103 research outputs found

    Why do Institutions Offer MOOCs?

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    By reviewing the literature and interviewing 83 individuals knowledgeable about massive open online courses (MOOCs), we investigate the goals of institutions of higher education that are currently developing and delivering such courses. We identify six major goals for MOOC initiatives: extending reach and access, building and maintaining brand, improving economics by reducing costs or increasing revenues, improving educational outcomes, innovation in teaching and learning, and conducting research on teaching and learning. Comparing these goals with the data being collected about MOOCs, their participants, and educational outcomes, as well as the resource requirements and cost drivers of the development and delivery process, we assess whether these goals are being met, or are likely to be in the future. While quantification of success in achieving these goals is for the most part lacking, we conclude that institutions are experiencing at least partial success in achieving each of these goals except for improving economics. We identify obstacles to fuller achievement of the goals and some potential solutions

    Large scale analytics of global and regional MOOC providers: Differences in learners' demographics, preferences, and perceptions

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    [EN] Massive Open Online Courses (MOOCs) remarkably attracted global media attention, but the spotlight has been concentrated on a handful of English-language providers. While Coursera, edX, Udacity, and FutureLearn received most of the attention and scrutiny, an entirely new ecosystem of local MOOC providers was growing in parallel. This ecosystem is harder to study than the major players: they are spread around the world, have less staff devoted to maintaining research data, and operate in multiple languages with university and corporate regional partners. To better understand how online learning opportunities are expanding through this regional MOOC ecosystem, we created a research partnership among 15 different MOOC providers from nine countries. We gathered data from over eight million learners in six thousand MOOCs, and we conducted a large-scale survey with more than 10 thousand participants. From our analysis, we argue that these regional providers may be better positioned to meet the goals of expanding access to higher education in their regions than the better-known global providers. To make this claim we highlight three trends: first, regional providers attract a larger local population with more inclusive demographic profiles; second, students predominantly choose their courses based on topical interest, and regional providers do a better job at catering to those needs; and third, many students feel more at ease learning from institutions they already know and have references from. Our work raises the importance of local education in the global MOOC ecosystem, while calling for additional research and conversations across the diversity of MOOC providers.We would like to thank support from the MIT-SPAIN program sponsored by "la Caixa" Foundation SEED FUND. Jose A. Ruiperez-Valiente acknowledges support from the Spanish Ministry of Science and Innovation through the Juan de la Cierva Incorporacion program (IJC2020-044852-I). Xitong Li acknowledges funding support from the French National Research Agency (ANR) [Grants ANR AAPG iMOOC-18-CE28-0020-01 and Investissements d'Avenir LabEx Ecodec Grant ANR-11-LABX-0047].Ruipérez-Valiente, JA.; Staubitz, T.; Jenner, M.; Halawa, S.; Zhang, J.; Despujol, I.; Maldonado-Mahauad, J.... (2022). Large scale analytics of global and regional MOOC providers: Differences in learners' demographics, preferences, and perceptions. Computers & Education. 180:1-17. https://doi.org/10.1016/j.compedu.2021.10442611718

    Psychophysiological Measures of Cognitive Absorption and Cognitive Load in E-Learning Applications

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    By understanding the psychophysiological factors behind successful e-learning, we aim to identify new techniques that improve participant retention and engagement. Past work has explored the relationship between Electroencephalography (EEG) and learning constructs, such as Cognitive Load and Cognitive Absorption. We believe that the unique application of an e-learning environment warrants an extension of existing theories. Our goal is to develop and validate a model explaining the role of Cognitive Load on Knowledge Gained. This research provides the foundation to then apply this model to create a neuroadaptive learning system. We describe an experiment that uses noninvasive tools to validate this model and explore the viability of off-the-shelf EEG for data collection in e-learning experiments. Potential theoretical contributions are discussed and results from a technical pilot are provided

    Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses

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    Following an accelerating pace of technological change, Massive Open Online Courses (MOOCs) have emerged as a popular educational delivery platform, leveraging ubiqui-tous connectivity and computing power to overcome longstanding geographical and financial barriers to education. Consequently, the demographic reach of education delivery is extended towards a global online audience, facilitating learning and development for a continually ex-panding portion of the world population. However, an extensive literature review indicates that the low completion rate is the major issue related to MOOCs. Due to a lack of in-person inter-action between instructors and learners in such courses, the ability of tutors to monitor learners is impaired, often leading to learner withdrawals. To address this problem, learner drop out patterns across five courses offered by Harvard and MIT universities are investigated in this paper. Learning Analytics is applied to address key factors behind participant dropout events through the comparison of attrition during the first and last weeks of each course. The results show that the number of attired participants during the first week of the course is higher than during the last week, low percentages of attired learners are found prior to course closing dates. It is indicated therefore that assessment fees may not represent a significant reason for learners withdrawal. We introduce supervised machine learning algorithms for the analysis of learner retention and attrition within MOOC platform. Results show that machine learning represents a viable direction for the predictive analysis of MOOCs, with highest performances yielded by Boosted Tree classification for initial attrition and Neural Network based classification for final attrition

