4 resultados para Learning management systems

em Greenwich Academic Literature Archive - UK


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A cross-domain workflow application may be constructed using a standard reference model such as the one by the Workflow Management Coalition (WfMC) [7] but the requirements for this type of application are inherently different from one organization to another. The existing models and systems built around them meet some but not all the requirements from all the organizations involved in a collaborative process. Furthermore the requirements change over time. This makes the applications difficult to develop and distribute. Service Oriented Architecture (SOA) based approaches such as the BPET (Business Process Execution Language) intend to provide a solution but fail to address the problems sufficiently, especially in the situations where the expectations and level of skills of the users (e.g. the participants of the processes) in different organisations are likely to be different. In this paper, we discuss a design pattern that provides a novel approach towards a solution. In the solution, business users can design the applications at a high level of abstraction: the use cases and user interactions; the designs are documented and used, together with the data and events captured later that represents the user interactions with the systems, to feed an intermediate component local to the users -the IFM (InterFace Mapper) -which bridges the gaps between the users and the systems. We discuss the main issues faced in the design and prototyping. The approach alleviates the need for re-programming with the APIs to any back-end service thus easing the development and distribution of the applications

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Common Learning Management Systems (for example Moodle [1] and Blackboard [2]) are limited in the amount of personalisation that they can offer the learner. They are used widely and do offer a number of tools for instructors to enable them to create and manage courses, however, they do not allow for the learner to have a unique personalised learning experience. The e-Learning platform iLearn offers personalisation for the learner in a number of ways and one way is to offer the specific learning material to the learner based on the learner's learning style. Learning styles and how we learn is a vast research area. Brusilovsky and Millan [3] state that learning styles are typically defined as the way people prefer to learn. Examples of commonly used learning styles are Kolb Learning Styles Theory [4], Felder and Silverman Index of Learning Styles [5], VARK [6] and Honey and Mumford Index of Learning Styles [7] and many research projects (SMILE [8], INSPIRE [9], iWeaver [10] amonst others) attempt to incorporate these learning styles into adaptive e-Learning systems. This paper describes how learning styles are currently being used within the area of adaptive e-Learning. The paper then gives an overview of the iLearn project and also how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile.

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In this paper we look at ways of delivering and assessing learning on database units offered on higher degree programmes (MSc) in the School of Computing and Mathematical Sciences at the University of Greenwich. Of critical importance is the teaching methods employed for verbal disposition, practical laboratory exercises and a careful evaluation of assessment methods and assessment tools in view of the fact that databases involve not only database design but also use of practical tools, such as database management systems (DBMSs) software, human designers, database administrators (DBA) and end users. Our goal is to clearly identify potential key success factors in delivering and assessing learning in both practical and theoretical aspects of database course units.

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Kurzel(2004) points out that researchers in e-learning and educational technologists, in a quest to provide improved Learning Environments (LE) for students are focusing on personalising the experience through a Learning Management System (LMS) that attempts to tailor the LE to the individual (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez,2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman; 2003). According to Kurzel (2004) this tailoring can have an impact on content and how it’s accessed; the media forms used; method of instruction employed and the learning styles supported. This project is aiming to move personalisation forward to the next generation, by tackling the issue of Personalised e-Learning platforms as pre-requisites for building and generating individualised learning solutions. The proposed development is to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system’s processing engine. This paper will discuss some of our early work and ideas.