scholarly journals Engagement and desertion in MOOCs: Systematic review

Comunicar ◽  
2022 ◽  
Vol 30 (70) ◽  
Author(s):  
Odiel Estrada-Molina ◽  
Dieter-Reynaldo Fuentes-Cancell
Keyword(s):  
Systematic Review ◽  
Extrinsic Motivation ◽  
Online Courses ◽  
Dropout Rate ◽  
Attrition Rate ◽  
Learning Needs ◽  
Revisión Sistemática ◽  
High Dropout Rate ◽  
Para Determinar ◽  
Future Work

Massive and open online courses (MOOCs) satisfy learning needs from the particularities of their typologies (xMOOC, tMOOC, cMOOC, iMOOC, among others) even though their high dropout rate is still latent. Recent studies reaffirm engagement as an alternative to reduce dropout rates. The literature analyzed has not yet been able to systematize responses as to how to guarantee engagement in MOOCs and thus reduce their attrition rate. And, consistent with that question, are there still challenges for teachers in this area of educational technology? These answers motivated us to carry out this systematic review to determine how engagement has been studied to help reduce the attrition rate in MOOCs. Articles from journals indexed in Scopus or WoS were reviewed applying the PRISMA protocol. At the end of the protocol, it was defined to analyze 40 studies. The results reflect that the main variables are: the design of e-activities, intrinsic and extrinsic motivation, and communication between students. This paper confirms that the main challenges to guarantee engagement in MOOCs are individualized tutoring, interactivity, and feedback. Due to the scarcity of studies that analyze the variables in an integrated way, it is proposed as future work to determine what relationships exist between these variables that interfere with engagement and dropout in MOOCs. Los cursos en línea masivos y abiertos (MOOCs) permiten satisfacer necesidades de aprendizaje desde las particularidades de sus tipologías (xMOOC, tMOOC, cMOOC, iMOOC, entre otras), sin embargo, es aún latente su alta tasa de deserción. Estudios recientes reafirman el engagement como una alternativa para disminuir los índices de deserción. La literatura analizada aún no logra sistematizar respuestas a ¿cómo garantizar el engagement en los MOOCs y disminuir así su tasa de deserción? Y, en coherencia con esa pregunta, ¿existen aún retos del profesorado en este ámbito de la tecnología educativa? Ello motivó a realizar esta revisión sistemática para determinar cómo se ha trabajado el engagement para contribuir a disminuir la tasa de deserción en los MOOCs. Se revisaron artículos de revistas indexadas en Scopus o en WoS aplicando el protocolo PRISMA. Al finalizar el protocolo se definió analizar 40 estudios. Los resultados reflejan que las principales variables son: el diseño e-actividades; la motivación intrínseca y extrínseca y; la comunicación entre los estudiantes. Se ratifica que los principales retos para garantizar el engagement en los MOOCs son: la tutoría individualizada; la interactividad; y la retroalimentación. Debido a la escasez de estudios que analicen de forma integrada las variables antes mencionadas, se propone como trabajo futuro, determinar qué relaciones existen entre estas variables que intervienen en el engagement y la deserción en los MOOCs.

scholarly journals MOOC Dropout Prediction Using a Hybrid Algorithm Based on Decision Tree and Extreme Learning Machine

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Jing Chen ◽  
Jun Feng ◽  
Xia Sun ◽  
Nannan Wu ◽  
Zhengzheng Yang ◽  
...  
Keyword(s):  
Decision Tree ◽  
Extreme Learning Machine ◽  
Hybrid Algorithm ◽  
Online Courses ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
Wide Range ◽  
Good Classification ◽  
High Dropout Rate ◽  
Learning Machine

Massive Open Online Courses (MOOCs) have boomed in recent years because learners can arrange learning at their own pace. High dropout rate is a universal but unsolved problem in MOOCs. Dropout prediction has received much attention recently. A previous study reported the problem of learning behavior discrepancy leading to a wide range of fluctuation of prediction results. Besides, previous methods require iterative training which is time intensive. To address these problems, we propose DT-ELM, a novel hybrid algorithm combining decision tree and extreme learning machine (ELM), which requires no iterative training. The decision tree selects features with good classification ability. Further, it determines enhanced weights of the selected features to strengthen their classification ability. To achieve accurate prediction results, we optimize ELM structure by mapping the decision tree to ELM based on the entropy theory. Experimental results on the benchmark KDD 2015 dataset demonstrate the effectiveness of DT-ELM, which is 12.78%, 22.19%, and 6.87% higher than baseline algorithms in terms of accuracy, AUC, and F1-score, respectively.

