The power of feedback.

On robust estimation of the location parameter

How to ... be a reflective practitioner.

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Keywords: a Vocabulary of Culture and Society

Educational games have the potential to provide intrinsically motivating learning experiences that immerse and engage the learner. However, the much heralded benefits of educational games seldom consider the one-size-fits-all approach to education they typically embody. The benefit provided by adaptive educational games is that of a motivating environment reinforced with a personalized learning experience. However, adapting a game to enhance its educational benefit endangers its intrinsic motivation and flow. This paper proposes a novel approach for non-invasively adapting a game to enable a personalized learning experience. This is achieved using an innovative, generic and reusable architecture, without mitigating the motivational features of gaming. An implementation of this approach in the form of the ALIGN (Adaptive Learning In Games through Noninvasion) system is detailed and the results of an authentic evaluation are discussed.

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Adaptive Educational Games: Providing Non-invasive Personalised Learning Experiences

One of the major obstacles in developing quality eLearning content is the substantial development costs involved and development time required [12]. Educational providers, such as those in the university sector and corporate learning, are under increasing pressure to enhance the pedagogical quality and technical richness of their course offerings while at the same time achieving improved return on investment. One means of enhancing the educational impact of eLearning courses, while still optimizing the return on investment, is to facilitate the personalization and repurposing of learning objects across multiple related courses. However, eLearning courses typically differ strongly in ethos, learning goals and pedagogical approach whilst learners, even within the same course, may have different personal learning goals, motivations, prior knowledge and learning style preferences. This paper proposes an innovative multi-model approach to the dynamic composition and delivery of personalized learning utilizing reusable learning objects. The paper describes an adaptive metadata driven engine that composes, at runtime, tailored educational experiences across a single content base. This paper presents the theoretical models, design and implementation of the adaptive hypermedia educational service. This service is currently being successfully used for the delivery of undergraduate degree courses in Trinity College, Dublin as well as being used as part of a major EU research trial.

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Multi-model, Metadata Driven Approach to Adaptive Hypermedia Services for Personalized eLearning

The evaluation of learner and tutor feedback is essential in the production of high quality personalized eLearning services There are few evaluations available in the Adaptive Hypermedia domain relative to the amount of research interest this domain is attracting Many of the papers in this domain focus on the technological design of systems without justifying the designs through the lessons learned from evaluations This paper evaluates the usability and effectiveness of using the multi-model, metadata-driven approach for producing rich adaptive eLearning solutions that remain content and domain independent Through this independence, the eLearning services developed can utilize many pedagogical approaches and a variety of models to produce a wide range of highly flexible solutions This paper identifies benefits to learners brought through adopting the multi-model approach gathered over four years of student evaluation It briefly describes the evaluation of the Adaptive Personalized eLearning Service (APeLS), a personalized eLearning service based on a generic adaptive engine

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Evaluation of APeLS – An Adaptive eLearning Service Based on the Multi-model, Metadata-Driven Approach

The goal of personalised eLearning is to support e-learning content, activities and collaboration, adapted to the specific needs and influenced by specific preferences of the learner and built on sound pedagogic strategies. One of the major challenges to the mainstream adoption of personalised eLearning is the complexity and time involved in composing the adaptive learning experience. The key goal in personalized eLearning development tools is to sup-port the teacher in composing adaptive and non-adaptive eLearning experiences. One of the arguments of this paper is that these learning experiences should be activityoriented and pedagogically driven. Presented is a detailed discussion of the challenges of composing adaptive courses and in particular the difficulties and possible techniques in composing appropriate models and information to support adaptive courses. The paper describes an adaptive course construction methodology which extends traditional eLearning syllabi development with design activities which support adaptivity definition, subject matter concept modelling, adaptivity technique selection as well as alternative instructional design template customisation. The paper then details the Adaptive Course Construction Toolkit (ACCT), which supports this methodology and illustrates the tools usage in the development of an adaptive course. Finally the paper presents an initial evaluation of the toolkit and its associated methodology.

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Personalisation for all: making adaptive course composition easy

e-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners’ cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of personalization involve considerable re-authoring of existing learning material. To reduce the implementation overhead on the content author and course designer it is imperative to facilitate the maximum reuse of learning resources. This paper investigates a standards-based approach to delivering personalized learning content to learners using WWW technologies. Detailed is an implementation of a personalized e-Learning service, called the OPen Adaptive Learning Environment (OPAL), which is based on delivering content personalized to the learner’s cognitive and presentation learning preferences using aggregation models based on ADL SCORM (ADL).

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Owen Conlan

Papers

Adaptive Educational Games: Providing Non-invasive Personalised Learning Experiences

Multi-model, Metadata Driven Approach to Adaptive Hypermedia Services for Personalized eLearning

Evaluation of APeLS – An Adaptive eLearning Service Based on the Multi-model, Metadata-Driven Approach

Personalisation for all: making adaptive course composition easy

Towards a Standards-based Approach to e-Learning Personalization using Reusable Learning Objects