ◽  
Learning System ◽  
Personal Digital Assistants ◽  
Learning Material ◽  
Mobile System ◽  
Learning Content ◽  
Clear Idea ◽  
Mobile Learning System

This chapter has the aim to point out an important functionality of a ubiquitous mobile system, and more specifically, its application in the learning domain. This functionality is the possibility to access the learning material from mobile devices, like PDAs (personal digital assistants) during their off-line periods and the technique to approach it, called hoarding. The chapter starts with the overview of a concrete mobile learning system—Mobile ELDIT, so as to give a clear idea of when and how this problem appears and why it is important to pay attention to it. Later, a description of the development approaches for both general and concrete solutions are discussed, followed by more detailed description of the important hoarding steps.

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