Design of a personalised adaptive ubiquitous learning system

ABSTRACT

With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to meet individual learner’s requirements and promote the effectiveness and performance of the learning process. Furthermore, the study used an experimental control group to ascertain the significance of learners’ learning styles and preferences in improving learning performance. The model considers different modules such as personalisation, location support, learning plan and context awareness while relying on the proper classification of learners’ learning styles. The system was experimented using 127 learners of a Computer Science Course. The result obtained using 10-fold cross-validation on various algorithms shows better performance in ROC, Kappa and Accuracy, which were all used to evaluate the quality of classification outcome and compared with learners’ performances in assessments. During classification, Naïve Bayes Model has the highest average ROC value of 0.979, TP Rate of 0.951 and FP Rate of 0.045. The results obtained show an improvement in learning.

KEYWORDS:

• Personalisation
• adaptive
• context awareness
• learning style
• ubiquitous

Disclosure statement

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

Additional information

Funding

This work was supported by TET Fund National Research Fund

Notes on contributors

O. S. Adewale

Professor O. S. Adewale is Professor in the Department of Computer Science, School of the Computing Federal University of Technology, Akure, Nigeria. He is presently the Dean of the School of Computing, Federal University of Technology, Akure. He has published many articles in local and international reputed journals. His research areas include Computer Networks, Soft Computing, Cloud Computing, Computer Architecture and Personalised e-learning systems.

O. C. Agbonifo

Dr. (Mrs.) O. C. Agbonifo holds a Ph.D. degree in Computer Science and she is an associate professor in the Department of Information Systems, School of Computing, Federal University of Technology Akure. She has published several articles in reputable local and international journals and conferences. Her research interests are personalised and adaptive e-learning systems; digital game-based learning systems; software engineering and artificial intelligence. She has been teaching many courses at undergraduate and postgraduate levels at the Federal University of Technology, Akure, Nigeria.

E. O. Ibam

Dr. E. O. Ibam has a Ph.D. (Computer Science), M.Sc (Computer Science) and B.Sc. (Computer Science & Statistics) from the Federal University of Technology Akure (FUTA), Ahmadu Bello University Zaria and the University of Nigeria, Nsukka, respectively. He is a Lecturer in the Department of Information Systems, Federal University of Technology Akure, Nigeria. He travels widely, attends international conferences, and has published in some reputable local and international journals. His research areas include Software Engineering, Intelligent Systems, E-learning systems, Soft Computing and Systems Modeling.

A. I. Makinde

Dr. A. I. Makinde holds a Ph.D.degree in Computer Science. He completed his Ph.D programme under the supervision of Prof. O. S. Adewale, Dr. (Mrs.) O. C. Agbonifo and Dr. (Mrs.) O. K. Boyinbode at the Federal University of Technology, Akure. His research work focuses on Personalisation, Adaptation and Ubiquitous learning system. He is also a System Programmer with the Federal University of Technology, Akure, Ondo State, Nigeria.

O. K. Boyinbode

Professor.(Mrs.) O. K. Boyinbode holds a Ph.D. degree in Computer Science. She is an Professor in the Department of Information Technology, Federal University of Technology, Akure. She has published several articles in reputable local and international journals. Her research areas are Mobile and Ubiquitous Computing, and Computer Networks. She has been teaching many courses at undergraduate and postgraduate levels at the Federal University of Technology, Akure, Nigeria.

B. A. Ojokoh

Professor. (Mrs.) B. A. Ojokoh holds a Ph.D. degree in Computer Science. She is an Professor in the Department of Information Systems, Federal University of Technology, Akure. She has published several articles in reputable local and international journals. Her research area includes Web Mining, Intelligent Information Management, and Digital Libraries. She has been teaching many courses at undergraduate and postgraduate levels at the Federal University of Technology, Akure, Nigeria.

O. Olabode

Professor O. Olabode is a Professor in the Department of Computer Science, Federal University of Technology, Akure, Nigeria. He has published many articles in local and international reputable journals. His research area includes Softcomputing, Machine Learning, e-Commerce.

M. S. Omirin

Professor M. S. Omirin is a professor in the Department of Tests, Measurement and Evaluation, Ekiti State University, Ado Ekiti, Ekiti State, Nigeria. He has published many articles in local and international journals.

S. O. Olatunji

Professor S. O. Olatunji is a professor in the Department of Psychology, Ekiti State University, Ado Ekiti, Ekiti State, Nigeria. He has published many articles in local and international reputable journals.