OER Development and Promotion. Outcomes of an International Research Project on the OpenCourseWare Model

In this paper, we describe the successful results of an international research project focused on the use of Web technology in the educational context. The article explains how this international project, funded by public organizations and developed over the last two academic years, focuses on the area of open educational resources (OER) and particularly the educational content of the OpenCourseWare (OCW) model. This initiative has been developed by a research group composed of researchers from three countries. The project was enabled by the Universidad Politécnica de Madrid OCW Office�s leadership of the Consortium of Latin American Universities and the distance education know-how of the Universidad Técnica Particular de Loja (UTPL, Ecuador). We give a full account of the project, methodology, main outcomes and validation. The project results have further consolidated the group, and increased the maturity of group members and networking with other groups in the area. The group is now participating in other research projects that continue the lines developed her

Hybrid human-AI driven open personalized education

Attaining those skills that match labor market demand is getting increasingly complicated as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Furthermore, people's interests in gaining knowledge pertaining to their personal life (e.g., hobbies and life-hacks) are also increasing dramatically in recent decades. In this situation, anticipating and addressing the learning needs are fundamental challenges to twenty-first century education. The need for such technologies has escalated due to the COVID-19 pandemic, where online education became a key player in all types of training programs. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open/free educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. Therefore, this thesis aims to contribute to the literature about the utilization of (open and free-online) educational resources toward goal-driven personalized informal learning, by developing a novel Human-AI based system, called eDoer. In this thesis, we discuss all the new knowledge that was created in order to complete the system development, which includes 1) prototype development and qualitative user validation, 2) decomposing the preliminary requirements into meaningful components, 3) implementation and validation of each component, and 4) a final requirement analysis followed by combining the implemented components in order develop and validate the planned system (eDoer). All in all, our proposed system 1) derives the skill requirements for a wide range of occupations (as skills and jobs are typical goals in informal learning) through an analysis of online job vacancy announcements, 2) decomposes skills into learning topics, 3) collects a variety of open/free online educational resources that address those topics, 4) checks the quality of those resources and topic relevance using our developed intelligent prediction models, 5) helps learners to set their learning goals, 6) recommends personalized learning pathways and learning content based on individual learning goals, and 7) provides assessment services for learners to monitor their progress towards their desired learning objectives. Accordingly, we created a learning dashboard focusing on three Data Science related jobs and conducted an initial validation of eDoer through a randomized experiment. Controlling for the effects of prior knowledge as assessed by the pretest, the randomized experiment provided tentative support for the hypothesis that learners who engaged with personal eDoer recommendations attain higher scores on the posttest than those who did not. The hypothesis that learners who received personalized content in terms of format, length, level of detail, and content type, would achieve higher scores than those receiving non-personalized content was not supported as a statistically significant result

Developing sustainable business models for institutions’ provision of open educational resources: Learning from OpenLearn users’ motivations and experiences

Universities across the globe have, for some time, been exploring the possibilities for achieving public benefit and generating business and visibility through releasing and sharing open educational resources (OER). Many have written about the need to develop sustainable and profitable business models around the production and release of OER. Downes (2006), for example, has questioned the financial sustainability of OER production at scale. Many of the proposed business models focus on OER’s value in generating revenue and detractors of OER have questioned whether they are in competition with formal education. This paper reports on a study intended to broaden the conversation about OER business models to consider the motivations and experiences of OER users as the basis for making a better informed decision about whether OER and formal learning are competitive or complementary with each other. The study focused on OpenLearn - the Open University’s (OU) web-based platform for OER, which hosts hundreds of online courses and videos and is accessed by over 3,000,000 users a year. A large scale survey and follow-up interviews with OpenLearn users worldwide revealed that university provided OER can offer learners a bridge to formal education, allowing them to try out a subject before registering on a formal course and to build confidence in their abilities as learners. In addition, it was found that using OER during formal paid-for study can improve learners’ performance and self-reliance, leading to increased retention and satisfaction with the learning experience

Open educational resources for all? Comparing user motivations and characteristics across The Open University’s iTunes U channel and OpenLearn platform.

