Identification of Affective States in MOOCs: A Systematic Literature Review

Massive Open Online Courses (MOOCs) are a type of online coursewere students have little interaction,  no instructor, and in some cases, no deadlines to finisch assignments. For this reason, a better understanding of student affection in MOOCs is importantant could have potential to open new perspectives for this type of course. The recent popularization of tools, code libraries and algorithms for intensive data analysis made possible collect data from text and interaction with the platforms, which can be used to infer correlations between affection and learning. In this context, a bibliographical review was carried out, considering the period between 2012 and 2018, with the goal of identifying which methods are being to identify affective states. Three databases were used: ACM Digital Library, IEEE Xplore and Scopus, and 46 papers were found. The articles revealed that the most common methods are related to data intensive techinques (i.e. machine learning, sentiment analysis and, more broadly, learning analytics). Methods such as physiological signal recognition andself-report were less frequent

MOOCKnowledge: Establishing a large-scale data-collection about participants of European Open Online Courses

While MOOCS have emerged as a new form of open online education around the world,there are still no cross- provider and large-scale data collections that provides reliable information about demographic details of the population of MOOC participants on the one hand, and their motivation, intentions, social context, lifelong learning profile and impact on study success and career development on the other hand. The MOOCKnowledge project is an initiative to establish a large-scale data-collection about participants of European MOOCs. In this paper we describe the motivation behind the project and discuss the research focus. We explain the structure of the survey instrument, report about the data collection process and provide an outlook on potential future developments of the project.JRC.J.3-Information Societ

Education Workforce Initiative: Initial Research

The purpose of this initial research is to offer evidenced possibilities in the key areas of education workforce roles, recruitment, training, deployment and leadership, along with suggested areas for further research to inform innovation in the design and strengthening of the public sector education workforce. The examples described were identified through the process outlined in the methodology section of this report, whilst we recognise that separation of examples from their context is problematic – effective innovations are highly sensitive to context and uncritical transfer of initiatives is rarely successful. The research aims to support the Education Workforce Initiative (EWI) in moving forward with engaging education leaders and other key actors in radical thinking around the design and strengthening of the education workforce to meet the demands of the 21st century. EWI policy recommendations will be drawn from a number of country level workforce reform activities and research activity associated with the production of an Education Workforce Report (EWR). This research has informed the key questions, approach and structure of the EWR as outlined in the Education Workforce Report Proposal. Issues pertaining to teaching and learning in primary and secondary education are at the centre of the research reported here; the focus is on moving towards schools as safe places where all children/ young people are able to engage in meaningful activity. The majority of the evidence shared here relates to teachers and school leaders; evidence on learning support staff, district officials and the wider education workforce is scant. Many of the issues examined are also pertinent to the early childhood care and education sector but these are being examined in depth by the Early Childhood Workforce Initiative. Resourcing for the Education Workforce was out of scope of this initial research but the EC recognises, as outlined in the Learning Generation Report, that provision of additional finance is a critical factor in achieving a sustainable, strong and well-motivated education workforce, particularly but not exclusively, in low and middle income countries. The next stage of EWI work will consider the relative costs of current initiatives and modelling of the cost implications of proposed reforms. EWI aims to complement the work on teacher policy design and teacher career frameworks (including salary structures) being undertaken by other bodies and institutions such as Education International, the International Task Force on Teachers for 2030 and the Teachers’ Alliance, most particularly by bringing a focus on school and district leadership, the role of Education Support Professionals (ESPs) and inter-agency working

The Big Five:Addressing Recurrent Multimodal Learning Data Challenges

The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback

Multimodal Challenge: Analytics Beyond User-computer Interaction Data

This contribution describes one the challenges explored in the Fourth LAK Hackathon. This challenge aims at shifting the focus from learning situations which can be easily traced through user-computer interactions data and concentrate more on user-world interactions events, typical of co-located and practice-based learning experiences. This mission, pursued by the multimodal learning analytics (MMLA) community, seeks to bridge the gap between digital and physical learning spaces. The “multimodal” approach consists in combining learners’ motoric actions with physiological responses and data about the learning contexts. These data can be collected through multiple wearable sensors and Internet of Things (IoT) devices. This Hackathon table will confront with three main challenges arising from the analysis and valorisation of multimodal datasets: 1) the data collection and storing, 2) the data annotation, 3) the data processing and exploitation. Some research questions which will be considered in this Hackathon challenge are the following: how to process the raw sensor data streams and extract relevant features? which data mining and machine learning techniques can be applied? how can we compare two action recordings? How to combine sensor data with Experience API (xAPI)? what are meaningful visualisations for these data

Rethinking Pedagogy: Exploring the Potential of Digital Technology in Achieving Quality Education

(First Paragraph) The Mahatma Gandhi Institute of Education for Peace and Sustainable Development (MGIEP) is UNESCO’s Category 1 education Institute in the Asia-Pacific region devoted to education for peace and sustainable development, as enshrined in SDG Target 4.7. UNESCO MGIEP promotes the use of digital learning platforms where teachers and students can co-create and share a highly interactive learning experience. With the rise of the internet, there has been a proliferation of online content and digital resources intended to support teaching and learning, albeit widely varying in quality. Digital education media and resources, if carefully designed and implemented, have a significant potential to be mobilized on a massive scale to support transformative learning for building sustainable, flourishing societies

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 do we model learning at scale?:A systematic review of research on MOOCs

Despite a surge of empirical work on student participation in online learning environments, the causal links between the learning-related factors and processes with the desired learning outcomes remain unexplored. This study presents a systematic literature review of approaches to model learning in Massive Open Online Courses offering an analysis of learning-related constructs used in the prediction and measurement of student engagement and learning outcome. Based on our literature review, we identify current gaps in the research, including a lack of solid frameworks to explain learning in open online setting. Finally, we put forward a novel framework suitable for open online contexts based on a well-established model of student engagement. Our model is intended to guide future work studying the association between contextual factors (i.e., demographic, classroom, and individual needs), student engagement (i.e., academic, behavioral, cognitive, and affective engagement metrics), and learning outcomes (i.e., academic, social, and affective). The proposed model affords further interstudy comparisons as well as comparative studies with more traditional education models. </jats:p