scholarly journals Course delivery and module learning via learning objects (knowledge map) in mobile learning environment

2012 ◽  
Vol 7 (1) ◽  
pp. 43-54
Author(s):  
Chung Sheng-Hung
Keyword(s):  
Learning Environment ◽  
Learning Style ◽  
Mobile Learning ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Spatial Knowledge ◽  
Learning Object ◽  
Knowledge Map ◽  
Portable Devices ◽  
Mobile Learning Environment

This paper focuses on the integration of the learning objects and knowledge map as the learning sequence suggestion in the mobile learning environment and explains the technologies involved, the applications and the issues of usability, accessibility, evaluation and effectiveness. Mobile learning has open up new path for learning support and opportunities to reach wider audience (learner) for education. This research focuses on using the knowledge map to store the characteristics of each learning object via concept schemas and represent the corresponding learning accessibility in the mobile learning environment. The proposed architecture provides a medium for the learning accessibility of learners through mobile applications and wireless portable devices such as smart phones, PDAs and tablet PCs. The approach using the combination of "touch" and "observe" spatial learning objects provides an intelligent solution to creating, sharing and improving the efficiency of mobile learning. The proposed mobile learning environment architecture consists of knowledge map components mainly, navigation, concept schemas and learning object path. By using these knowledge structures, this study may enhance and enrich the concept and activity of adaptive learning in different individuals and communities. The spatial knowledge map constructed was useful in identifying the characteristics of the learning objects (e.g., learning object 1: lesson with navigating sentences, learning object 2: lesson with navigating sentence and code explanation, etc) and automatically matches the most appropriate learning contentand path suitable for learners. The architecture of the platform discussed in this study using the learning objects approach and knowledge map would facilitate a more widespread use of mobile learning, including courses or modules delivery of individualised learning path and learning style analysis.

scholarly journals MILO - A Proposal of Multiple Intelligences Learning Objects

10.28945/3137 ◽  
2007 ◽  
Author(s):  
Hamilton Matos ◽  
Pollyana Mustaro ◽  
Ismar Silveira
Keyword(s):  
Instructional Design ◽  
Multiple Intelligences ◽  
Learning Style ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Learning Object ◽  
Proof Of Concept ◽  
Personal Learning ◽  
Learning Contexts ◽  
Instructional Content

Learning objects-driven approaches for the development of instructional content have been widely used to structure entire courses and repositories for distinct learning contexts. Nonetheless, their use is still done in a static, non-adaptive manner, since students are presented to prebuilt compilations of learning object having few or none relationship with its learning current conditions, history or personal learning style, which together compose the student momentum. This work presents an analysis of current instructional design and multiple intelligences theories in order to create learning objects that provide adaptive learning methods according to different students’ characteristics. Using technologies that allow such dynamic approaches, it was created -as a proof of concept - a learning object about the Pythagorean Theorem.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

scholarly journals Towards a Mobile Learning Environment using Reference Architectures

2017 ◽  
Author(s):  
Maria Lydia Fioravanti ◽  
Nemésio Freitas Duarte Filho ◽  
Lucas Bortolini Fronza ◽  
Ellen Francine Barbosa
Keyword(s):  
Learning Environment ◽  
Mobile Learning ◽  
Mobile Learning Environment

Work-Based Mobile Learning Environments

2012 ◽  
pp. 229-238 ◽  
Author(s):  
Graham Attwell
Keyword(s):  
Learning Environment ◽  
Informal Learning ◽  
Learning Environments ◽  
Mobile Devices ◽  
Mobile Learning ◽  
Cultural Practices ◽  
Cultural Ecology ◽  
Work Process ◽  
Learning At Work ◽  
Mobile Learning Environment

This paper examines the idea of a Work Oriented Mobile Learning Environment (WOMBLE) and considers the potential affordances of mobile devices for supporting developmental and informal learning in the workplace. The authors look at the nature and pedagogy of work-based learning and how technologies are being used in the workplace for informal learning. The paper examines the nature of Work Process Knowledge and how individuals are shaping or appropriating technologies, often developed or designed for different purposes, for social learning at work. The paper goes on to describe three different use cases for a Work Oriented Mobile Learning Environment. The final section of the paper considers how the idea of the WOMBLE can contribute to a socio-cultural ecology for learning, and the interplay of agency, cultural practices, and structures within mobile work-based learning.

Technical Evaluation of Wireless Communications in a Mobile Learning Architecture

2011 ◽  
pp. 297-314
Author(s):  
Javier Carmona-Murillo ◽  
Jaime Galán-Jiménez ◽  
José-Luis González-Sánchez
Keyword(s):  
Mobile Learning ◽  
Mobile Networks ◽  
High Growth ◽  
Portable Devices ◽  
Desktop Computer ◽  
Embedded Devices ◽  
Wireless Technologies ◽  
Learning Platform ◽  
Mobile Learning Environment ◽  
Technical Evaluation

Due to the high growth of mobile networks and portable devices, learning process is evolving from desktop computer to mobile devices. In this sense, technologies and services that support this change are also evolving. The appearance of portable devices has made users to take part in this process from anywhere. On the other hand, architectures used in a mobile learning environment are designed to offer users the ability of participate in learning activities from its embedded devices. Campus Ubicuo is a mobile architecture over which learning services can be developed. The successful of any mobile learning platform fundamentally depends on the quality in learning services and also in the good operation of wireless technologies. In this chapter, we focus on this second aspect. We have evaluated the behaviour of wireless technologies in a mobile learning architecture when different services are offered through diverse networks.

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