Catálogo de publicaciones - libros

The increasing popularity of the move to e-learning or webbased education throughout the world has not only accompanied advances in information technology, but has brought about a recognition of the importance of the need for teachers to keep pace with changes in teaching and learning in areas of organisation, curriculum, infrastructure and pedagogy. Constructivism has been an underlying pedagogy that has influenced education since the middle of the twentieth century and continues to form an important foundation for e-learning. It continues to guide the move to help students acquire the higher level cognitive abilities of comprehension, application, analysis, evaluation and hypothesis creation. This chapter provides a brief overview of the changes in teaching and learning including the latest ideas, theories and technologies being applied in web-based education world-wide.

When instructional designers design online learning environments, they, like all other designers, call on prior knowledge and experience [1]. They call to mind previous solutions and strategies they have used, have experienced, or have seen that fit the particular constraints of the current situation [2]. These previous experiences play a central role in specifying the structure, contents and delivery strategies. Consequently, if the pedagogical component of the design is not consciously considered and planned, the instructional designer tends to incorporate his/her own model of learning into the environment. This may be inappropriate and even conflict with the learning processes which are intended to be supported by Information and Communication Technologies (ICT). Furthermore, the lack of an overall pedagogical strategy implies an absence of a consistent and adequate educational approach throughout the whole online learning environment [3].

Increasing numbers of medical schools in Australia and overseas have moved away from didactic teaching methodologies and embraced problem-based learning (PBL) to improve clinical reasoning skills and communication skills as well as to encourage self-directed lifelong learning. In January 2005, the first cohort of students entered the new MBBS program at the Griffith University School of Medicine, Gold Coast, to embark upon an exciting, fully integrated curriculum using PBL, combining electronic delivery, communication and evaluation systems incorporating cognitive principles that underpin the PBL process. This chapter examines the educational philosophies and design of the e-learning environment underpinning the processes developed to deliver, monitor and evaluate the curriculum. Key initiatives taken to promote student engagement and innovative and distinctive approaches to student learning at Griffith promoted within the conceptual model for the curriculum are (a) Student engagement, (b) Pastoral care, (c) Staff engagement, (d) Monitoring and (e) Curriculum/ Program Review.

Educational resources available on the Web are invaluable learning objects that should not only be accessible, sharable and informative, but also reusable, constructive, and responsive to various pedagogical aspects. Using “Ontology”, the knowledge representation core of the Semantic Web, to organize, personalize, and publish learning resources and to discover, generate and compose learning objects has been widely proposed. In response to the diverse education needs, especially learning on the Web, this chapter addresses the issues and methodologies in the design and construction of education ontology and discusses the necessities of such an education ontology that can help retrieving, organizing, and recommending educational resources for personalized learning. Follow a systematic ontology construction approach, the design and implementation of a Personalized Education Ontology (PEOnto) will demonstrate the flexibilities of ontology usages in performing different education tasks as well as enhancing system extensibilities and exchangeabilities.

Web-based education (WBE) has seen in recent years a significant increase both in its functionality as well as possible scenarios. After a first stage in which these systems offered mainly content management and course management capabilities, systems now offer solutions that cover pedagogical aspects such as activity sequencing. This chapter presents several approaches to the problem of adaptive sequencing. They are representative of the main initiatives for defining sequences of learning units that can be adapted to different users, with different capabilities and needs. All of them have some graphical background, but they focus on different issues use of well-known tools, use of simple metaphors like graphs, etc. The main two initiatives of standardization related to the sequencing problem (IMS Simple Sequencing and IMS Learning Design) are also examined. Finally, two approaches to social sequencing, an emerging trend inspired by the behaviour of social insects, are depicted.

The history of MUDs (multiuser domains or dungeons) goes back to the 1970s. Primarily this is a history of role-playing games and textbased virtual realities. As the decades have passed, MUDs increasingly have been developed and deployed for a wide range of applications in education and the Science of Learning. As opposed to an historical recounting of the development of MUDs, this chapter describes the evolution of MUDs as they have influenced education and learning, from simple meeting and discussion places, to simulated learning spaces, to the current state of the art, which is Immersive Virtual Environments (IVEs) for Education.

In this chapter, the key elements to facilitate success of an educational shift to learning within the middle schooling paradigm have been discussed. The aim of middle schooling at Kings Christian College is to provide a balanced and holistic education that meets the spiritual needs of all students as they grow to take their place in society. Effective middle schools provide a safe, supportive learning community and pastoral care is the umbrella under which all of the positive outcomes of middle schooling are achieved. This nurturing of young people according to an asset promotion paradigm, helps them to develop self-confidence, self-esteem and the capacity to contribute to the community.

This chapter aims to provide an up-to-date snapshot of the current state of research and applications of Data Mining methods in e-learning. The cross-fertilization of both areas is still in its infancy, and even academic references are scarce on the ground, although some leading education-related publications are already beginning to pay attention to this new field. In order to offer a reasonable organization of the available bibliographic information according to different criteria, firstly, and from the Data Mining practitioner point of view, references are organized according to the type of modeling techniques used, which include: Neural Networks, Genetic Algorithms, Clustering and Visualization Methods, Fuzzy Logic, Intelligent agents, and Inductive Reasoning, amongst others. From the same point of view, the information is organized according to the type of Data Mining problem dealt with: clustering, classification, prediction, etc.

As mentioned elsewhere in this book, e-learning offers “a new context for education where large amounts of information describing the continuum of the teaching–learning interactions are endlessly generated and ubiquitously available”. But raw information by itself may be of no help to any of the e-learning actors. The use of Data Mining methods to extract knowledge from this information can, therefore, be an adequate approach to follow in order to use the obtained knowledge to fit the educational proposal to the students’ needs and requirements. This chapter provides a case study in which several advanced Data Mining techniques are employed to extract different types of knowledge from virtual campus data concerning students system usage behaviour. The diverse palette of Data Mining problems addressed here include data clustering and visualization, outlier detection, classification, feature selection, and rule extraction. They concern diverse e-learning problems, such as the characterization of atypical students’ behaviour and the prediction of students’ performance.

A limitation of future development is the lack of ability to use technical equipment. To avoid this problem it is necessary to concentrate on pedagogy of technology – how to teach and learn technology? The paper also tries to break down some attitudes in both sides of teaching technology. The problem is mainly based on the lack of conversation and understanding between two sciences: Technology and Pedagogy. The aim of this paper is to help this conversation to begin and continue – this acts as a transmitter between these sciences. Paper explains basic ideas of both sciences with such language that the other is able to understand.