scholarly journals Evaluation Grid for xMOOCs

2015 ◽  
Vol 10 (4) ◽  
pp. 40 ◽  
Author(s):  
Mohammad Khalil ◽  
Hubert Brunner ◽  
Martin Ebner
Keyword(s):  
Literature Review ◽  
Online Courses ◽  
Decision Makers ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online

Massive Open Online Courses, shortly MOOCs, are a phenomenon nowadays. The number of courses is worldwide steadily increasing since Sebastian Thrun has offered a free online course for more than 100.000 students. Nowadays, decision makers and students as well as lecturers are asking about the quality of such courses. After a live experiment on 15 randomly chosen courses and a brief literature review, we discuss the possibility of finding an evaluation grid for xMOOCs. The finally suggested criteria can be used now for future investigations.

Valor dos massive open online course (MOOC) na educação para a cidadania

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Hermano Carmo ◽  
Teresa Maia e Carmo
Keyword(s):  
Online Courses ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Massive Open Online Course ◽  
Tecnología Educativa

A sociedade contemporânea é marcada por três macrotendências que a identificam como uma sociedade singular na história humana: processo de mudança acelerada, desigualdade crescente e fibrilhação dos sistemas de poder. Tais tendências têm tido como efeitos um quadro de ameaças e oportunidades que tanto têm constituído gigantesco desafio aos sistemas educativos quanto configuram a urgência de ressocialização de todas as gerações vivas no sentido da construção de uma cidadania global. Nesse contexto, propõe-se um modelo que configura uma estratégia de educação para a cidadania, com dois eixos, quatro vertentes e dez áreas-chave. Seguidamente, descreve-se e discute-se a emergência quase explosiva dos Massive Open Online Courses (MOOC) a partir de instituições de ensino superior internacionalmente reconhecidas, no quadro do novo paradigma digital, sua diversidade e seu potencial ainda em aberto. Confrontando a nova abordagem educativa com o modelo de educação para a cidadania proposto, conclui-se constituir um meio robusto para o potenciar.Palavras-chave:Conjuntura. Macrotendências. Educação para a cidadania. MOOC. Tecnologia educativa. Paradigma digital.Link: http://revista.ibict.br/inclusao/article/view/4171/3642

scholarly journals Elaboração de um framework para MOOC na Formação Contínua de Professores

2020 ◽  
Vol 58 (58) ◽  
Author(s):  
Carolina Amado ◽  
Ana Pedro
Keyword(s):  
Literature Review ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Scoping Literature Review

O presente artigo decorre de uma investigação que tem como objetivo contribuir para a estruturação de um referencial para caracterizar Massive Open Online Courses, no âmbito da formação contínua de professores. Neste artigo iremos identificar quais as dimensões que a literatura assinala como adequadas para o design de MOOC. Para isso iremos adotar a abordagem qualitativa scoping literature review, cujo propósito passa por identificar e analisar dimensões formuladas em trabalhos relevantes publicados na área. Foi possível identificar um conjunto de necessidades relacionadas com as ofertas formativas para professores e questões de design de cursos massivos no âmbito da formação contínua de professores. Por aplicação de critérios de elegibilidade foram selecionados para análise nove artigos. Os resultados revelam a existência de um conjunto de recursos e decisões a valorizar e destacar aquando da implementação de cursos massivos para a formação contínua de professores, nomeadamente, os conteúdos, a avaliação, a descrição geral do curso, o público-alvo e a abordagem pedagógica.

scholarly journals Topic Discovery of Online Course Reviews Using LDA with Leveraging Reviews Helpfulness

2019 ◽  
Vol 9 (1) ◽  
pp. 426
Author(s):  
Fetty Fitriyanti Lubis ◽  
Yusep Rosmansyah ◽  
Suhono H. Supangkat
Keyword(s):  
Topic Modeling ◽  
Online Courses ◽  
Influential Factors ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Small Scale ◽  
Massive Open Online ◽  
Topic Discovery ◽  
Modeling Approach ◽  
Teaching Learning

Despite the popularity of the Massive Open Online Courses, small-scale research has been done to understand the factors that influence the teaching-learning process through the massive online platform. Using topic modeling approach, our results show terms with prior knowledge to understand e.g.: Chuck as the instructor name. So, we proposed the topic modeling approach on helpful subjective reviews. The results show five influential factors: “learn easy excellent class program”, “python learn class easy lot”, “Program learn easy python time game”, and “learn class python time game”. Also, research results showed that the proposed method improved the perplexity score on the LDA model.

scholarly journals Recommender Systems for MOOCs: A Systematic Literature Survey (January 1, 2012 – July 12, 2019)

2020 ◽  
Vol 21 (4) ◽  
pp. 255-291
Author(s):  
Asra Khalid ◽  
Karsten Lundqvist ◽  
Anne Yates
Keyword(s):  
Quantitative Analysis ◽  
Literature Review ◽  
Student Performance ◽  
Recommender Systems ◽  
Online Courses ◽  
Systems Design ◽  
Literature Survey ◽  
Massive Open Online Courses ◽  
Future Research ◽  
Massive Open Online

