A Review on Visualization of Educational Data in Online Learning

M. Ali Akber Dewan, Walter Moreno Pachon, Fuhua Lin

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

5 Citations (Scopus)

Abstract

Higher educational institutions capture huge amounts of educational data, especially in online learning. Data mining techniques have shown promises to interpret these data using different patterns. However, understanding the mining patterns and extracting meaningful information from the data require reasonable skills and knowledge for the users. Information visualization, due to its potential to display large amount of data, may fill this gap. In this paper, we present a short review of such visualization systems that focus on extracting meaningful information from the educational data. Visualizations have been used in different applications dealing with educational data, especially for monitoring student performance, understanding learning style, analyzing course and program status, and dropout prediction. In this paper, we reviewed the existing visualization systems, their design considerations, and their strengths and weaknesses to analyze educational data in the context of online learning. Research findings indicate that although some progress has been achieved in educational data mining and visualizations, designing and developing effective and easy to understand visualizations and having the functionalities of interactivity and time-series analysis are still challenging. This review provides insight into how to build a learner and instructor focused effective visualization system for an online learning environment.

Original languageEnglish
Title of host publicationLearning Technologies and Systems - 19th International Conference on Web-Based Learning, ICWL 2020, and 5th International Symposium on Emerging Technologies for Education, SETE 2020, Proceedings
EditorsChaoyi Pang, Yunjun Gao, Guanliang Chen, Elvira Popescu, Lu Chen, Tianyong Hao, Bailing Zhang, Silvia Margarita Navarro, Qing Li
Pages15-24
Number of pages10
DOIs
Publication statusPublished - 2021
Event19th International Conference on Web-Based Learning, ICWL 2020 and 5th International Symposium on Emerging Technologies for Education, SETE 2020 - Ningbo, China
Duration: 22 Oct. 202024 Oct. 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Web-Based Learning, ICWL 2020 and 5th International Symposium on Emerging Technologies for Education, SETE 2020
Country/TerritoryChina
CityNingbo
Period22/10/2024/10/20

Keywords

  • Educational data mining
  • Information visualization
  • Learning management system
  • Pattern recognition
  • Visual analytics

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