Analysis of Student Performance in E-learning Environment using Crow search based Fuzzy clustering

2021 ◽  
Author(s):  
Parvathavarthini S ◽  
Sharvanthika K S ◽  
Jagadeesh M ◽  
Kishore B
Keyword(s):  
Learning Environment ◽  
Student Performance ◽  
Fuzzy Clustering ◽  
E Learning

A Literature Review of Student Performance Prediction in E-Learning Environment

2020 ◽  
Vol 01 (01) ◽  
pp. 22-36
Author(s):  
Ruth Chweya ◽  
Siti Mariyam Shamsuddin ◽  
Samuel-Soma M. Ajibade ◽  
Samuel Moveh
Keyword(s):  
Literature Review ◽  
Learning Environment ◽  
Student Performance ◽  
Performance Prediction ◽  
E Learning

The digital age: is this the future of medical education? A cross-sectional study to assess medical students’ opinions about e-learning in psychiatry undergraduate medical education

2014 ◽  
Vol 31 (2) ◽  
pp. 89-96
Author(s):  
D. Mullins ◽  
F. Jabbar ◽  
N. Fenlon ◽  
K. C. Murphy
Keyword(s):  
Medical Education ◽  
Medical Students ◽  
Learning Environment ◽  
Learning Styles ◽  
Student Performance ◽  
Undergraduate Medical Education ◽  
Cross Sectional Study ◽  
Virtual Learning Environment ◽  
Cross Sectional ◽  
E Learning

ObjectivesThe main objectives were to assess medical students’ opinions about e-learning in psychiatry undergraduate medical education, and to investigate a possible relationship between learning styles and preferences for learning modalities.MethodDuring the academic year 2009/2010, all 231 senior Royal College of Surgeons in Ireland (RCSI) medical students in their penultimate year of study were invited to answer a questionnaire that was posted online on Moodle, the RCSI virtual learning environment.ResultsIn all, 186 students responded to the questionnaire, a response rate of 80%. Significantly more students stated a preference for live psychiatry tutorials over e-learning lectures. Students considered flexible learning, having the option of viewing material again and the ability to learn at one’s own pace with e-learning lectures, to be more valuable than having faster and easier information retrieval.ConclusionStudents prefer traditional in-class studying, even when they are offered a rich e-learning environment. Understanding students’ learning styles has been identified as an important element for e-learning development, delivery and instruction, which can lead to improved student performance.

scholarly journals Predicting Students’ Performance In Basic Algorithms Programming In an E-Learning Environment Using Decision Tree Approach

2022 ◽  
Vol 7 (1) ◽  
pp. 498
Author(s):  
Jonas De Deus Guterres ◽  
Kusuma Ayu Laksitowening ◽  
Febryanti Sthevanie
Keyword(s):  
Learning Environment ◽  
Decision Tree ◽  
Student Performance ◽  
Information Gain ◽  
Quality Data ◽  
Basic Algorithm ◽  
Id3 Algorithm ◽  
E Learning ◽  
Advanced Analysis ◽  
Quality In Higher Education

Predicting the performance of students plays an important role in every institution to protect their students from failures and leverage their quality in higher education. Algorithm and Programming is a fundamental course for the students who start their studies in Informatics. Hence, the scope of this research is to identify the critical attributes which influence student performance in the E-learning Environment on Moodle LMS (Learning Management System) Platform and its accuracy. Data mining helps the process of preprocessing data in a dataset from raw data to quality data for advanced analysis. Dataset set is consisting of student academic performance such as grades of Quizzes, Mid exams, Final exams, and Final projects. Moreover, the dataset from LMS is considered as well in the process of modeling, in terms of constructing the decision tree, such as punctuality submission of Quizzes, Assignments, and Final Projects. Regarding the Basic Algorithm and Programming course, which is separated into two subjects in the first and second semester, thus the research will predict the student performance in the Basic Algorithm and programming course in the second semester based on the Introduction to programming course in the first semester. Decision Tree techniques are applied by using information gain in ID3 algorithm to get the important feature which is the PP index has the highest information gain with value 0.44, also the accuracy between ID3 and J48 algorithm that shows ID3 has the highest accuracy of modeling which is 84.80% compared to J48 82.34%.

THE PROCESS OF DIGITALIZATION OF EDUCATIONAL INSTITUTIONS

2020 ◽  
Author(s):  
Муса Увайсович Ярычев
Keyword(s):  
Learning Environment ◽  
Education System ◽  
New Teacher ◽  
Educational Institutions ◽  
Quality Of Education ◽  
Necessary Condition ◽  
Teacher Competencies ◽  
Important Condition ◽  
E Learning

В статье рассматривается вопрос о цифровизации школы, как важном условии повышения качества образования. Организованная при помощи электронных форм среда обучения предоставляет ученикам большую самостоятельность. Необходимым условием совершенствования системы образования выступает создание новых, необходимых для цифровой экономики компетенций педагога. The article considers the issue of school digitalization as an important condition for improving the quality of education. The e-learning environment provides students with greater independence. A necessary condition for improving the education system is the creation of new teacher competencies necessary for the digital economy.

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