scholarly journals Construction of the Quality Evaluation Index System of MOOC Platforms Based on the User Perspective

2021 ◽  
Vol 13 (20) ◽  
pp. 11163
Author(s):  
Pei-Yao Su ◽  
Jing-Hong Guo ◽  
Qi-Gan Shao
Keyword(s):  
Online Courses ◽  
Fuzzy Theory ◽  
Research Result ◽  
Multiple Criteria Decision Making ◽  
Evaluation Index System ◽  
Massive Open Online Courses ◽  
Future Research ◽  
Analysis Method ◽  
User Perspective

Massive open online courses (MOOCs) have become a mainstream form of online learning. At present, various countries are vigorously developing MOOC platforms, which provide a helpful platform for people to acquire knowledge and skills. However, the quality of each MOOC platform is different, which is a challenge for learners seeking excellent courses. Since the evaluation of MOOC quality is a multiple criteria decision-making issue, it is important to find the major dimensions and criteria that determine the quality of platforms. This paper determines the weight of each dimension and criterion by using the best worst method (BWM). The results indicate that content accuracy has the greatest impact on MOOC quality. This paper selected five well-known domestic MOOC websites as research objects and used the VIKOR analysis method to rank the platform quality of the five chosen websites. The results show that IMOOC and Xuedong are ranked as the top two websites. This research result helps learners deepen their understanding of MOOC platforms and can serve as a reference for MOOC platforms to improve their quality. Techniques to reduce the uncertainty of expert judgments (such as rough sets, fuzzy theory, grey correlation, etc.) and models that clarify the influence relationship between criteria (DEMATEL-ANP) can be applied in future research.

scholarly journals MOOC Success Factors: Proposal of an Analysis Framework

10.28945/3861 ◽  
2017 ◽  
Vol 16 ◽  
pp. 233-251 ◽  
Author(s):  
Jose Azevedo ◽  
Margarida M. Marques
Keyword(s):  
Best Practices ◽  
Success Factors ◽  
Online Courses ◽  
Massive Open Online Courses ◽  
Future Research ◽  
Completion Rates ◽  
Analysis Framework ◽  
Factors Analysis ◽  
Future Work

Aim/Purpose: From an idea of lifelong-learning-for-all to a phenomenon affecting higher education, Massive Open Online Courses (MOOCs) can be the next step to a truly universal education. Indeed, MOOC enrolment rates can be astoundingly high; still, their completion rates are frequently disappointingly low. Nevertheless, as courses, the participants’ enrolment and learning within the MOOCs must be considered when assessing their success. In this paper, the authors’ aim is to reflect on what makes a MOOC successful to propose an analysis framework of MOOC success factors. Background: A literature review was conducted to identify reported MOOC success factors and to propose an analysis framework. Methodology: This literature-based framework was tested against data of a specific MOOC and refined, within a qualitative interpretivist methodology. The data were collected from the ‘As alterações climáticas nos média escolares - Clima@EduMedia’ course, which was developed by the project Clima@EduMedia and was submitted to content analysis. This MOOC aimed to support science and school media teachers in the use of media to teach climate change Contribution: By proposing a MOOC success factors framework the authors are attempting to contribute to fill in a literature gap regarding what concerns criteria to consider a specific MOOC successful. Findings: This work major finding is a literature-based and empirically-refined MOOC success factors analysis framework. Recommendations for Practitioners: The proposed framework is also a set of best practices relevant to MOOC developers, particularly when targeting teachers as potential participants. Recommendation for Researchers: This work’s relevance is also based on its contribution to increasing empirical research on MOOCs. Impact on Society: By providing a proposal of a framework on factors to make a MOOC successful, the authors hope to contribute to the quality of MOOCs. Future Research: Future work should refine further the proposed framework, by in testing it against data collected in other MOOCs.