scholarly journals Metaanálisis entre la videolaringoscopia y la laringoscopia directa en el manejo de la vía aérea difícil por parte de anestesiólogos experimentados

2018 ◽  
Vol 10 (8) ◽  
pp. 5
Author(s):  
Orreaga Zugasti Echarte
Keyword(s):  
Systematic Review ◽  
Tracheal Intubation ◽  
Difficult Airway ◽  
Meta Analysis ◽  
Standard Of Care ◽  
Added Value ◽  
Initial Management ◽  
Revisión Sistemática ◽  
Para Determinar ◽  
First Time

En este artículo se presenta una revisión sistemática y metaanálisis para determinar si la literatura indicaba que los videolaringoscopios suponen una ventaja sobre la laringoscopia directa cuando son utilizados por anestesiólogos experimentados en el manejo de la vía aérea difícil prevista. El éxito en la intubación al primer intento fue mayor en el grupo de los videolaringoscopios. Su uso también se asoció con una significativa mejor visión de la glotis y con un menor traumatismo de la mucosa de la vía aérea. Se concluye que la videolaringoscopia es un valor añadido para el anestesiólogo experimentado, mejorando la intubación en el primer intento, la visión de la glotis y reduciendo el trauma de la mucosa, pudiendo tener un papel importante en el abordaje inicial de la vía aérea difícil prevista. ABSTRACT This article presents a systematic review and meta-analysis to ascertain if the literature indicated if videolaryngoscopy conferred an advantage when used by experienced anaesthetists managing patients with a known difficult airway. First-attempt success of tracheal intubation was higher in the videolaryngoscopy group. Use of videolaryngoscopy was also associated with a significantly better view of the glottis and with a less rate of airway mucosal trauma. Videolaryngoscopy has added value for the experienced anaesthetist, improving first-time success, the view of the glottis and reducing mucosal trauma. It could become a standard of care in the initial management of the known difficult airway.

scholarly journals A Grounded Theory Exploration of Language Massive Open Online Courses (LMOOCs): Understanding Students’ Viewpoints

2021 ◽  
Vol 13 (5) ◽  
pp. 2577
Author(s):  
Robert Li-Wei Hsu
Keyword(s):  
Grounded Theory ◽  
Theoretical Model ◽  
Online Courses ◽  
Internet Access ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
English For Specific Purposes ◽  
Massive Open Online ◽  
Innovation In Education ◽  
High Dropout Rate

Massive open online courses (MOOCs) have been called the biggest innovation in education in 200 years for their unique attribute of being open and free to any individual with Internet access; however, their high dropout rate has led many people to be concerned or dubious about their effectiveness and applicability. The applicability of MOOCs in English for specific purposes (ESP) courses (in this case, hospitality English) needs more empirical evidence; the present study intends to help fill this gap and extend our current understanding of this issue. This study followed a grounded theory methodology to develop a theoretical model based on a constant dialogue between collected data and the literature. The results suggest that most participants had positive perceptions of language MOOCs (LMOOCs) in general, but some doubted their applicability. Most participants said they would continue to use LMOOCs for learning, depending on the attributes of specific courses. Based on the extracted data, a conceptual model for the applicability of LMOOCs is proposed.

scholarly journals Efectos del entrenamiento de fuerza sobre la condición física en niños y niñas con sobrepeso y obesidad: una revisión sistemática (Effects of strength training on the fitness in boys and girls with overweight and obesity: a systematic review)

Retos ◽  
2021 ◽  
Vol 43 ◽  
pp. 233-242
Author(s):  
Luis Le-Cerf Paredes ◽  
Pablo Valdés-Badilla ◽  
Eduardo Guzman Muñoz
Keyword(s):  
Systematic Review ◽  
Muscle Strength ◽  
Strength Training ◽  
Physical Condition ◽  
Muscle Power ◽  
Overweight And Obesity ◽  
Google Scholar ◽  
Revisión Sistemática ◽  
Para Determinar ◽  
General Physical

