Raising awareness of the accessibility challenges in mathematics MOOCs

MOOCs provide learning environments that make it easier for learners to study from anywhere, at their own pace and with open access to content. This has revolutionised the field of eLearning, but accessibility continues to be a problem, even more so if we include the complexity of the STEM disciplines which have their own specific characteristics. This work presents an analysis of the accessibility of several MOOC platforms which provide courses in mathematics. We attempt to visualise the main web accessibility problems and challenges that disabled learners could face in taking these types of courses, both in general and specifically in the context of the subject of mathematics

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

How to design for persistence and retention in MOOCs?

Design of educational interventions is typically carried out following a design cycle involving phases of investigation, conceptualization, prototyping, implementation, execution and evaluation. This cycle can be applied at different levels of granularity e.g. learning activity, module, course or programme. In this paper we consider an aspect of learner behavior that can be critical to the success of many MOOCs i.e. their persistence to study, and the related theme of learner retention. We reflect on the impact that consideration of these can have on design decisions at different stages in the design cycle with the aim of en-hancing MOOC design in relation to learner persistence and retention, with particular attention to the European context

FOREIGN EXPERIENCE AND UKRAINIAN REALITIES OF MASS OPEN ONLINE COURSES USE IN INTERNATIONAL EDUCATION AREA

The article deals with the problem of influence of information and communication technologies on the higher education development. The peculiarities and dynamics of the MOOC expansion in the international educational space are determined, the experience of MOOC usage in the conditions of transnational education has been analysed, and the MOOC functions in Ukrainian educational reality have been investigated. The following methods were used in research: content analysis of scientific literature to clarify the essence of the research main categories; online courses netnography for studying their specifics; questionnaire, statistical processing and graphical representation of the study results concerning the MOOC functions in domestic educational practices. The essence of the term “MOOC” is clarified, the concept of their construction as well as features of technological functioning is revealed. The history of MOOC development in foreign countries (USA, Australia, Japan, Europe) and Ukraine is analysed. MOOC emergence and expansion is associated with digital humanities development and digital humanistic pedagogy establishment in the international educational space. The research results, which define the MOOC functions in the Ukraine educational practices, namely, ensuring openness, enriching the content of learning, individualization and inter-activation are characterized. Five main problems of the MOOC implementation are highlighted and investigated: 1) the presence of two different MOOC types; 2) the role of a teacher in MOOC; 3) participation of students in MOOC; 4) understanding and usage of the “mass” character of MOOC; 5) the boundary between the MOOC openness and control over them. Unprecedented popularity and opportunities for reaching the student audience have prompted international organizations and their education departments to initiate global forums to discuss the urgent economic, social, technological, psychological and pedagogical issues that arose during the MOOC introduction, as well as to adopt regulatory documents to ensure the quality of MOOC provision

Teaching Classics in the Digital Age

The papers and videos presented here are the result of the international conference 'Teaching Classics in the Digital Age' held online on the 15 and 16 June 2020. As digital media provide new possibilities for teaching and outreach in Classics, the conference 'Teaching Classics in the Digital Age' aimed at presenting current approaches to digital teaching and sharing best practices by bringing together different projects and practitioners from all fields of Classics (including Classical Archaeology, Greek and Latin Studies and Ancient History). Furthermore, it aimed at starting a discussion about principles, problems and the future of teaching Classics in the 21st century within and beyond its single fields

Designing MOOC:a shared view on didactical principles

The innovative impact of the paper can be highlighted by the following statements: 1. Applying the Group Concept Mapping, a non-traditional and power research methodology for objectively identifying the shared vision of a group of experts on MOOC didactical principles. 2. Defining MOOC didactical principles and their operationalisations in more concrete guidelines. 3. Formulating suggestions for combining xMOOC and cMOOC.Supported by European Commission, DG EAC, under the Erasmus+ Programm

Massive Open Online Courses for Business Learning: Key research, best practices and pathways to innovation