    MOOCs in the Education of the Future : Digitizing Training

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    Everybody agrees that education is the foundation of a developed society. Parents make it abundantly clear to their children from a tender age: education will open doors for you; it will allow you to grow both personally and socially, to make money.... too many responsibilities for a single word. Improving education has become a magical mantra that is repeated over and over in both families and institutions. It is therefore quite striking to witness how the procedures and structure of the educational system in developed countries have remained fairly stable almost since its creation as a public service and its subsequent universalization. The reason for this is that education has been very successful in its main goal: spreading general knowledge among the population to allow citizens to get by in their everyday lives, and providing a more specialized knowledge so they can perform a specific job. Thus, the university education system teaches students to be, for instance, doctors, so they can replace other doctors who are retiring in any part of the country or they can work in newly opened health centers. The traditional view of higher education is to create somewhat interchangeable pieces that try to fit into a stable society. However, times are changing. Organizations need to adapt faster; knowledge is more specialized; and technology constantly modifies jobs. The traditional educational system therefore faces increased difficulties to remain a fundamental reference for training. Technology is behind many of the changes that seem to challenge society, and with it, the educational system. This monograph provides compelling arguments about how it can also be the solution. Although online training, and MOOCs in particular, have so far only been a reflection of in-class teaching, and a virtual reflection where many of the most important qualities are lost, there are currently enough elements to suggest that things will be different in the future. Speaking of technology as the element that prompts change does not include merely the Internet or improved interfaces. It also refers to new concepts such as big data, which will allow a staggering amount of data to be collected about users and behaviors to provide to adapt education in real-time; it refers to immersive technologies such as those developed for virtual reality environments, which will allow laboratory environments to be recreated for the users (the so-called remote laboratories); it refers to technologies that support the Open Content movement in the educational world. It therefore refers to the convergence of a large number of technologies that are much more powerful when combined than applied separately. Furthermore, the disruptive capabilities of these educational models do not lie simply in the adaptation of traditional methods to new technologies, but on the possibility of applying new pedagogical practices. Students will be able to explore, either through the use of simulators or of other technologies such as 3D printers. Additionally, peer-to-peer collaboration models could be used, whereby the core of the learning process is transferred from the teacher to the community itself, which uses teamwork and interaction to make its own deductions

    A Research Agenda on MOOCs: The Perspective of Social Sciences,

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    Originated to help academic institutions innovate pedagogical models, MOOCs are taking different routes, some of them marked by public policies, others by market strategies. Questioning the MOOC phenomenon according only to pedagogies and learning theories means, however, underestimating their impact on the evolution of educational systems. This article intends to define a research agenda into the social impact of MOOCs, in order to reflect on changes in educational policies, on academic culture, and on learning measurement. For this reason we suggest focusing attention on three features of MOOC phenomenology: MOOCs as a social movement - an active policy to request a greater democratization of education - MOOC as a medium and a cultural artifact (mediated texts, videos, interface, platform’ functionalities) able to convey learning to distant learners - and, at last, MOOC as a measurement - in other words as a strumentation (i.e. learning statements, analytics, algorythms, visualizion tools, dashboards etc) that allows you to monitor, analyze and optimize the effectiveness of online teaching and learning, highlighting also their limits

    Massive Open Online Courses (MOOCS): Emerging Trends in Assessment and Accreditation

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    In 2014, Massive Open Online Courses (MOOCs) are expected to witness a phenomenal growth in student registration compared to the previous years (Lee, Stewart, & Claugar-Pop, 2014). As MOOCs continue to grow in number, there has been an increasing focus on assessment and evaluation. Because of the huge enrollments in a MOOC, it is impossible for the instructor to grade homework and evaluate each student. The enormous data generated by learners in a MOOC can be used for developing and refining automated assessment techniques. As a result, “Smart Systems” are being designed to track and predict learner behavior while completing MOOC assessments. These automated assessments for MOOCs can automatically score and provide feedback to students multiple choice questions, mathematical problems and essays. Automated assessments help teachers with grading and also support students in the learning processes. Theseassessments are prompt, consistent, and support objectivity in assessment and evaluation (Ala-Mutka, 2005). This paper reviews the emerging trends in MOOC assessments and their application in supporting student learning and achievement. The paper concludes by describing how assessment techniques in MOOCs can help to maximize learning outcomes.AbstractIn 2014, Massive Open Online Courses (MOOCs) are expected towitness a phenomenal growth in student registration compared to the previous years. As MOOCs continue to grow in number, therehas been an increasing focus on assessment and evaluation. Because of the huge enrollments in a MOOC, it is impossible for the instructor to grade homework and evaluate each student. The enormous data generated by learners in a MOOC can be used for developing and refining automated assessment techniques. As a result, "Smart Systems" are being designed to track and predict learner behavior while completing MOOC assessments. These automated assessments for MOOCs can automatically score and provide feedback to students multiple choice questions, mathematical problems and essays. Automated assessments help teachers with grading and also support students in the learning processes. These assessments are prompt, consistent, and support objectivity in assessment and evaluation (Ala-Mutka, 2005). This paper reviews the emerging trends in MOOC assessments and their application in supporting student learning and achievement. The paper concludes by describing how assessment techniques in MOOCs can help to maximize learning outcomes
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