Adaptive hypermedia for education and training

Adaptive hypermedia (AH) is an alternative to the traditional, one-size-fits-all approach in the development of hypermedia systems. AH systems build a model of the goals, preferences, and knowledge of each individual user; this model is used throughout the interaction with the user to adapt to the needs of that particular user (Brusilovsky, 1996b). For example, a student in an adaptive educational hypermedia system will be given a presentation that is adapted specifically to his or her knowledge of the subject (De Bra & Calvi, 1998; Hothi, Hall, & Sly, 2000) as well as a suggested set of the most relevant links to proceed further (Brusilovsky, Eklund, & Schwarz, 1998; Kavcic, 2004). An adaptive electronic encyclopedia will personalize the content of an article to augment the user's existing knowledge and interests (Bontcheva & Wilks, 2005; Milosavljevic, 1997). A museum guide will adapt the presentation about every visited object to the user's individual path through the museum (Oberlander et al., 1998; Stock et al., 2007). Adaptive hypermedia belongs to the class of user-adaptive systems (Schneider-Hufschmidt, Kühme, & Malinowski, 1993). A distinctive feature of an adaptive system is an explicit user model that represents user knowledge, goals, and interests, as well as other features that enable the system to adapt to different users with their own specific set of goals. An adaptive system collects data for the user model from various sources that can include implicitly observing user interaction and explicitly requesting direct input from the user. The user model is applied to provide an adaptation effect, that is, tailor interaction to different users in the same context. In different kinds of adaptive systems, adaptation effects could vary greatly. In AH systems, it is limited to three major adaptation technologies: adaptive content selection, adaptive navigation support, and adaptive presentation. The first of these three technologies comes from the fields of adaptive information retrieval (IR) and intelligent tutoring systems (ITS). When the user searches for information, the system adaptively selects and prioritizes the most relevant items (Brajnik, Guida, & Tasso, 1987; Brusilovsky, 1992b)

Semantic Web Application and Framework Development in South African Higher Education Institutions

The evolution of the Semantic Web (SW) and its application marked a turning point in how students could benefit from a range of educational web tools and applications enabled by the SW, also referred to as Web 3.0 technology for academic purposes to meet their demands. This shift afforded students the opportunity to obtain meaningful information, collaboration and data filtering to suit their needs. It also offers freedom in how and where they choose to learn. SW tools and applications are progressively being used at several universities worldwide. However, educators’ ability to integrate the use of these tools and applications in teaching and learning appears to be a major problem in almost every development plan of education and educational reform efforts. Moreover, very few educators integrate web tools to their full potential in teaching. This paper probed the integration and use of SW tools and applications in higher education institutions (HEIs), and developed a framework for its adoption in academic processes. The objectives aimed to establish the credible features and benefits of SW tools and applications in HEIs, and how the integration supports students’ academic goals. It is anticipated to improve learning interaction and collaboration, and build a social presence and cohesion among students. The paper employed a systematic literature review, and information and communication technology theory of adoption. The developed framework ultimately suggests that SW tools and applications are beneficial and useful in positively impacting the pedagogical setting. Findings revealed that certain challenges with human factors (technophobia, beliefs), infrastructure, security concerns, ethical and legal issues were identified as a hindrance to be considered during integration. Despite the challenges, these tools and applications provide variety and a new wave of teaching and learning in South African HEIs, which is crucial for meeting the demand of the Fourth Industrial Revolution (4IR) era

Some Research Questions and Results of UC3M in the E-Madrid Excellence Network

32 slides.-- Contributed to: 2010 IEEE Global Engineering Education Conference (EDUCON), Madrid, Spain, 14-16 April, 2010.-- Presented by C. Delgado Kloos.Proceedings of: 2010 IEEE Global Engineering Education Conference (EDUCON), Madrid, Spain, 14-16 April, 2010Universidad Carlos III de Madrid is one of the six main participating institutions in the eMadrid excellence network, as well as its coordinating partner. In this paper, the network is presented together with some of the main research lines carried out by UC3M. The remaining papers in this session present the work carried out by the other five universities in the consortium.The Excellence Network eMadrid, “Investigación y Desarrollo de Tecnologías para el e-Learning en la Comunidad de Madrid” is being funded by the Madrid Regional Government under grant No. S2009/TIC-1650. In addition, we acknowledge funding from the following research projects: iCoper: “Interoperable Content for Performance in a Competency-driven Society” (eContentPlus Best Practice Network No. ECP-2007-EDU-417007), Learn3: Hacia el Aprendizaje en la 3ª Fase (“Plan Nacional de I+D+I” TIN2008-05163/ TSI), Flexo: “Desarrollo de aprendizaje adaptativo y accesible en sistemas de código abierto” (AVANZA I+D, TSI-020301- 2008-19), España Virtual (CDTI, Ingenio 2010, CENIT, Deimos Space), SOLITE (CYTED 508AC0341), and “Integración vertical de servicios telemáticos de apoyo al aprendizaje en entornos residenciales” (Programa de creación y consolidación de grupos de investigación de la Universidad Carlos III de Madrid).Publicad

Collaborative Authoring of Adaptive Educational Hypermedia by Enriching a Semantic Wiki’s Output