This book contains all you need to know about Massive Open Online Courses (MOOC) for the world of business! It was written by academics and business experts from across Europe as part of the BizMOOC project (bizmooc.eu). Inside you will find a detailed analysis of key literature in this field along with a range of practical tips for designing, implementing, evaluating and improving online learning at scale. Use this guide to understand the MOOC potential for you and your organisation!BizMOOC (2016-9) was a Knowledge Alliance project funded by the European Union (Erasmus+ / Key Action 2 / Knowledge Alliance; 562286-EPP-1-2015-1-AT-EPPKA2-KA). The European Commission support for the production of this publication does not constitute an endorsement of the contents which reflects the views only of the authors, and the Commission cannot be held responsi­ble for any use which may be made of the information contained therein

Predicting the Need for Urgent Instructor Intervention in MOOC Environments

In recent years, massive open online courses (MOOCs) have become universal knowledge resources and arguably one of the most exciting innovations in e-learning environments. MOOC platforms comprise numerous courses covering a wide range of subjects and domains. Thousands of learners around the world enrol on these online platforms to satisfy their learning needs (mostly) free of charge. However, the retention rates of MOOC courses (i.e., those who successfully complete a course of study) are low (around 10% on average); dropout rates tend to be very high (around 90%). The principal channel via which MOOC learners can communicate their difficulties with the learning content and ask for assistance from instructors is by posting in a dedicated MOOC forum. Importantly, in the case of learners who are suffering from burnout or stress, some of these posts require urgent intervention. Given the above, urgent instructor intervention regarding learner requests for assistance via posts made on MOOC forums has become an important topic for research among researchers. Timely intervention by MOOC instructors may mitigate dropout issues and make the difference between a learner dropping out or staying on a course. However, due to the typically extremely high learner-to-instructor ratio in MOOCs and the often-huge numbers of posts on forums, while truly urgent posts are rare, managing them can be very challenging –– if not sometimes impossible. Instructors can find it challenging to monitor all existing posts and identify which posts require immediate intervention to help learners, encourage retention, and reduce the current high dropout rates. The main objective of this research project, therefore, was thus to mine and analyse learners’ MOOC posts as a fundamental step towards understanding their need for instructor intervention. To achieve this, the researcher proposed and built comprehensive classification models to predict the need for instructor intervention. The ultimate goal is to help instructors by guiding them to posts, topics, and learners that require immediate interventions. Given the above research aim the researcher conducted different experiments to fill the gap in literature based on different platform datasets (the FutureLearn platform and the Stanford MOOCPosts dataset) in terms of the former, three MOOC corpora were prepared: two of them gold-standard MOOC corpora to identify urgent posts, annotated by selected experts in the field; the third is a corpus detailing learner dropout. Based in these datasets, different architectures and classification models based on traditional machine learning, and deep learning approaches were proposed. In this thesis, the task of determining the need for instructor intervention was tackled from three perspectives: (i) identifying relevant posts, (ii) identifying relevant topics, and (iii) identifying relevant learners. Posts written by learners were classified into two categories: (i) (urgent) intervention and (ii) (non-urgent) intervention. Also, learners were classified into: (i) requiring instructor intervention (at risk of dropout) and (ii) no need for instructor intervention (completer). In identifying posts, two experiments were used to contribute to this field. The first is a novel classifier based on a deep learning model that integrates novel MOOC post dimensions such as numerical data in addition to textual data; this represents a novel contribution to the literature as all available models at the time of writing were based on text-only. The results demonstrate that the combined, multidimensional features model proposed in this project is more effective than the text-only model. The second contribution relates to creating various simple and hybrid deep learning models by applying plug & play techniques with different types of inputs (word-based or word-character-based) and different ways of representing target input words as vector representations of a particular word. According to the experimental findings, employing Bidirectional Encoder Representations from Transformers (BERT) for word embedding rather than word2vec as the former is more effective at the intervention task than the latter across all models. Interestingly, adding word-character inputs with BERT does not improve performance as it does for word2vec. Additionally, on the task of identifying topics, this is the first time in the literature that specific language terms to identify the need for urgent intervention in MOOCs were obtained. This was achieved by analysing learner MOOC posts using latent Dirichlet allocation (LDA) and offers a visualisation tool for instructors or learners that may assist them and improve instructor intervention. In addition, this thesis contributes to the literature by creating mechanisms for identifying MOOC learners who may need instructor intervention in a new context, i.e., by using their historical online forum posts as a multi-input approach for other deep learning architectures and Transformer models. The findings demonstrate that using the Transformer model is more effective at identifying MOOC learners who require instructor intervention. Next, the thesis sought to expand its methodology to identify posts that relate to learner behaviour, which is also a novel contribution, by proposing a novel priority model to identify the urgency of intervention building based on learner histories. This model can classify learners into three groups: low risk, mid risk, and high risk. The results show that the completion rates of high-risk learners are very low, which confirms the importance of this model. Next, as MOOC data in terms of urgent posts tend to be highly unbalanced, the thesis contributes by examining various data balancing methods to spot situations in which MOOC posts urgently require instructor assistance. This included developing learner and instructor models to assist instructors to respond to urgent MOOCs posts. The results show that models with undersampling can predict the most urgent cases; 3x augmentation + undersampling usually attains the best performance. Finally, for the first time, this thesis contributes to the literature by applying text classification explainability (eXplainable Artificial Intelligence (XAI)) to an instructor intervention model, demonstrating how using a reliable predictor in combination with XAI and colour-coded visualisation could be utilised to assist instructors in deciding when posts require urgent intervention, as well as supporting annotators to create high-quality, gold-standard datasets to determine posts cases where urgent intervention is required

