Analysis of Student Behaviour in e-Learning Courses in Relation to Academic Performance

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17450%2F20%3AA21026UR" target="_blank" >RIV/61988987:17450/20:A21026UR - isvavai.cz</a>

Result on the web

<a href="https://www.academic-conferences.org/conferences/ecel/" target="_blank" >https://www.academic-conferences.org/conferences/ecel/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Analysis of Student Behaviour in e-Learning Courses in Relation to Academic Performance

Original language description

E-Learning is now widely used in education. However, it is the feedback on how students use the course that is important for course creators and teachers alike. The article deals with the application of learning analytics to identify relationships between the variables of students’ behaviour when studying in LMS Moodle, continuous testing during the semester and the score achieved in the final test. The overall approach of students to the course is monitored as well. We focus on current approaches and results in the literature. We describe, relative to the present findings, the approach that was chosen for the analysis of students’ behaviour when studying in LMS. The method of choice is a quantitative analysis of the students’ behaviour, their visits, the length of these visits, the total period of study and repeated visits on the same calendar day. The aim of the data analysis is to be able to understand students’ studying behaviour on the basis of their activity records in the course. We also aim to draw more general relationships based on the understanding of the specific relationships that exist between the variables, so that the course designer can make appropriate adjustments to the e-Learning course or its use in teaching. The proposed data analysis is applied to four e-Learning courses taught in our workplace. We compare an experiment that examines the impact of regular testing during the semester on final academic performance in comparison with a method of teaching without testing. Here we identify statistically significant differences in both the students’ approach to studying and the final academic performance. Regular testing during the semester clearly tends to result in higher scores in the final test. However, regular testing blurs the differences of the individual students’ approach to studying. We then apply the data analysis of academic records to two other e-Learning courses with different teaching concepts and with focus on dependency comparison.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

50301 - Education, general; including training, pedagogy, didactics [and education systems]

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 19th European Conference on e-Learning ECEL 2020

ISBN

978-1-912764-78-5

ISSN

2048-8637

e-ISSN

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Number of pages

9

Pages from-to

428-437

Publisher name

Academic Conferences International Limited

Place of publication

Reading

Event location

Berlin

Event date

Oct 28, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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