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 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.

Administrators’ Assessments of Online Courses and Student Retention in Higher Education

2014 ◽  
pp. 138-150
Author(s):  
Ruth Gannon Cook ◽  
Roy Sutton
Keyword(s):  
Best Practices ◽  
Student Retention ◽  
Online Courses ◽  
Course Completion ◽  
Online Course ◽  
Future Research ◽  
Completion Rates ◽  
For Profit ◽  
The World ◽  
Strategic Factors

Criteria may vary across public, private, and for profit universities for online courses around the world, but despite differences, there seem to be some successful lessons that could be shared across universities with respect to certain factors that increased student online course completion rates among certain universities’ courses. This study looked at an associate dean’s search for strategic factors that could contribute to increased online course completion rates at his university and more effectively address problems on a timely basis to improve those course completion rates. The associate dean’s collaboration with a researcher led to their conducting representative model research that revealed best practices and assessments from a number of universities and provided insights into which factors could be applied to online courses at his university. Future research could look at whether there was a substantial increase in student retention in the online courses implementing these factors to see if there may be best practices that could be generalized to other universities around the world.

scholarly journals Massive Open Online Courses (MOOC) Evaluation Methods: Protocol for a Systematic Review (Preprint)

2018 ◽  
Author(s):  
Kimberley Foley ◽  
Abrar Alturkistani ◽  
Alison Carter ◽  
Terese Stenfors ◽  
Elizabeth Blum ◽  
...  
Keyword(s):  
Systematic Review ◽  
Online Courses ◽  
Data Extraction ◽  
Evaluation Methods ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Massive Open Online ◽  
Data Synthesis ◽  
Meta Analyses ◽  
Future Work

BACKGROUND Massive open online courses (MOOCs) have increased in popularity in recent years. They target a wide variety of learners and use novel teaching approaches, yet often exhibit low completion rates (10%). It is important to evaluate MOOCs to determine their impact and effectiveness, but little is known at this point about the methodologies that should be used for evaluation. OBJECTIVE The purpose of this paper is to provide a protocol for a systematic review on MOOC evaluation methods. METHODS We will use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) guidelines for reporting this protocol. We developed a population, intervention, comparator, and outcome (PICO) framework to guide the search strategy, based on the overarching question, “What methods have been used to evaluate MOOCs?” The review will follow six stages: 1) literature search, 2) article selection, 3) data extraction, 4) quality appraisal, 5) data analysis, and 6) data synthesis. RESULTS The systematic review is ongoing. We completed the data searches and data abstraction in October and November 2018. We are now analyzing the data and expect to complete the systematic review by March 2019. CONCLUSIONS This systematic review will provide a useful summary of the methods used for evaluation of MOOCs and the strengths and limitations of each approach. It will also identify gaps in the literature and areas for future work. INTERNATIONAL REGISTERED REPOR DERR1-10.2196/12087

scholarly journals The use of gamification in xMOOCs about energy: Effects and predictive models for participants’ learning

2019 ◽  
pp. 43-59 ◽  
Author(s):  
Elvira G Rincon Flores ◽  
Juanjo Mena ◽  
María Soledad Ramírez Montoya ◽  
Raul Ramirez Velarde
Keyword(s):  
Predictive Models ◽  
Online Courses ◽  
National Laboratory ◽  
Analytical Data ◽  
The United States ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Academic Degree ◽  
Added Benefit ◽  
The Relationship

Open access education has significantly grown in strength as a new way of fostering innovation in schools. Such is the case of massive open online courses (MOOCs), which have the added benefit of encouraging the democratisation of learning. In this sense, the Bi-National Laboratory on Smart Sustainable Energy Management and Technology Training between Mexico and the United States of America was launched with the purpose of trying MOOC technology and measuring its impact on the academic, business, and social sectors. Under this scenario, this study aimed to show the relationship between using gamification and level of performance in a MOOC on energy topics. The methodology was quantitative, using the course analytical data for socio-demographic information and predictive models. A total of 6246 participants enrolled in the MOOC and 1060 finished it. The results showed that participants aged between 20 and 50 had the highest completion rates in the gamified challenge; the higher academic degree, the more inclined participants were to solve the gamified challenge; and no such distinction exists by gender.

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.

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