A Hybrid Soft Computing Approach for Prediction of Cloud-Based Learning Management Systems Determinants

Abstract

A robust, accurate and reliable approach is essential for not only examining people’s acceptance of cloud-based learning management systems in developing nations but also for accurate prediction of factors affecting its implementation and progress. Therefore, in this study, three different soft computing models; Adaptive neuro-fuzzy inference system (ANFIS), Support vector regression (SVR), and Emotional artificial neural network (EANN), were employed for predictions of factors affecting cloud-based learning management systems take-up and progress using data gotten from six Nigerian colleges. The performance of the models was assessed using five arithmetic metrics; MAPE, NSE, RMSE, rRMSE, and RM. All the proposed models forecast the effects of the study inputs on LMS with higher accuracy (NSE > 0.98). However, the SVR model outshone the other models as it increased the performance of the study-reported model by 2% and 4% respectively. Based on the study results, instructors’ quality, motivation, and resource availability were found to be the key factors that affect cloud-based learning technologies take-up and progress in the study area. Interestingly, unlike prior studies, this study found system ease of use and usefulness to have insignificant effects on LMS take-up. Finally, the practical implications and limitations of the study were discussed based on the study findings.

Keywords:

• Cloud-based learning
• soft computing
• support vector regression
• LMS

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Yakubu Bala Mohammed

Yakubu Bala Mohammed, completed his Masters in 2015 at UTM, Malaysia, and his Ph.D. at NEU, Cyprus. His teaching and research areas include but not limited to; Artificial intelligence (AI), and e-Learning. He has many articles published in reputable journals, and serves as editor/reviewer in many reputable journals.

Nadire Cavus

Nadire Cavus is the present Chairperson of the Department of Computer Information Systems at the Near East University. Prof. Dr. Nadire Cavus has several scientific articles published by the famous journals indexes by British Education, Web of science, Science Direct, Scopus, and IEEE.

Abdulsalam Ya’u Gital

Abdulsalam Ya’u Gital is the present Head of Department computer science at ATBU. He completed his B-Tech in 2003 at ATBU, Bauchi, and Masters in the year 2007 at same Universiti, and his Ph.D. in 2015 at UTM, Malaysia. He has many articles published in international journals.

Mohammed Bulama

Mohammed Bulama is a lecturer in the Department of computer science at ATAPoly, Bauchi. He obtained his B-Tech. in 2000 at ATBU, Bauchi and finished his Masters in 2012 at Hull Universiti, UK, and his Ph.D. in 2020 at ATBU, Bauchi. He has many articles published in international journals.

Abba Hassan

Abba Hassan is the present HoD Department of Software Engineering at the Nigerian Army University, Biu. He obtained his PhD and Master’s degrees at the KLIU Malysia, in the years 2021, and 2014 respectively. His areas of research interest include but not limited to software, LMS, and Machine learning.