scholarly journals Gamification Increases Completion Rates in Massive Open Online Courses

2022 ◽  
Vol 18 (1) ◽  
pp. 0-0
Keyword(s):  
Online Courses ◽  
Course Completion ◽  
Dropout Rate ◽  
Completion Rate ◽  
Massive Open Online Courses ◽  
Dropout Rates ◽  
Completion Rates ◽  
Massive Open Online ◽  
High Dropout Rate ◽  
Course Completion Rate

Massive Open Online Courses (MOOCs) aim at unlimited participation and open access via the web. There are concerns about the actual value of such courses. This is predominantly due to higher dropout rates. According to studies, only 7-13% go on to complete these courses. The high dropout rate in MOOCs is a challenge for education providers. This paper aims to explore reasons for high dropout rates within MOOCs and how they can be minimized. With this in mind, two research questions have been set for this study: 1) Why do MOOC participants not complete their courses? 2) How can the course completion rate be increased? Implementation of the strategies investigated in this paper can increase completion rates in MOOCs. In conclusion, after analyzing the collected data, the final results have shown that gamification increased the completion rate of MOOCs.

scholarly journals Massive open online course completion rates revisited: Assessment, length and attrition

2015 ◽  
Vol 16 (3) ◽  
Author(s):  
Katy Jordan
Keyword(s):  
Online Courses ◽  
Course Completion ◽  
Massive Open Online Courses ◽  
Online Course ◽  
Completion Rates ◽  
Massive Open Online ◽  
Attrition Rates ◽  
Start Date ◽  
Massive Open Online Course ◽  
Course Length

<p>This analysis is based upon enrolment and completion data collected for a total of 221 Massive Open Online Courses (MOOCs). It extends previously reported work (Jordan, 2014) with an expanded dataset; the original work is extended to include a multiple regression analysis of factors that affect completion rates and analysis of attrition rates during courses. Completion rates (defined as the percentage of enrolled students who completed the course) vary from 0.7% to 52.1%, with a median value of 12.6%. Since their inception, enrolments on MOOCs have fallen while completion rates have increased. Completion rates vary significantly according to course length (longer courses having lower completion rates), start date (more recent courses having higher percentage completion) and assessment type (courses using auto grading only having higher completion rates). For a sub-sample of courses where rates of active use and assessment submission across the course are available, the first and second weeks appear to be critical in achieving student engagement, after which the proportion of active students and those submitting assessments levels out, with less than 3% difference between them.</p>

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 Framework for Personalizing Mooc Courses based on Learners’ Stress Levels Towards Increased Course Completion Rates

2019 ◽  
Vol 8 (9) ◽  
pp. 2721-2724
Keyword(s):  
Online Courses ◽  
Course Completion ◽  
Content Delivery ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Massive Open Online ◽  
Online Learners ◽  
Learning Platform ◽  
Stress Levels ◽  
Open Nature

Massive Open Online Courses (MOOC) has gained a huge popularity amongst the current generation students mainly because of its open nature and its ubiquity. MOOC made it possible for thousands of aspiring learners to learn from their favorite Universities. Though this online learning platform has its advantages, many studies have proved that these massive courses are suffering from tremendous rates in students’ dropouts. This study surveys the major causes of dropouts and would try to link the MOOC failures with the learners’ stress levels. The study also proposes a framework which could be used while designing MOOC courses and will help MOOC providers to personalize the content delivery according to the online learners’ stress levels.

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 A grounded theory exploration of language massive open online courses (LMOOCs): Understanding students’ viewpoints

2020 ◽  
Author(s):  
Liwei Hsu
Keyword(s):  
Grounded Theory ◽  
Theoretical Model ◽  
Empirical Evidence ◽  
Online Courses ◽  
Internet Access ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
English For Specific Purposes ◽  
Massive Open Online ◽  
High Dropout Rate

Abstract Massive open online courses (MOOCs) have been called the biggest innovation to happen in education for 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 MOOCs’ 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 constant dialogue between collected data and the literature. The results suggest that most participants had positive perceptions of LMOOCs in general but that some of them doubted the applicability of LMOOCs. Most participants said they would continue to use LMOOCs in 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 A Grounded Theory Exploration of Language Massive Open Online Courses (LMOOCs): Understanding Students’ Viewpoints

2020 ◽  
Author(s):  
Liwei Hsu
Keyword(s):  
Grounded Theory ◽  
Theoretical Model ◽  
Empirical Evidence ◽  
Online Courses ◽  
Internet Access ◽  
Dropout Rate ◽  
Massive Open Online Courses ◽  
English For Specific Purposes ◽  
Massive Open Online ◽  
High Dropout Rate