In recent years, massive open online courses (MOOCs) have gained popularity with learners and providers, and thus MOOC providers have started to further enhance the use of MOOCs through recommender systems. This paper is a systematic literature review on the use of recommender systems for MOOCs, examining works published between January 1, 2012 and July 12, 2019 and, to the best of our knowledge, it is the first of its kind. We used Google Scholar, five academic databases (IEEE, ACM, Springer, ScienceDirect, and ERIC) and a reference chaining technique for this research. Through quantitative analysis, we identified the types and trends of research carried out in this field. The research falls into three major categories: (a) the need for recommender systems, (b) proposed recommender systems, and (c) implemented recommender systems. From the literature, we found that research has been conducted in seven areas of MOOCs: courses, threads, peers, learning elements, MOOC provider/teacher recommender, student performance recommender, and others. To date, the research has mostly focused on the implementation of recommender systems, particularly course recommender systems. Areas for future research and implementation include design of practical and scalable online recommender systems, design of a recommender system for MOOC provider and teacher, and usefulness of recommender systems.  

scholarly journals A Semantic Recommendation System for Learning Personalization in Massive Open Online Courses

2020 ◽  
Vol 8 (1) ◽  
pp. 71
Author(s):  
Sara Assami ◽  
Najima Daoudi ◽  
Rachida Ajhoun
Keyword(s):  
Recommendation System ◽  
Online Courses ◽  
Learning Technologies ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Learning Context ◽  
Massive Open Online ◽  
New Era ◽  
Learner Model ◽  
Massive Open Online Course

<p class="0abstract">For an innovation producing education, MOOC (Massive Open Online Course) platforms offer a plethora of learning resources and pedagogical activities to support the university’s 4.0 new era and the lifelong learning movement. Nevertheless, the rapid advances in learning technologies imply the need for personalized guidance for learners and adapted learning materials. In this paper we seek to enhance the MOOC learner experience by providing a semantic recommender system for the diversity and abundance of MOOCs available for learners. Firstly, the paper analyses the state of the art of the semantic recommendation approach in a distance learning context. Then it describes the proposed MOOC recommendation system that uses the ontological representation of the learner model and MOOCs content to make its intelligent suggestions. Finally, we explore the development phases of the semantic MOOC recommendation system to define the implications for the progress of our research.</p>

Mining Individual Learning Topics in Course Reviews Based on Author Topic Model

2017 ◽  
Vol 15 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Sanya Liu ◽  
Cheng Ni ◽  
Zhi Liu ◽  
Xian Peng ◽  
Hercy N.H. Cheng
Keyword(s):  
Topic Model ◽  
Online Courses ◽  
Rapid Development ◽  
Educational Data Mining ◽  
Online Reviews ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Analysis Technique ◽  
Learning Analysis

Nowadays, Massive Open Online Courses (MOOC) has obtained a rapid development and drawn much attention from the areas of learning analytics and artificial intelligence. There are lots of unstructured data being generated in online reviews area. The learning behavioral data become more and more diverse, and they prompt the emergence of big data in education. To mine useful information from these data, we need to use educational data mining and learning analysis technique to study the learning feelings and discussed topics among learners. This paper aims to mine and analyze topic information hidden in the unstructured reviews data in MOOC, a novel author topic model based on an unsupervised learning idea is proposed to extract learning topics for the each learner. According to the experimental results, we will analyze and focuses of interests of learners, which facilitates further personalized course recommendation and improve the quality of online courses.

Understanding learner participation at scale: How and why

2020 ◽  
Vol 17 (3) ◽  
pp. 236-252
Author(s):  
Samaa Haniya ◽  
Luc Paquette
Keyword(s):  
Teaching And Learning ◽  
Large Scale ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Massive Open Online ◽  
Learner Participation ◽  
Massive Open Online Course ◽  
Motivation For Learning ◽  
E Learning

Understanding learner participation is essential to any learning environment to enhance teaching and learning, especially in large scale digital spaces, such as massive open online courses. However, there is a lack of research to fully capture the dynamic nature of massive open online courses and the different ways learners participate in these emerging massive e-learning ecologies. To fill in the research gap, this paper attempted to investigate the relationship between how learners choose to participate in a massive open online course, their initial motivation for learning, and the barriers they faced throughout the course. This was achieved through a combination of data-driven clustering approaches—to identify patterns of learner participation—and qualitative analysis of survey data—to better understand the learners’ motivation and the barriers they faced during the course. Through this study we show how, within the context of a Coursera massive open online course offered by the University of Illinois, learners with varied patterns of participation (Advanced, Balanced, Early, Limited, and Delayed Participation) reported similar motivations and barriers, but described differences in how their participation was impacted by those factors. These findings are significant to gain insights about learners’ needs which in turn serve as the basis to innovate more adaptive and personalized learning experiences and thus advance learning in these large scale environments.

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