IDENTIFYING FACTORS THAT INFLUENCE STUDENTS ' DROPOUTS FROM MOOC COURSES

2020 ◽  
Vol 5 (12) ◽  
pp. 4-16
Author(s):  
T. A. BOYKO ◽  
◽  
P. D. IVANOV ◽  
Keyword(s):  
Logistic Regression ◽  
Distance Learning ◽  
Random Forest ◽  
Decision Trees ◽  
Online Courses ◽  
Educational Process ◽  
Massive Open Online Courses ◽  
Classification Models ◽  
Educational Content ◽  
Massive Open Online

The article considers one of the most popular forms of distance learning – massive open online courses (MOOC). The number of educational content, as well as universities and platforms that develop and provide access to courses, is constantly growing. The relevance of the work is due to the fact that according to various estimates, only 5-13% of students who have signed up for MOOC courses are trained to the end. The aim of the work is to determine the quantitative variables that affect the proportion of students who complete the course. To solve this problem, classification models are used: the model of logistic regression, decision trees and random forest. The obtained results can be used to improve the educational process in online courses.

scholarly journals Development of Massive Open Online Courses Based on 3D Computer Graphics and Multimedia

2019 ◽  
Vol 9 (4) ◽  
pp. 4
Author(s):  
Leonid Leonidovich Khoroshko ◽  
Peter A. Ukhov ◽  
Pavel P. Keyno
Keyword(s):  
Distance Learning ◽  
Computer Graphics ◽  
Online Courses ◽  
Three Dimensional ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Interactive Mode ◽  
Training Materials ◽  
Software Product ◽  
Independent Work

This work is devoted to the creation of a laboratory workshop (virtual) for open online courses based on programs of three-dimensional computer graphics and multimedia. The issues of using SolidWorks, Autodesk® 3DS MAX software in distance learning are discussed. The software was used to prepare training materials for the courses course "Machines and mechanisms theory", "Computer Graphics" and "Engineering and Computer Graphics". Using the software product SolidWorks, Autodesk® 3DS MAX has significantly increased the visibility of the course and develop tools for organizing the independent work of students in an interactive mode.

scholarly journals E-learning Text Sentiment Classification Using Hierarchical Attention Network (HAN)

2021 ◽  
Vol 16 (13) ◽  
pp. 157
Author(s):  
Abdessamad Chanaa ◽  
Nour-eddine El Faddouli
Keyword(s):  
Online Courses ◽  
Research Field ◽  
Massive Open Online Courses ◽  
Analysis Tool ◽  
Classification Models ◽  
Discussion Forums ◽  
Hierarchical Network ◽  
Massive Open Online ◽  
Attention Network ◽  
E Learning

Massive Open Online Courses (MOOCs) have recently become a very motivating research field in education. Analyzing MOOCs discussion forums presents important issues since it can create challenges for understanding and appropriately identifying student sentiment behaviours. Using the high effectiveness of deep learning, this study aims to classify forum posts based on their sentiment polarity using two experiments. The first use the three known sentiment labels (positive/negative/neutral) and the second one employs sevens labels. The classification method implemented the Hierarchical Attention Network (HAN) algorithm; it combines the attention mechanism with a hierarchical network that simulates the same hierarchical structure of the document. The analysis of 29604 discussion posts from Stanford University affirms the effectiveness of our model. HAN achieved a classification accuracy of 70.3%, which surpassed the other prediction results using usual text classification models. These results are promising and have implications on the future development of automated sentiment analysis tool on e-learning discussion forum.

scholarly journals Intellectualization of professional and pedagogical activity based on the integration of pedagogical and digital technologies

2020 ◽  
pp. 83-92
Author(s):  
Natalia P. Goncharuk ◽  
Evgeniya I. Khromova
Keyword(s):  
Blended Learning ◽  
Information And Communication Technologies ◽  
Online Courses ◽  
Digital Technologies ◽  
Educational Environment ◽  
Educational Process ◽  
Open Educational Resources ◽  
Massive Open Online Courses ◽  
Learning Technology ◽  
Massive Open Online

The article is dedicated to the issues of intellectualization of professional and pedagogical activity with the main purpose of continuously development of teachers’ competencies in the field of using digital technologies in the educational process, transformation of the teachers’ activities in accordance with the capabilities of modern information and communication technologies and the digital educational environment. The article highlights the potential of massive open online courses and open educational resources that contribute to the development of ways to effectively use Internet technologies in education. The article points out the role of the pedagogical technologies’ integration with the latest digital technologies in updating and developing the competencies of teachers. The article describes how to use online courses in the educational process, scenarios for integrating online courses into the educational process, technologies for placing educational materials, interaction tools in an electronic informational and educational environment. The article focuses on blended learning technology as a means of implementing an integrated learning model using Internet resources. The article highlights the main characteristics of blended learning technology allowing the use of modern methods and tools of online learning, combining the advantages of educational and digital technologies. Particular attention is paid to the “MOOC discipline support” model which uses massive open online courses as additional material. The article describes variants of methodological support for the process of implementing an online course, Internet services for organizing academic work and networking.

Learning Management in Massive Open Online Courses

2021 ◽  
Vol 12 (1) ◽  
pp. 1-14
Author(s):  
Tapan Kumar Basantia ◽  
Vishal Kumar
Keyword(s):  
Distance Learning ◽  
Online Courses ◽  
Traditional Education ◽  
Vital Role ◽  
Massive Open Online Courses ◽  
Massive Open Online ◽  
Learning Time ◽  
Open And Distance Learning ◽  
Learning Management

Massive open online courses (MOOCs) are the unconventional and latest means of education in the present society. MOOCs are the strong alternative to traditional education and latest development in the area of open and distance learning. MOOCs are the online courses which are delivered with little rigidity in place of learning, time of learning, pace of learning, etc. Learning management in MOOCs is one of the prime features of MOOCs that helps for the delivery of MOOCs. Learning management in MOOCs plays a vital role for the success of MOOCs. The stakeholders of MOOCs must be well conversant with different aspects of learning management in MOOCs for achieving the success of the MOOCs. Referring to these contexts, in the present paper, thematic discussions have been made on different aspects of learning management in MOOCs. In the paper, special emphasis in discussion is given on different components of learning management in MOOCs, learning management in different platforms of MOOCs, and issues in learning management in MOOCs.

scholarly journals Recommendation System for Knowledge Acquisition in MOOCs Ecosystems

2020 ◽  
Author(s):  
Rodrigo Campos ◽  
Rodrigo Santos ◽  
Jonice Oliveira
Keyword(s):  
Distance Learning ◽  
Recommendation System ◽  
Online Courses ◽  
State Of The Art ◽  
Massive Open Online Courses ◽  
Knowledge Gap ◽  
Massive Open Online ◽  
Master's Thesis ◽  
Online Distance Learning ◽  
Online Distance

In recent years, students face difficulties in choosing the best content from the online distance learning of MOOCs (Massive Open Online Courses). The emerged recommendations systems to solve this problem do not identify the student's prior knowledge broadly. From this problem, the main contribution of this work is the identification and reduction of the students' knowledge gap in MOOCs. As such, in this Master's thesis, we model and analyze the MOOCs ecosystems and propose a solution for recommending parts of courses. Based on a set of three experiments, we verify that our recommendations are accurate, useful and reliable. We also present new content to fill the knowledge gap of users as the main contribution of this work to the state of the art.

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