Pedagogically informed metadata content and structure for learning and teaching

In order to be able to search, compare, gap analyse, recommend, and visualise learning objects, learning resources, or teaching assets, the metadata structure and content must be able to support pedagogically informed reasoning, inference, and machine processing over the knowledge representations. In this paper, we present the difficulties with current metadata standards in education: Dublin Core educational version and IEEELOM, using examples drawn from the areas of e-learning, institutional admissions, and learners seeking courses. The paper suggests expanded metadata components based on an e-learning system engineering model to support pedagogically informed interoperability. We illustrate some examples of the metadata relevant to competency in the nurse training domain

A conceptual framework for developing explorative e-learning strategy using ontology-based knowledge management

This paper presents a conceptual framework for developing explorative e-learning strategy using ontology-based knowledge management. It conducts a comprehensive analysis of the applicability of ontologies in management of knowledge, with a particular reference to the development of explorative e-learning environments for enhancing an efficient use and reuse of available information and knowledge in e-learning, leading to a better understanding of the main issues for developing effective explorative e-learning strategies in an e-learning environment

Семантическое аннотирование текстовых документов на основе иерархической радиально-базисной нейронной сети

The hierarchical radial basis function neural network with a multi-layered architecture is proposed. This neural network is used for extracting knowledge from textual sources with the maximum number of relevant attributes for each object and assigns it to the selected class of ontology.В работе предложена иерархическая радиально-базисная нейронная сеть с многослойной архитектурой, которая используется для извлечения знаний из текстовых источников с учетом максимального количества релевантных признаков каждого объекта и отнесения его к выбранному классу онтологии.В роботі запропоновано ієрархічну радіально-базисну нейронну мережу з багатошаровою архітектурою, яка використовується для видобування знань із текстових джерел із урахуванням максимальної кількості релевантних ознак кожного об’єкта та віднесення його до обраного класу онтології

Семантическое аннотирование текстовых документов на основе иерархической радиально-базисной нейронной сети

The hierarchical radial basis function neural network with a multi-layered architecture is proposed. This neural network is used for extracting knowledge from textual sources with the maximum number of relevant attributes for each object and assigns it to the selected class of ontology.В работе предложена иерархическая радиально-базисная нейронная сеть с многослойной архитектурой, которая используется для извлечения знаний из текстовых источников с учетом максимального количества релевантных признаков каждого объекта и отнесения его к выбранному классу онтологии.В роботі запропоновано ієрархічну радіально-базисну нейронну мережу з багатошаровою архітектурою, яка використовується для видобування знань із текстових джерел із урахуванням максимальної кількості релевантних ознак кожного об’єкта та віднесення його до обраного класу онтології

Metastandard für den internationalen Austausch von MOOCs – der MOOChub als erster Prototyp

Der MOOChub ist eine Webseite, die weit über 700 Massive Open Online Courses (MOOCs) aus dem deutschsprachigen Raum von insgesamt neun unterschiedlichen Partner:innen listet. Damit eine solche Seite automatisiert aufgebaut werden kann, ist es notwendig, dass alle Partner:innen die Metadaten der Kurse in gleicher Weise beschreiben und verfügbar machen. Dieser Artikel beschreibt zunächst die Entstehung der Idee eines gemeinsamen Standards und wie dieser im Anschluss entwickelt worden ist. Das Ergebnis ist einerseits ein offen lizenzierter Quasi-Standard, der sich an üblichen Standards orientiert, und ein erster Prototyp, der sogenannte MOOChub, auf dem nun alle Kurse auffindbar und durchsuchbar sind. Abschließend wird über die nächsten möglichen und auch notwendigen Entwicklungen berichtet, die die Schnittstelle weiter optimieren sollen

Repositories of Open Educational Resources: An Assessment of Reuse and Educational Aspects

This article provides an overview of the current state of repositories of open educational resources (ROER) in higher education at international level. It analyses a series of educational indicators to determine whether ROER can meet the specific needs of the education context, and to clarify understanding of the reuse of open educational resources (OER) provided by ROER. The aim of the study is to assess ROER by combining these two perspectives, and to form a basis for discussion among the universities that are responsible for these repositories. The method was based on content analysis and consisted of two phases: an exploration of international sources, and an analysis of 110 ROER using the proposed set of indicators. The results focus on data from the analysis of ROER websites and some models of good practices. They are presented according to three core dimensions for evaluating ROER: general factors to establish types of ROER, a focus on drivers for OER reuse, and a focus on educational aspects. It was found that most of the ROER that included one or more of the proposed reuse indicators were created exclusively for educational resources. Educational aspects are not yet firmly embedded into ROER. The few repositories that seem to have successfully included them are those that provide other educational metadata and use educational standards

Supporting the discoverability of open educational resources

Open Educational Resources (OERs), now available in large numbers, have a considerable potential to improve many aspects of society, yet one of the factors limiting this positive impact is the difficulty to discover them. This study investigates and proposes strategies to better support educators in discovering OERs, mainly focusing on secondary education. The literature suggests that the effectiveness of existing search systems could be improved by supporting high-level and domain-oriented tasks. Hence a preliminary taxonomy of discovery-related tasks was developed, based on the analysis of the literature, interpreted through Information Foraging Theory. This taxonomy was empirically evaluated with a few experienced educators, to preliminary identify an interesting class of Query By Examples (QBE) expansion by similarity tasks, which avoids the need to decompose natural high-level tasks in a complex sequence of sub-tasks. Following the Design Science Research methodology, three prototypes to support as well as to refine those tasks were iteratively designed, implemented, and evaluated involving an increasing number of educators in usability oriented studies. The resulting high-level and domain-oriented blended search/recommendation strategy, transparently replicates Google searches in specialized networks, and identifies similar resources with a QBE strategy. It makes use of a domain-oriented similarity metric based on shared schema.org/LRMI alignments to educational frameworks, and clusters results in expandable classes of comparable degree of similarity. The summative evaluation shows that educators appreciate this exploratory-oriented strategy because – balancing similarity and diversity – it supports their high-level tasks, such as lesson planning and personalization of education

Experiences with GRAIL::Learning Design support in .LRN

The IMS-LD specification allow the transcription of almost any pedagogical model in a "Unit of Learning" (UoL), which is a package where contents and methodology are combined together in order to be deployed in a compliant software. Making use of GRAIL as the supporting tool inside the .LRN Learning Management System, this paper presents two real experiences of use where IMS-LD has been used to deploy pedagogical models with different levels of complexity