An Extensive Analysis on Computing Students' Academic Performance in Online Environment using Decision Tree
Main Article Content
Abstract
Maintaining the continuation of study is a vitalelement as it holds students' concentration to achieve what the external world left them to explore. COVID-19 acts as some kind of a barrier infront of this continuation of study. Online education lifts this barrier and gives the students a free open road to roam around. But to be sure that students are maintaining the pace and continuing their sturdy approach to achieve their goals, there has to be some monitoring.Educational Data Mining (EDM) is a
new discipline that arose from applying data mining techniques to educational data. EDM can be used to understand students and their learning environments better, improve teaching support, and make decisions in educational systems.The main objective of this paper is toanalyze the factors that have a profound impact on students' academic performance while conducting EDM applications, more specifically using decision trees. Four distinct datasets are derived from X University students' academic marks in four different undergraduate program courses during an online semester. The decision trees' knowledge revealscritical factors in analyzing students' performance. The findings of this paperwill help educators develop new strategies to cope with various challenges and ultimately the betterment of education.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
