17,170 research outputs found

    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

    A systematic literature review on the quality of moocs

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    This paper presents the findings from a systematic literature review on the quality of massive open online courses (MOOCs). The main research question was “How can the quality criteria for MOOCs identified in the analysed studies from the systematic literature review be best organ-ised in a categorisation scheme?” The systematic literature review was conducted using the PRISMA procedures. After conducting the screening and eligibility analysis according the pre-defined crite-ria, 103 studies were finally selected. The analysis was done in iterative cycles for continuous im-provements of the assignments and clustering of the quality criteria. The final version was validated in consensus through the categorisation and assignment of all 103 studies in a consistent way to four dimensions (pedagogical, organisational, technological, and social) and their sub-categories. This quality framework can be re-used in future MOOC research and the discussion of the analysed studies provides a current literature overview on the quality of MOOCs

    Eduke.me : reaching out for new sources of growth.

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    The Thesis presented in the form of a Case Study focuses on the challenges and opportunities a Portuguese educational technology startup, Eduke.me, faces upon choosing a path for further growth in the future. By addressing several topics such as market potential, vertical integration, partnerships, capabilities, diversification, innovation and growth constraints, students can apply strategic frameworks and other theories to the analysis of this case. The Thesis is divided into three parts: Case Study, Literature Review and Teaching Note. The thesis intends to be a practical means for students to develop their critical thinking, as well as information processing, with imperfect and scattered data. It allows students to grasp the possible constraints a company may face, and what alternatives exist to overcome them.A tese apresentada sob a forma de um Estudo de Caso centra-se sobre os desafios e oportunidades que uma startup de tecnologia educacional portuguesa, Eduke.me; enfrenta as escolhes um caminho de crescimento futuro. Ao abordar vários temas, tais como potencial de mercado, integração vertical, as parcerias, os recursos, a diversificação, inovação e as restrições ao crescimento; os alunos poderão aplicar modelos estratégicos e outras teorias para a analisar deste caso. O trabalho está dividido em três partes: Estudo de Caso, Revisão Literária e Nota de Aula. A tese pretende ser um meio prático para que os alunos possam desenvolver o seu espírito crítico, bem como o processamento de informações, com dados imperfeitos e dispersos. Isto permite que os alunos compreendam as possíveis restrições que uma empresa pode enfrentar, e que alternativas existem para superá-las

    Setting The Pace: Examining Cognitive Processing in MOOC Discussion Forums With Automatic Text Analysis

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    Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can create challenges for understanding and adequately describing student behaviors. Utilizing automatic text analysis, this study built a hierarchical linear model that examines the influence of the pacing condition of a massive open online course (MOOC), whether it is self-paced or instructor-paced, on the demonstration of cognitive processing in a HarvardX MOOC. The analysis of 2,423 discussion posts generated by 671 students revealed the number of dictionary words used were positively associated with cognitive processing while analytical thinking and clout was negatively associated. We found that none of the student background information (gender, education), status of the course engagement (explored or completed), or the course pace (self-paced versus instructor paced) significantly influenced the cognitive processing of the postings

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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