Introducción: Debido a las preocupantes cifras de obesidad infantil y los riesgos para la salud que significa tener este estado nutricional no saludable, nuestro objetivo fue realizar una revisión sistemática para determinar los efectos del entrenamiento de fuerza muscular sobre la condición física general de niños y niñas con sobreopeso y obesidad. Métodos: Se utilizaron las bases de datos PubMed, Science direct, Scopus, SciELO y Google Scholar. Los estudios que cumplieron los criterios de inclusión fueron valorados en cuanto a su calidad metodológica a través de la escala PEDro. Resultados: Los estudios señalan que el entrenamiento de fuerza cuando es aplicado de manera aislada aumenta la fuerza muscular, flexibilidad, potencia muscular, agilidad y capacidad cardiorrespiratoria en niños y niñas con sobrepeso y obesidad. Cuando el entrenamiento de fuerza se combinó con actividades aeróbicas se observaron aumentos significativos de la fuerza muscular, capacidad cardiorrespiratoria y flexibilidad Conclusiones: A pesar de la diversidad de los estudios, el entrenamiento de fuerza muscular parece tener un efecto positivo en la condición física general de los niños y niñas con sobrepeso y obesidad. Abstract. Introduction: Due to the worrying figures for childhood obesity and the health risks of having this unhealthy nutritional state, our objective was to carry out a systematic review to determine the effects of muscle strength training on the general physical condition of boys and girls overweight and obese. Methods: PubMed, Science direct, Scopus, SciELO and Google Scholar databases were used. The studies that met the inclusion criteria were assessed for their methodological quality using the PEDro scale. Results: Studies indicate that strength training when applied in isolation increases muscle strength, flexibility, muscle power, agility, and cardiorespiratory capacity in overweight and obese boys and girls. When strength training was combined with aerobic activities, significant increases in muscle strength, cardiorespiratory capacity and flexibility were observed. Conclusions: Despite the diversity of studies, muscle strength training seems to have a positive effect on the general physical condition of overweight and obese boys and girls.

scholarly journals Massive Open Online Courses (MOOCs) Dropout Rate in the World: A Systematic Review Protocol

2020 ◽  
Author(s):  
Manoosh Mehrabi ◽  
Ali Reza Safarpour ◽  
Abbas Ali Keshtkar
Keyword(s):  
Systematic Review ◽  
Online Courses ◽  
Meta Analysis ◽  
Dropout Rate ◽  
Open Science ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
The World ◽  
Review Protocol ◽  
Science Framework

Abstract BackgroundRecently, massive open online courses (MOOCs) have received increasing popularity throughout the world. Regardless of the subject taught and the university providing the course, the dropout rate of MOOCs is one of the most important challenges ahead.Methods This systematic review will search MEDLINE/PubMed, Scopus, Web of Science (Clarivate Analytics), Embase (Embase.com), ASSIA, CINAHL, Education Research, BEI, and Eric databases systematically according to predefined criteria without language restrictions to retrieve prospective and retrospective observational studies conducted between the 1st of January 2000 and 30th of March 2020 which evaluated the frequency of leaving MOOCs throughout the world. In the absence of severe methodological heterogeneity, the data will be combined and a meta-analysis will be performed. DiscussionAs dropout rate is one of the most challenges that universities may encounter, this systematic review will help universities extend their view, save their resources or maybe design their MOOCs differently.RegistrationRegistered in Open Science Framework, available at: https://osf.io/jgyqx/

scholarly journals Investigating Student Satisfaction With Online Courses

2021 ◽  
Vol 17 (3) ◽  
pp. 12-28
Author(s):  
Jeetendra Pande ◽  
Mythili G.
Keyword(s):  
Student Satisfaction ◽  
Support Services ◽  
Online Courses ◽  
Dropout Rate ◽  
Satisfaction Survey ◽  
Statistical Measures ◽  
High Dropout Rate ◽  
The University ◽  
Students Satisfaction ◽  
Study Center

The educational system has moved towards digitization and online learning in the past two decades. The institutions are focusing on delivering online courses to facilitate the students. Uttarakhand Open University offered online courses to reach the unreached learners. High dropout rate from MOOCs is a global concern. Learners' satisfaction survey is one of the important instruments to investigate the reasons of discontinuance from an online course. Detailed analysis of learners' satisfaction survey will help the educators understand learners' expectations from the course and they can work on these factors which leads to increasing the learners' satisfaction with MOOCs and thereby address high-dropout rates from MOOCs. This paper investigates the students' satisfaction of online courses on academic counselling, assignments, and examination marking process and various support services provided by the university. A structed questionnaire of 5-point Likert scale was administrated using Google form. The data (269 valid responses) have been analysed quantitatively by implying statistical measures. The findings show that academic counselling provided by the university to students are conceptual, clear, and knowledgeable. The students are comfortable on assignment, examination, and their result declarations. Along with this the online services, different initiatives and other support services provided by university are discussed in detail and suggested for further enhancements. Furthermore, it is also concluded that the study center structure is adequate, and personnel at study center are very helpful with students.