Abstract Massive open online courses (MOOCs) have been called the biggest innovation to happen in education for 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 MOOCs’ 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 constant dialogue between collected data and the literature. The results suggest that most participants had positive perceptions of LMOOCs in general but that some of them doubted the applicability of LMOOCs. Most participants said they would continue to use LMOOCs in 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 How MOOC-Takers Estimate Learning Success: Retrospective Reflection of Perceived Benefits

2018 ◽  
Vol 19 (5) ◽  
Author(s):  
Svetlana Sablina ◽  
Natalia Kapliy ◽  
Alexandr Trusevich ◽  
Sofia Kostikova
Keyword(s):  
Text Analysis ◽  
Career Education ◽  
Online Courses ◽  
Course Completion ◽  
Massive Open Online Courses ◽  
Learning Technology ◽  
Perceived Benefits ◽  
Massive Open Online ◽  
Learning Success ◽  
New Learning

Massive open online courses (MOOCs) have attracted a great deal of interest in recent years as a new learning technology. Since MOOCs inception, only limited research has been carried out to address how learners perceive success in MOOCs after course completion.  The aim of this study was to investigate the perceived benefits as the measurement of learning success.  Narrative interviews were conducted with 30 Russian-speaking learners who completed at least one MOOC in full.  By employing text analysis of interview transcripts, we revealed the authentic voices of participants and gained deeper understanding of learners' perceived benefits based on retrospective reflection. The findings of the study indicate that after finishing MOOCs, learners have received tangible and intangible benefits that in general justified their expectations.  University-affiliated students, as well as working professionals, recognized the complementarity of MOOCs, but their assessments were limited to educational tracks. We discovered that taking MOOCs often coincided with the time when an individual was planning to change career, education, or life tracks.  The results of the study and their implications are further discussed, together with practical suggestions for MOOC providers.

scholarly journals Initial trends in enrolment and completion of massive open online courses

2014 ◽  
Vol 15 (1) ◽  
Author(s):  
Katy Jordan
Keyword(s):  
Online Courses ◽  
Rapid Development ◽  
Good Deal ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Massive Open Online ◽  
Factors Affecting ◽  
The Public ◽  
The Past ◽  
Course Length

<p>The past two years have seen rapid development of massive open online courses (MOOCs) with the rise of a number of MOOC platforms. The scale of enrolment and participation in the earliest mainstream MOOC courses has garnered a good deal of media attention. However, data about how the enrolment and completion figures have changed since the early courses is not consistently released. This paper seeks to draw together the data that has found its way into the public domain in order to explore factors affecting enrolment and completion. The average MOOC course is found to enroll around 43,000 students, 6.5% of whom complete the course. Enrolment numbers are decreasing over time and are positively correlated with course length. Completion rates are consistent across time, university rank, and total enrolment, but negatively correlated with course length. This study provides a more detailed view of trends in enrolment and completion than was available previously, and a more accurate view of how the MOOC field is developing.</p>

scholarly journals Troubleshooters for Tasks of Introductory Programming MOOCs

2018 ◽  
Vol 19 (4) ◽  
Author(s):  
Marina Lepp ◽  
Tauno Palts ◽  
Piret Luik ◽  
Kaspar Papli ◽  
Reelika Suviste ◽  
...  
Keyword(s):  
Online Courses ◽  
Assessment System ◽  
Massive Open Online Courses ◽  
Completion Rates ◽  
Massive Open Online ◽  
Automated Assessment ◽  
Persistent Problem ◽  
Help Systems ◽  
The Masses ◽  
Learning Programming

Learning programming has become more and more popular and organizing introductory massive open online courses (MOOCs) on programming can be one way to bring this education to the masses. While programming MOOCs usually use automated assessment to give feedback on the submitted code, the lack of understanding of certain aspects of the tasks and feedback given by the automated assessment system can be one persistent problem for many participants. This paper introduces troubleshooters, which are help systems, structured like decision trees, for giving hints and examples of certain aspects of the course tasks. The goal of this paper is to give an overview of usability (benefits and dangers) of, and the participants’ feedback on, using troubleshooters. Troubleshooters have been used from the year 2016 in two different programming MOOCs for adults in Estonia. These MOOCs are characterized by high completion rates (50–70%), which is unusual for MOOCs. Data is gathered from the learning analytics integrated into the troubleshooters’ environment, letters from the participants, questionnaires, and tasks conducted through the courses. As it was not compulsory to use troubleshooters, the results indicate that only 19.8% of the users did not use troubleshooters at all and 10% of the participants did not find troubleshooters helpful at all. The main difference that appeared is that the number of questions asked from the organizers about the programming tasks during the courses via helpdesk declined about 29%.

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.

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