Designing learning object repositories : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science in Information Sciences at Massey University

Learning object repositories are expanding rapidly into the role of independent educational systems that not only are a supplement to a traditional way of learning, but also allow users to search, exchange and re-use learning objects. The intention of this innovative technology is to have such repositories to collect a database of learning objects catalogued by the learning content management system. However, for users to perform an efficient search, these learning objects would need to use metadata standards or specifications to describe their properties. For learning objects stored within the repositories, metadata standards are often used to descibe them so users of the respositories are able to find the accurate resources they required, hence metadata standards are important elements of any learning object repository. In this paper, a courseware example is used to demonstrate how to define a set of characteristics that we want to describe for our courseware, and attempt to map the data schema in the database with the available metadata standards. The outcome is to identify a set of metadata elements that would fully describe our learning objects stored within the learning object repository, and these metadata elements will also assist instructors to create adaptable courseware that can be reused by different instructors. Metadata standard is known as a critical element for the management of learning objects, not only will it increase the accuracy of the search results, it will also provide more relevant and descriptive information about the learning objects to the searchers

Learning object metadata surrogates in search result interfaces: user evaluation, design and content

The purpose of this research was to evaluate user interaction with learning object metadata surrogates both in terms of content and presentation. The main objectives of this study were: (1) to review the literature on learning object metadata and user-centred evaluation of metadata surrogates in the context of cognitive information retrieval (including user-centred relevance and usability research); (2) to develop a framework for the evaluation of user interaction with learning object metadata surrogates in search result interfaces; (3) to investigate the usability of metadata surrogates in search result interfaces of learning object repositories (LORs) in terms of various presentation aspects (such as amount of information, structure and highlighting of query terms) as a means for facilitating the user relevance judgment process; (4) to investigate in-depth the type of content that should be included in learning object metadata surrogates in order to facilitate the process of relevance judgment; (5) to provide a set of recommendations—guidelines for the design of learning object metadata surrogates in search result interfaces both in terms of content and presentation. [Continues.

Detecting Communities and Analysing Interactions with Learning Objects in Online Learning Repositories

The widespread use of online learning object repositories has raised the need of studies that assess the quality of their contents, and their user’s performance and engagement. The present research addresses two fundamental problems that are central to that need: the need to explore user interaction with these repositories and the detection of emergent communities of users. The current dissertation approaches those directions through investigating and mining the Khan Academy repository as a free, open access, popular online learning repository addressing a wide content scope. It includes large numbers of different learning objects such as instructional videos, articles, and exercises. In addition to a large number of users. Data was collected using the repository’s public application programming interfaces combined with Web scraping techniques to gather data and user interactions. Different research activities were carried out to generate useful insights out of the gathered data. We conducted descriptive analysis to investigate the learning repository and its core features such as growth rate, popularity, and geographical distribution. A number of statistical and quantitative analysis were applied to examine the relation between the users’ interactions and different metrics related to the use of learning objects in a step to assess the users’ behaviour. We also used different Social Network Analysis (SNA) techniques on a network graph built from a large number of user interactions. The resulting network consisted of more than 3 million interactions distributed across more than 300,000 users. The type of those interactions is questions and answers posted on Khan Academy’s instructional videos (more than 10,000 video). In order to analyse this graph and explore the social network structure, we studied two different community detection algorithms to identify the learning interactions communities emerged in Khan Academy then we compared between their effectiveness. After that, we applied different SNA measures including modularity, density, clustering coefficients and different centrality measures in order to assess the users’ behaviour patterns and their presence. Using descriptive analysis, we discovered many characteristics and features of the repository. We found that the number of learning objects in Khan Academy’s repository grows linearly over time, more than 50% of the users do not complete the watched videos, and we found that the average duration for video lessons 5 to 10 minutes which aligns with the recommended duration in literature. By applying community detection techniques and social network analysis, we managed to identify learning communities in Khan Academy’s network. The size distribution of those communities found to follow the power-law distribution which is the case of many real-world networks. Those learning communities are related to more than one domain which means the users are active and interacting across domains. Different centrality measures we applied to focus on the most influential players in those communities. Despite the popularity of online learning repositories and their wide use, the structure of the emerged learning communities and their social networks remain largely unexplored. Our findings could be considered initial insights that may help researchers and educators in better understanding online learning repositories, the learning process inside those repositories, and learner behaviou

User Experience for Disabled Users in Open Educational Resources Websites

Open Educational Resources (OER) are digital materials for teaching-learning purpose released under an open license that are available through websites. In the last decade, some governments have encouraged the development and using of OER in order to contribute to the achievement of the right to education for everyone, a fundamental right included in The Universal Declaration of Human Rights. Besides, inclusion of people with disabilities is a global concern that need to be addressed in all living aspects including education.In this research we address the user experience in OER websites —considering the perspective of users with disabilities— in order to recognize possible barriers in web design. The conformance criteria considered for this reviewing are mandatory aspects of user experience in relation to Web accessibility and Web usability. &nbsp

OER in the Mobile Era: Content Repositories’ Features for Mobile Devices and Future Trends

Learning objects and open contents have been named in the Horizon reports from 2004 and 2010 respectively, predicting to have an impact in the short term due to the current trend of offering open content for free on the Web. OER repositories should adapt their features so their contents can be accessed from mobile devices. This paper summarizes recent trends in the creation, publication, discovery, acquisition, access, use and re-use of learning objects on mobile devices based on a literature review on research done from 2007 to 2012. From the content providers side, we present the results obtained from a survey performed on 23 educational repository owners prompting them to an- swer about their current and expected support on mobile devices. From the content user side, we identify features provided by the main OER repositories. Finally, we intro- duce future trends and our next contribution

Identification des caractéristiques des modèles de diffusion de contenus numériques : revue de littérature partie 1

Tiré de l'écran-titre (visionné le 27 juin 2017).Ce rapport de recherche a été produit par Gabriel Dumouchel, sous la direction de Thierry Karsenti, professeur en éducation à l'Université de Montréal et membre du Centre de recherche interuniversitaire sur la formation et la profession enseignante (CRIFPE). Il présente un état des lieux des dépôts de ressources d’enseignement et d’apprentissage (REA) que l'on trouve en milieu universitaire. Dans cette première partie du rapport, les auteurs présentent différents types de dépôts et décrivent de façon plus approfondie quatre dépôts parmi les plus actifs principalement en milieu universitaire

Model for democratisation of the contents hosted in MOOCs

Massive Online Open Courses (MOOCs) have emerged as a new educational tool in higher education, based on gratuity, massiveness and ubiquity. Essentially they suggest an evolution of the Open Learning Movement based on principles of reusing, revising, remixing and redistributing open educational resources (OER). However, in contrast with the content of OERs, content hosed in MOOCs tends to be paywalled and copyrighted, which restricts its reuse. Philosophically, the main problem with MOOCs is the inaccessibility and inadaptability of their resources, challenging democratic open access to knowledge. A number of authors and organisations consider it an ultimate necessity to open up MOOC resources. Therefore in this paper three strategies to open up MOOC contents are proposed: to deposit the materials in repositories of OER (ROER) as individual objects, to archive them in ROER in data packages as learning units or to convert them into OpenCourseWare (OCW) as self-taught courses