mLearning is made possible by the existence and application of mobile hardware and networking technology. By exploring the capabilities of these technologies, it is possible to construct a picture of how different components of mLearning can be implemented. This paper will explore the major technologies currently in use: PDAs, SMS messaging via mobile phone, and podcasts via MP3 players.

https://trace.tennessee.edu/cgi/viewcontent.cgi?article=1006&context=utk_manapubs

The Growth of m-Learning and the Growth of Mobile Computing: Parallel developments

The ELeGI project focuses on integrating technology-enhanced learning methodologies into a pedagogy-driven and service-oriented architecture based on Grid technology. It aims at a system that is capable of realising personalised, adaptive, and experiential learning. This requires to have available a framework that, on the one hand, allows for representing existing domain knowledge, and, on the other hand, provides a representation of the learner's current state of knowledge. It is shown that a competence-based extension of Knowledge Space Theory provides a representation of the conceptual organization of a domain that not only allows for an adaptive assessment of an individual's knowledge, but also for generating personalised learning paths. The discussion of this framework emphasizes its application within an open distributed service model, and in the context of Virtual Scientific Experiments.

Competence-based Knowledge Structures for Personalised Learning.

http://people.cn.ntua.gr/jenny/images/MyData/journals/User%20Profile%20Modeling%20in%20the%20Context%20of%20Web%20-%20Based%20Learning%20Management%20Systems.pdf

User Profile Modeling in the context of web-based learning management systems

Determinants of Mobile Learning Acceptance: An Empirical Investigation in Higher Education.

A c hallenging topic in computer based education is to pr ovide personalization support for learners when e-learning t akes place in an open and dynamic envi ronment. By selecting and combining appropriate l earning ass ets into a l earning ob ject a l earner's needs and preferences may be ac counted for. Also by implementing web service in an adaptive learning environment the reusability of the learning content can be ensured. This paper addresses the problems of automatically selecting and integrating appropriate l earning materials for a learner using web services based o n the learners initial knowledge, goals, preferences etc. A system is described that provides l earning co ntent to multimedia i ndustries and institutions those who are working i n A dobe Flas h. Instead of providing a learner with static d ata, the approach is based on fulfilling learning objectives based on a d ynamic supply of services. Furthermore, the approach is based on reusable learning objects describing a learning process as a composition of learning goals. Based on the learning goals as well as web services, services appropriate t o ach ieve a specific learning goal ca n be selected, co mposed and invoked dynamically.

Adaptive Content Creation for Personalized e-Learning Using Web Services

The runtime creation of pedagogically coherent learning content for an individual learner’s needs and preferences is a considerable challenge By selecting and combining appropriate learning assets into a new learning object such needs and preferences may be accounted for However, to assure coherence these objects should be consumed within pedagogically meaningful learning activity structures There are a number of key aspects that need to be addressed in order to perform this kind of personalization, such as the appropriate modelling of the learner’s needs and preferences, representation of pedagogical strategies, representation of learning designs and assets as well as the runtime reconciliation of these elements to produce effective and coherent learning activities Moreover, preferences that teachers may have about the learner’s studies should also be considered iClass, an Integrated Project, funded by the European Commission under the auspices of the IST FP6, addresses this challenge with an innovative and ambitious suite of eLearning services This paper introduces iClass and its objectives

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The Challenge of Content Creation to Facilitate Personalized E-Learning Experiences

This article describes a learner modeling strategy that is employed by an adaptive learning system in order to provide each learner with a personalized e-Learning experience. Parameters related to the learners' prior knowledge, goal and learning style constitute the basis of the personalization and the adaptivity of the mentioned learning system. The present paper focuses on the mechanisms concerning the learner's prior knowledge and the goal parameters. The learner modeling that takes into account the prior knowledge of the learners is achieved by developing an ontological abstraction. Based on this ontological abstraction, a knowledge base is constructed in order to introduce the knowledge representations of the domain model and the curricular model, the knowledge and the learning structures. These knowledge representations specify how the prior knowledge of a learner will be represented, and also how it will be assessed and continuously updated.

Ali Turker

Papers

The Challenge of Content Creation to Facilitate Personalized E-Learning Experiences

Learner Modeling to Facilitate Personalized E-Learning Experience.