scholarly journals Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums

2021 ◽  
Vol 13 (16) ◽  
pp. 9364
Author(s):  
Raquel L. Pérez-Nicolás ◽  
Carlos Alario-Hoyos ◽  
Iria Estévez-Ayres ◽  
Pedro Manuel Moreno-Marcos ◽  
Pedro J. Muñoz-Merino ◽  
...  
Keyword(s):  
Online Courses ◽  
Research Work ◽  
Massive Open Online Courses ◽  
Three Dimensions ◽  
Future Research ◽  
Discussion Forums ◽  
Automatic Assessment ◽  
Automatic Grading ◽  
The Impact

Discussion forums are a valuable source of information in educational platforms such as Massive Open Online Courses (MOOCs), as users can exchange opinions or even help other students in an asynchronous way, contributing to the sustainability of MOOCs even with low interaction from the instructor. Therefore, the use of the forum messages to get insights about students’ performance in a course is interesting. This article presents an automatic grading approach that can be used to assess learners through their interactions in the forum. The approach is based on the combination of three dimensions: (1) the quality of the content of the interactions, (2) the impact of the interactions, and (3) the user’s activity in the forum. The evaluation of the approach compares the assessment by experts with the automatic assessment obtaining a high accuracy of 0.8068 and Normalized Root Mean Square Error (NRMSE) of 0.1799, which outperforms previous existing approaches. Future research work can try to improve the automatic grading by the training of the indicators of the approach depending on the MOOCs or the combination with text mining techniques.

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.  

What is Best for the Learner?

2015 ◽  
pp. 142-157 ◽  
Author(s):  
Carole A. Bagley ◽  
Janet Weisenford
Keyword(s):  
Online Courses ◽  
Massive Open Online Courses ◽  
Training Design ◽  
Educational Training ◽  
Education Practice ◽  
Learner Performance ◽  
Multiple Factors ◽  
On Line ◽  
Instruction And Learning

Massive Open Online Courses or MOOCs are increasing in use by universities, corporations and other organizations. The quality of instruction and learning is an ongoing topic of debate as to whether MOOCs are effective for learning. What is best for the learner is determined by multiple factors. This chapter looks at what is best for the learner and whether MOOCs are the answer. The authors examine each of the factors that impact what is best for the learner. Each of the factors (accessibility, cost to the learner, quality of instructional design, learner performance, and acquiring on-line collaboration methods and resources) are described and are followed by a discussion of the issues, controversies and problems associated with each factor. This chapter takes up the discussion on the book section ‘RIA and education practice of MOOCs,' with the particular focus on the topic of ‘educational training design.'

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.

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.

scholarly journals Instructional quality of Massive Open Online Courses (MOOCs)

2015 ◽  
Vol 80 ◽  
pp. 77-83 ◽  
Author(s):  
Anoush Margaryan ◽  
Manuela Bianco ◽  
Allison Littlejohn
Keyword(s):  
Online Courses ◽  
Instructional Quality ◽  
Massive Open Online Courses ◽  
Massive Open Online

Fuzzy AHP-Based Algorithm for Performance Evaluation of New Socialist Countryside in Northwest Minority Regions of China

2013 ◽  
Vol 734-737 ◽  
pp. 3124-3128
Author(s):  
Chao Ji Yang ◽  
Hai Ying Ma
Keyword(s):  
Social Economic ◽  
Fuzzy Theory ◽  
Fuzzy Ahp ◽  
Multiple Criteria Decision Making ◽  
Evaluation Index System ◽  
Good Reliability ◽  
Analysis Technique ◽  
Result Show ◽  
Social Economic Development ◽  
Minority Regions

New socialist countryside (NHC) is usually observed in rural social economic development in China since 2005. In this paper, we analyzed NSC construction in Northwest Minorities regions of China based on the idea of an Fuzzy AHP Algorithm which builds a combined analysis technique of AHP and Fuzzy theory for multiple criteria decision making, and by four aspects: new farmersdeveloped agricultureharmonious countryside and environment for minority populations. The result show that evaluation index system based on Fuzzy AHP Algorithm in Northwest Minority regions has good reliability.

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