Who can benefit more from massive open online courses? A prospective cohort study

Jia, Mengmeng; Gong, De; Luo, Jie; Zhao, Juanjuan; Zheng, Jing; Li, Kun

doi:10.1016/j.nedt.2019.02.004

Cited by 35 publications

(37 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Another parameter that is important for the success of both online teaching techniques and the other parts of the course is the existence of a community. Online learning built around an active and engaged community is more likely to achieve its goals (Jia et al, 2019).…”

Section: How Do We Learn a Technique?mentioning

confidence: 99%

Online coach development and certification programs in sports: are they possible?

Παπαγεωργίου

2020

Central European Journal of Sport Sciences and Medicine

View full text Add to dashboard Cite

Anticipating the inevitable shift of coach education and Coach Certification Programs (CCP) to distance-learning platforms in the imminent future, I have attempted to identify obstacles that we are likely to face. After explaining the rationale and the potential benefits of such courses, I have identified technique as the most difficult component to both teach and evaluate. A specific viewpoint regarding technique is briefly discussed and several related guidelines are provided to assist in both teaching (coach education) and evaluating technique (CCP) within the context of distance education.

show abstract

Section: How Do We Learn a Technique?mentioning

confidence: 99%

Online coach development and certification programs in sports: are they possible?

Παπαγεωργίου

2020

Central European Journal of Sport Sciences and Medicine

View full text Add to dashboard Cite

show abstract

“…Another reported that 93% of its participants believed the course had changed their lives (n = 516). Two studies [20,34] attempted to use controls to determine differences in outcomes between respondents who had used MOOCs in isolation vs respondents who had used MOOCs in addition to "traditional" courses. One qualitative study [54] attempted to map students' responses from focus group discussions to Herrington's authentic learning framework [66] as a way to demonstrate the achievement of learning outcomes related to the development of graduate attributes.…”

Section: Effectivenessmentioning

confidence: 99%

These may not be the courses you are seeking: a systematic review of open online courses in health professions education

et al. 2019

View full text Add to dashboard Cite

Introduction Open Online Courses (OOCs) are increasingly presented as a possible solution to the many challenges of higher education. However, there is currently little evidence available to support decisions around the use of OOCs in health professions education. The aim of this systematic review was to summarise the available evidence describing the features of OOCs in health professions education and to analyse their utility for decision-making using a self-developed framework consisting of point scores around effectiveness, learner experiences, feasibility, pedagogy and economics. Methods Electronic searches of PubMed, Medline, Embase, PsychInfo and CINAHL were made up to April 2019 using keywords related to OOC variants and health professions. We accepted any type of full text English publication with no exclusions made on the basis of study quality. Data were extracted using a custom-developed, a priori critical analysis framework comprising themes relating to effectiveness, economics, pedagogy, acceptability and learner experience. Results 54 articles were included in the review and 46 were of the lowest levels of evidence, and most were offered by institutions based in the United States (n = 11) and United Kingdom (n = 6). Most studies provided insufficient course detail to make any confident claims about participant learning, although studies published from 2016 were more likely to include information around course aims and participant evaluation. In terms of the five categories identified for analysis, few studies provided sufficiently robust evidence to be used in formal decision making in undergraduate or postgraduate curricula. Conclusion This review highlights a poor state of evidence to support or refute claims regarding the effectiveness of OOCs in health professions education. Health professions educators interested in developing courses of this nature should adopt a critical and cautious position regarding their adoption.

show abstract

“…The number of people enrolled in MOOCs has been steadily increasing, and there are several platforms, such as Coursera, edX, MiríadaX, or FutureLearn, to provide free open courses from prestigious institutions worldwide to thousands of participants [47]. MOOC platforms generally employ conventional learning content, such as short video lectures, slide presentations, reading texts, problem sets, live chat, and online learning assessments [31,43]. In addition, MOOCs are generally supported by discussion forums to enhance the interactions between the stakeholders of the learning process.…”

Section: Introductionmentioning

confidence: 99%

Sentiment analysis on massive open online course evaluations: A text mining and deep learning approach

Onan

2020

Comp Applic In Engineering

263

View full text Add to dashboard Cite

Massive open online courses (MOOCs) are recent innovative approaches in distance education, which provide learning content to participants without age-, gender-, race-, or geography-related barriers. The purpose of our research is to present an efficient sentiment classification scheme with high predictive performance in MOOC reviews, by pursuing the paradigms of ensemble learning and deep learning. In this contribution, we seek to answer several research questions on sentiment analysis on educational data. First, the predictive performance of conventional supervised learning methods, ensemble learning methods and deep learning methods has been evaluated. Besides, the efficiency of text representation schemes and word-embedding schemes has been evaluated for sentiment analysis on MOOC evaluations. For the evaluation task, we have analyzed a corpus containing 66,000 MOOC reviews, with the use of machine learning, ensemble learning, and deep learning methods.The empirical analysis indicate that deep learning-based architectures outperform ensemble learning methods and supervised learning methods for the task of sentiment analysis on educational data mining. For all the compared configurations, the highest predictive performance has been achieved by long short-term memory networks in conjunction with GloVe word-embedding scheme-based representation, with a classification accuracy of 95.80%.

show abstract

Who can benefit more from massive open online courses? A prospective cohort study

Cited by 35 publications

References 15 publications

Online coach development and certification programs in sports: are they possible?

Online coach development and certification programs in sports: are they possible?

These may not be the courses you are seeking: a systematic review of open online courses in health professions education

Sentiment analysis on massive open online course evaluations: A text mining and deep learning approach

Contact Info

Product

Resources

About