Skip to content
Research Article Open access CC BY 4.0

A Framework of Concept Complexity-based Personalized E-learning System

A. T. Adesuyi, O. A. Obolo, S. V. Oloja, Bukola Badeji-Ajisafe

Journal of Education, Society and Behavioural Science · pp. 1–6 · Published 13 Apr 2018

10.9734/JESBS/2018/39320

Abstract

Personalized learning allows individual learner to be taught and assessed in ways that are appropriate and comfortable for that learner. It allows teaching to be carried out in several ways in order to increase the scope of learning. Personalized learning is an important aspect of e-learning systems because no particular learning path will be adequate for all learners. Hence, this research paper presents a framework of concept complexity-based personalized e-learning system. Some existing works on personalized e-learning have dealt with learner’s preference without considering the complexity/difficulty level of the course concepts and the degree of relationship that exist between the various course concepts. Other works also prevented the students from gaining the freedom to rearrange the course concepts in the most individually preferred order. Hence, this affects the learning ability and the overall performance of learners. Therefore, by allowing the learners to know the complexity/difficulty level of each of the course concepts and giving learners the freedom to rearrange the course concepts in the order they will like to learn will not only improve the learning ability of learners but will also give personalized e-learning an edge.

Personalized e-learning course concepts difficulty parameters individual learner concept complexity.

Cited by 2

Enhancing Personalized Feedback in Adaptive E-Learning Systems: A Neural Network Approach

H. R. Ahamed, D. Hanirex · 2024 International Conference on Data Science and Network Security (ICDSNS) · 2024

Step by Step Implementation of DSRM for Personalization of Reading

Marzita Mansor, Wan Adilah Wan Adnan, R. A. Wahid · International Journal of Humanities Management and Social Science · 2021

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

2

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.