Accessibility and adaptability of learning objects: responding to metadata, learning patterns and profiles of needs and preferences

The case for learning patterns as a design method for accessible and adaptable learning objects is explored. Patterns and templates for the design of learning objects can be derived from successful existing learning resources. These patterns can then be reused in the design of new learning objects. We argue that by attending to criteria for reuse in the definition of these patterns and in the subsequent design of new learning objects, those new resources can be themselves reusable and also adaptable to different learning contexts. Finally, if the patterns identified can be implemented as templates for standard authoring tools, the design of effective, reusable and adaptable resources can be made available to those with limited skills in multimedia authoring and result in learning resources that are more widely accessible

Building communities for the exchange of learning objects: theoretical foundations and requirements

In order to reduce overall costs of developing high-quality digital courses (including both the content, and the learning and teaching activities), the exchange of learning objects has been recognized as a promising solution. This article makes an inventory of the issues involved in the exchange of learning objects within a community. It explores some basic theories, models and specifications and provides a theoretical framework containing the functional and non-functional requirements to establish an exchange system in the educational field. Three levels of requirements are discussed. First, the non-functional requirements that deal with the technical conditions to make learning objects interoperable. Second, some basic use cases (activities) are identified that must be facilitated to enable the technical exchange of learning objects, e.g. searching and adapting the objects. Third, some basic use cases are identified that are required to establish the exchange of learning objects in a community, e.g. policy management, information and training. The implications of this framework are then discussed, including recommendations concerning the identification of reward systems, role changes and evaluation instruments

Systematising Learning and Research Information

This paper considers the ways in which information of relevance to the learning and research communities is organised and used. It contends that there is considerable overlap between the different types of online resources and information currently available within education. It describes some of the structured environments and data stores that have emerged in recent years, along with standards which are attempting to define the properties of discrete learning objects, through the specification of Learning Object Metadata (LOM). The paper contends that current developments of structured learning environments such as Managed and Virtual Learning Environments (MLEs and VLEs) are occurring on the whole in parallel to resource data stores, such as information gateways and portals. This discrepancy has arisen in part because these developments have occurred independently of one another and in part because there has to date been no rigorous definition of the underlying theoretical models. Furthermore, it argues that these predefined structured environments are unlikely to be sufficient to meet the information needs of users in different contexts. The paper goes on to describe an information toolkit, which provides a way of systematising information handling in learning and research, which helps users articulate information plans within specific contexts. The paper concludes with a description of two case studies which illustrate how this toolkit can be used

Moodle for Italian Astronomy Olympiad

Italian Astronomy Olympiads are organized by Societ\`a Italiana di Astronomia in collaboration with Istituto Nazionale di Astrofisica (INAF) and they are included in the MIUR's upgrading program for educational excellence. The Presidency of the National Olympic Committee based at Osservatorio Astronomico di Brera (INAF). Olympiads are aimed to italian high school students: the winners of the national stage participate to International Astronomy Olympiad (IAO). IAO officially born in 1996 at the initiative of Euro-Asian Astronomical Society. They are held every year in autumn, in a different country, and they see the regular participation of over twenty national teams of the European and Asian area, including Italy. Today the didactical support is limited to the little material provided by Italian Committee on the italian official site. In order to supply this lack, we projected a didatcical platform, developed with Moodle, that it could propose astronomical learning pages like glossary's voices and a lot of exercises about every subject

Adaptive course sequencing for personalization of learning path using neural network

Advancements in technology have led to a paradigm shift fromtraditional to personalized learning methods with varied implementationstrategies. Presenting an optimal personalized learning path in aneducational hypermedia system is one of the strategies that is important inorder to increase the effectiveness of a learning session for each student.However, this task requires much effort and cost particularly in definingrules for the adaptation of learning materials. This research focuses onthe adaptive course sequencing method that uses soft computingtechniques as an alternative to a rule-based adaptation for an adaptivelearning system. The ability of soft computing technique in handlinguncertainty and incompleteness of a problem is exploited in the study. Inthis paper we present recent work concerning concept-based classificationof learning object using artificial neural network (ANN). Self OrganizingMap (SOM) and Back Propagation (BP) algorithm were employed todiscover the connection between the domain concepts contained in thelearning object and the learner’s learning need. The experiment resultshows that this approach is assuring in determining a suitable learningobject for a particular student in an adaptive and dynamic learning environment

Automatic validation of learning object compositions

Course construction using reusable learning objects is becoming ever more popular due to its’ efficiency. The course creator who uses this methodology may face problems due to the fact that he or she is not as intimately involved in the creation of every element of the course. In this paper we discuss one such problem faced by course creator known as “the competency gap”. Here, we define the competency gap, explain how it can be identified and suggest ways of correcting the problem

A novel algorithm for dynamic student profile adaptation based on learning styles

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.E-learning recommendation systems are used to enhance student performance and knowledge by providing tailor- made services based on the students’ preferences and learning styles, which are typically stored in student profiles. For such systems to remain effective, the profiles need to be able to adapt and reflect the students’ changing behaviour. In this paper, we introduce new algorithms that are designed to track student learning behaviour patterns, capture their learning styles, and maintain dynamic student profiles within a recommendation system (RS). This paper also proposes a new method to extract features that characterise student behaviour to identify students’ learning styles with respect to the Felder-Silverman learning style model (FSLSM). In order to test the efficiency of the proposed algorithm, we present a series of experiments that use a dataset of real students to demonstrate how our proposed algorithm can effectively model a dynamic student profile and adapt to different student learning behaviour. The results revealed that the students could effectively increase their learning efficiency and quality for the courses when the learning styles are identified, and proper recommendations are made by using our method

OASEARCH: Modelo de aplicación basado en web semántica para la búsqueda de objetos de aprendizaje mediante perfilado de consultas

Uno de los aspectos que determina la calidad de un Sistema Educativo Basado en la Web es la manera en que este proporciona a los estudiantes los objetos de aprendizaje que mejor se adaptan a sus condiciones específicas -- Es por lo anterior que se hace necesario contar con mecanismos de búsqueda para estos objetos que puedan ser usados fácilmente por la aplicación o por los usuarios de la misma y que entreguen los resultados más relevantes posibles en un contexto determinado -- Múltiples mecanismos se han propuesto para la búsqueda de recursos digitales en la web -- El enfoque fundamental de recuperación de la información ha sido utilizado por muchos años con bastante éxito pero con el advenimiento de las tecnologías que componen lo que se conoce como La Web Semántica es posible definir nuevas representaciones para los datos que permiten obtener una mayor precisión y relevancia de los resultados obtenidos -- El presente documento presenta un nuevo enfoque para la construcción de motores de búsqueda para objetos de aprendizaje basado en La Web Semántica que se apoya en la definición previa o perfilado de consultas de una manera desacoplada de la aplicación -- Con este enfoque es posible construir Conceptos de Búsqueda que son especificados en una Ontología de Dominio de tal manera que luego puede ser utilizada por la aplicación para entregar sus resultados en un entorno distribuido de repositorios RDF que se basen en el estándar LOM para la descripción de metadato