With the rise in access to mobile multimedia devices, educational institutions have exploited the iTunes U platform as an additional channel to provide free educational resources with the aim of profile-raising and breaking down barriers to education. For those prepared to invest in content preparation, it is possible to produce interactive, portable material that can be made available globally. Commentators have questioned both the financial implications for platform-specific content production, and the availability of devices for learners to access it (Osborne, 2012). The Open University (OU) makes its free educational resources available on iTunes U and via its web-based open educational resources (OER) platform, OpenLearn. The OU’s OER on iTunes U reached the 60 million download mark in 2013; its OpenLearn platform boasts 27 million unique visitors since 2006. This paper reports the results of a large-scale study of users of the OU’s iTunes U channel and OpenLearn platform. A survey of several thousand users revealed key differences in demographics between those accessing OER via the web and via iTunes U. In addition, the data allowed comparison between three groups: formal learners, informal learners and educators. The study raises questions about whether university-provided OER meet the needs of users and makes recommendations for how content can be modified to suit their needs. As the publishing of OER becomes core to business, we reflect on reasons why understanding users’ motivations and demographics is vital, allowing for needs-led resource provision and content that is adapted to best achieve learner satisfaction, and to deliver institutions’ social mission

Novel Datasets, User Interfaces and Learner Models to Improve Learner Engagement Prediction on Educational Videos

With the emergence of Open Education Resources (OERs), educational content creation has rapidly scaled up, making a large collection of new materials made available. Among these, we find educational videos, the most popular modality for transferring knowledge in the technology-enhanced learning paradigm. Rapid creation of learning resources opens up opportunities in facilitating sustainable education, as the potential to personalise and recommend specific materials that align with individual users’ interests, goals, knowledge level, language and stylistic preferences increases. However, the quality and topical coverage of these materials could vary significantly, posing significant challenges in managing this large collection, including the risk of negative user experience and engagement with these materials. The scarcity of support resources such as public datasets is another challenge that slows down the development of tools in this research area. This thesis develops a set of novel tools that improve the recommendation of educational videos. Two novel datasets and an e-learning platform with a novel user interface are developed to support the offline and online testing of recommendation models for educational videos. Furthermore, a set of learner models that accounts for the learner interests, knowledge, novelty and popularity of content is developed through this thesis. The different models are integrated together to propose a novel learner model that accounts for the different factors simultaneously. The user studies conducted on the novel user interface show that the new interface encourages users to explore the topical content more rigorously before making relevance judgements about educational videos. Offline experiments on the newly constructed datasets show that the newly proposed learner models outperform their relevant baselines significantly

The Universal Primer - An open source solution for archiving, organizing and streaming live lectures

Many disparate projects providing open access to educational videos are currently available or under development. These projects lack a unifying interface for accessing content, employ differing content licenses, and provide little or no infrastructure for user-contribution or live teaching. The goal of the Universal Primer is to address these problems, and allow anyone, anywhere, to teach or learn anything that can be reasonably taught or learned through a computer. The Universal Primer is : • A fully open source solution for streaming live lectures. • A Wikipedia-like website for uploading and organizing open-licensed community-contributed educational material. Relevance: The Universal Primer is an attempt at building a global educational network that allows teacher's and students to connect across the globe. Submission Category: CDIO Project demonstration session Keywords – online, video, streaming, community, open-sourc

Enhancing curriculum design and delivery with OER

This paper reports on the key findings from the EVOL-OER project which aims to develop a deeper understanding of the reuse of open educational resources (OERs) by academics in Higher Education Institutions (HEIs). This paper builds on the JISC OER Impact study by exploring and expanding on the Ratified quadrant of the study’s landscape of reuse framework (White & Manton, 2011). This paper puts forward a different four-quadrant diagram called ‘OER-enhanced curriculum’ to illustrate different approaches adopted by academics to embedding OER into curriculum design and delivery. Key issues in relation to motivation and challenges in reusing OER are discussed

Design of an E-learning system using semantic information and cloud computing technologies

Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí

System Design and Architecture of an Online, Adaptive, and Personalized Learning Platform

The authors propose that personalized learning can be brought to traditional and nontraditional learners through a new type of asynchronous learning platform called Guided Learning Pathways (GLP). The GLP platform allows learners to intelligently traverse a vast field of learning resources, emphasizing content only of direct relevance to the learner and presenting it in a way that matches the learner’s pedagogical preference and contextual interests. GLP allows learners to advance towards individual learning goals at their own pace, with learning materials catered to each learner’s interests and motivations. Learning communities would support learners moving through similar topics. This report describes the software system design and architecture required to support Guided Learning Pathways. The authors provide detailed information on eight software applications within GLP, including specific learning benefits and features of each. These applications include content maps, learning nuggets, and nugget recommendation algorithms. A learner scenario helps readers visualize the functionality of the platform. To describe the platform’s software architecture, the authors provide conceptual data models, process flow models, and service group definitions. This report also provides a discussion on the potential social impact of GLP in two areas: higher education institutions and the broader economy