scholarly journals Dropout Time and Learners’ Performance in Computer Programming MOOCs

2021 ◽  
Vol 11 (10) ◽  
pp. 643
Author(s):  
Marili Rõõm ◽  
Marina Lepp ◽  
Piret Luik
Keyword(s):  
Quantitative Study ◽  
Computer Programming ◽  
Online Courses ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
Dropping Out ◽  
Massive Open Online ◽  
High Dropout Rate ◽  
Different Levels

One of the problems regarding MOOCs (Massive Open Online Courses) is the high dropout rate. Although dropout periods have been studied, there is still a lack of understanding of how dropout differs for MOOCs with different levels of difficulty. A quantitative study was conducted to determine the periods with the highest dropouts in computer programming MOOCs and the performance of the dropouts on the course before dropping out. Four occurrences of three MOOCs, with different durations, difficulty of the topic, and the degree of supportive methods, were included. The results showed that dropout was highest at the beginning of all studied courses. Learners also dropped out before the project. In the easier and shorter courses, most dropouts were successful until they quit the course. In longer and more difficult courses, learners mainly dropped out in the week they started due to experiencing problems with the course activities. It is suggested to recommend that learners take courses at a level that suits them if their current course is too easy or difficult and encourage learners to use course resources for help. It would be a good idea to provide learners with example topics to assist them in starting with a project.

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 Understanding Dropouts in MOOCs

2019 ◽  
Vol 33 ◽  
pp. 517-524 ◽  
Author(s):  
Wenzheng Feng ◽  
Jie Tang ◽  
Tracy Xiao Liu
Keyword(s):  
Online Courses ◽  
Interaction Network ◽  
Dropout Rate ◽  
Drop Out ◽  
Feature Interaction ◽  
Modeling Framework ◽  
High Dropout Rate ◽  
Feature Values ◽  
Major Factors ◽  
Method Model

Massive open online courses (MOOCs) have developed rapidly in recent years, and have attracted millions of online users. However, a central challenge is the extremely high dropout rate — recent reports show that the completion rate in MOOCs is below 5% (Onah, Sinclair, and Boyatt 2014; Kizilcec, Piech, and Schneider 2013; Seaton et al. 2014).What are the major factors that cause the users to drop out?What are the major motivations for the users to study in MOOCs? In this paper, employing a dataset from XuetangX1, one of the largest MOOCs in China, we conduct a systematical study for the dropout problem in MOOCs. We found that the users’ learning behavior can be clustered into several distinct categories. Our statistics also reveal high correlation between dropouts of different courses and strong influence between friends’ dropout behaviors. Based on the gained insights, we propose a Context-aware Feature Interaction Network (CFIN) to model and to predict users’ dropout behavior. CFIN utilizes context-smoothing technique to smooth feature values with different context, and use attention mechanism to combine user and course information into the modeling framework. Experiments on two large datasets show that the proposed method achieves better performance than several state-of-the-art methods. The proposed method model has been deployed on a real system to help improve user retention.

scholarly journals Personalized Online Learning

2021 ◽  
Vol 16 (6) ◽  
pp. 1-15
Author(s):  
Benmedakhene Nadira ◽  
Derdour Makhlouf ◽  
Mohamed Amroune
Keyword(s):  
Online Courses ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
Educational Institutions ◽  
Learning Needs ◽  
Massive Open Online ◽  
Learning Path ◽  
Common Problems ◽  
Term Data

The success of MOOC (massive open online courses) is rapidly increasing. Most educational institutions are highly interested in these online platforms, which embrace intellectual and educational objectives and provide various opportunities for lifelong learning. However, many limitations, such as learners' diversity, lack of motivation, affected learners' outcomes, which unfortunately raised the dropout rate. Thus, multiple solutions were afforded on MOOC platforms to tackle these common problems. This paper suggests a model outline of a customizable system Context-Driven Massive Open Online Courses that could be implemented in any learning environment, and that goes hand in hand with learners' context to boost their motivation towards learning, and to help identify their learning needs. The paper introduces CD-MOOC following a learner-based approach by employing two types of users' data; long-term and short-term data assembled form learners' online traces when interacting on the platform. The data help users design their own learning path based on their context and preferences.

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