Random forest application on cognitive level classification of E-learning content

Title

Random forest application on cognitive level classification of E-learning content

Creator

Thomas B.; Chandra J.

Description

The e-learning is the primary method of learning for most learners after the regular academics studies. The knowledge delivery through E-learning technologies increased exponentially over the years because of the advancement in internet and e-learning technologies. Knowledge delivery to some people would never have been possible without the e-learning technologies. Most of the working professional do focused studies for carrier advancement, promotion or to improve the domain knowledge. These learner can find many free e-learning web sites from the internet easily in the domain of interest. However it is quite difficult to find the best e-learning content suitable for their learning based on their domain knowledge level. User spent most of the time figuring out the right content from a plethora of available content and end up learning nothing. An intelligent framework using machine learning algorithms with random forest Classifier is proposed to address this issue, which classifies the e-learning content based on its difficulty levels and provide the learner the best content suitable based on the knowledge level. The frame work is trained with the data set collected from multiple popular e-learning web sites. The model is tested with real time e-learning web sites links and found that the e-contents in the web sites are recommended to the user based on its difficulty levels as beginner level, intermediate level and advanced level. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved.

Source

International Journal of Electrical and Computer Engineering, Vol-10, No. 4, pp. 4372-4380.

Date

2020-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Blooms taxonomy; Difficulty level; E-learning; Machine learning; Random forest classifier

Coverage

Thomas B., Department of Computer Science, CHRIST (Deemed to be University), India; Chandra J., Department of Computer Science, CHRIST (Deemed to be University), India

Rights

All Open Access; Gold Open Access; Green Open Access

Relation

ISSN: 20888708

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijece.v10i4.pp4372-4380

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