Investigating self-regulation in the context of a blended learning computing course

PURPOSE: Massive open online courses (MOOCs) provide an innovative educational technology, which has become widely used for distance learning by independent learners. However, there has been little work so far to study the effects of using MOOCs as part of a blended classroom approach in which learning activities take place both online and in a traditional classroom setting. The purpose of this study is to investigate the aspects of blended MOOC usage in the context of a computing course for first-year undergraduates at a UK university. DESIGN/METHODOLOGY/APPROACH: The MOOC was implemented on a purpose-built platform that supports learners to make informed choices about their learning path. This research investigates students’ capacity for self-regulated learning (SRL) and understands their preparedness for independent study, profile the general areas of SRL strength and weakness, which may affect their ability to learn effectively in a self-directed environment. An existing survey instrument, based on a six-dimensional conceptualization of SRL was adapted to investigate the self-regulation in the MOOC study. FINDINGS: The results demonstrate that the dimensions of self-evaluation and time management represent particular areas of weakness for these students. Furthermore, profiles of SRL for individual students show considerable differences in capability within the study. However, the deficiencies in SRL dimensions contrast with the students’ of generally high levels of attainment. This leads us to question the validity of the existing SRL. Furthermore, a high level of social interaction and help-seeking was reported in relation to the MOOC study indicating the increasing importance of social learning and the importance of co-regulation for SRL. RESEARCH LIMITATIONS/IMPLICATIONS: Although this study presents findings from a small data sample, it points to a number of areas for future implementation and exploration. Firstly, in line with the action research approach, students’ SRL could, in the future, be tested early in the course with the MOOC component being ideally placed to provide personalised support for each student in aspects which they may benefit from developing further. Secondly, for students in the cohort studied in this paper, a longitudinal study will track how their SRL develops as they progress through the degree. We feel that it is important to gain further qualitative data to understand how students work in practice and the strategies they adopt when confronted with different modes of learning. Finally, it is necessary to consider the conceptualisation of SRL to understand if existing instruments could be adapted to provide a more accurate assessment of the effectiveness of learners’ self-regulation. ORIGINALITY/VALUE: There has been little research on the effects of using a MOOC as the online component of a blended classroom learning approach. This study has used a theoretical perspective of SRL to investigate the approaches to self-regulation adopted by undergraduate computer science students studying in a blended MOOC environment. The MOOC used for this purpose was developed on the innovative eLDa platform, allowing students to determine, track and visualise their individual path through topics and materials offered in the MOOC