This research is concerned with harnessing collaborative approaches for the authoring of Adaptive Educational Hypermedia (AEH) systems. It involves the enhancement of Semantic Wikis with pedagogy aware features to this end. There are many challenges in understanding how communities of interest can efficiently collaborate for learning content authoring, in introducing pedagogy to the developed knowledge models and in specifying user models for efficient delivery of AEH systems. The contribution of this work will be the development of a model of collaborative authoring which includes domain specification, content elicitation, and definition of pedagogic approach. The proposed model will be implemented in a prototype AEH authoring system that will be tested and evaluated in a formal education context

Using motivation derived from computer gaming in the context of computer based instruction

This paper was originally presented at the IEEE Technically Sponsored SAI Computing Conference 2016, London, 13-15 July 2016. Abstract— this paper explores how to exploit game based motivation as a way to promote engagement in computer-based instruction, and in particular in online learning interaction. The paper explores the human psychology of gaming and how this can be applied to learning, the computer mechanics of media presentation, affordances and possibilities, and the emerging interaction of playing games and how this itself can provide a pedagogical scaffolding to learning. In doing so the paper focuses on four aspects of Game Based Motivation and how it may be used; (i) the game player’s perception; (ii) the game designers’ model of how to motivate; (iii) team aspects and social interaction as a motivating factor; (iv) psychological models of motivation. This includes the increasing social nature of computer interaction. The paper concludes with a manifesto for exploiting game based motivation in learning

Adaptive intelligent personalised learning (AIPL) environment

As individuals the ideal learning scenario would be a learning environment tailored just for how we like to learn, personalised to our requirements. This has previously been almost inconceivable given the complexities of learning, the constraints within the environments in which we teach, and the need for global repositories of knowledge to facilitate this process. Whilst it is still not necessarily achievable in its full sense this research project represents a path towards this ideal.In this thesis, findings from research into the development of a model (the Adaptive Intelligent Personalised Learning (AIPL)), the creation of a prototype implementation of a system designed around this model (the AIPL environment) and the construction of a suite of intelligent algorithms (Personalised Adaptive Filtering System (PAFS)) for personalised learning are presented and evaluated. A mixed methods approach is used in the evaluation of the AIPL environment. The AIPL model is built on the premise of an ideal system being one which does not just consider the individual but also considers groupings of likeminded individuals and their power to influence learner choice. The results show that: (1) There is a positive correlation for using group-learning-paradigms. (2) Using personalisation as a learning aid can help to facilitate individual learning and encourage learning on-line. (3) Using learning styles as a way of identifying and categorising the individuals can improve their on-line learning experience. (4) Using Adaptive Information Retrieval techniques linked to group-learning-paradigms can reduce and improve the problem of mis-matching. A number of approaches for further work to extend and expand upon the work presented are highlighted at the end of the Thesis

Personalized content provision for virtual learning environments via the semantic web

In this paper we discuss how we may personalize e-learning along three distinct axes, namely: teaching and learning pedagogical philosophies, personalized educational processes to taste and the coordination of these processes during execution. In doing so we are concerned with supporting users' choices of educational options in course delivery via the Web services. In the work presented here, we assess the practical needs of learners and tutors and then the main research problems are analysed from a practical and pragmatic point of view. Following on from this the design of an intelligent virtual learning environment (VLE) is described to map a set of extensive didactic paradigms, which is represented by a system model and architecture. In this system, the semantic information of learning units and processes (e.g. the relationships among units) can be described and integrated in terms of various requirements of our users. As a result instructional materials with a wide variety of executional options and conditions can be built. Furthermore, through reassembling the semantics of learning content according to users' new demands, our target audience (both student and content deliverers) can change their particular educational experience dynamically. This VLE can provide high-powered pedagogy-layered personalization - thus enabling new managed e-learning Web services and applications

SEMAG: A Novel Semantic-Agent Learning Recommendation Mechanism for Enhancing Learner-System Interaction

In this paper, we present SEMAG - a novel semantic-agent learning recommendation mechanism which utilizes the advantages of instructional Semantic Web rules and multi-agent technology, in order to build a competitive and interactive learning environment. Specifically, the recommendation-making process is contingent upon chapter-quiz results, as usual; but it also checks the students' understanding at topic-levels, through personalized questions generated instantly and dynamically by a knowledge-based algorithm. The learning space is spread to the social network, with the aim of increasing the interaction between students and the intelligent tutoring system. A field experiment was conducted in which the results indicated that the experimental group gained significant achievements, and thus it supports the use of SEMAG

Investigating heuristic evaluation as a methodology for evaluating pedagogical software: An analysis employing three case studies

This paper looks specifically at how to develop light weight methods of evaluating pedagogically motivated software. Whilst we value traditional usability testing methods this paper will look at how Heuristic Evaluation can be used as both a driving force of Software Engineering Iterative Refinement and end of project Evaluation. We present three case studies in the area of Pedagogical Software and show how we have used this technique in a variety of ways. The paper presents results and reflections on what we have learned. We conclude with a discussion on how this technique might inform on the latest developments on delivery of distance learning. © 2014 Springer International Publishing