Oluwatoyin C. Agbonifo

Work place: Department of Information Systems, Federal University of Technology, Akure, Ondo State, Nigeria

E-mail: ocagbonifo@futa.edu.ng


Research Interests: Software Engineering, Computer systems and computational processes, Artificial Intelligence, Data Structures and Algorithms


Oluwatoyin C. Agbonifo obtained her PhD degree in Computer Science from the Federal University of Technology, Akure, Nigeria. She is an Associate Professor in the Department of Information Systems, Federal University of Technology, Akure, Nigeria. She has authored/co-authored a number of articles at both local and international refereed journals and conference proceedings. She is a regular reviewer in local as well as international scientific/academic journals. She is a member of the NCS, CPN, IEEE, AACE and OWSD. Her research interest areas include: Personalised and Adaptive Ubiquitous learning, Digital Game-Based Learning, Software Engineering and Artificial Intelligence.

Author Articles
Design of a Digital Game-based Learning System for Fraction Algebra

By Oluwatoyin C. Agbonifo Olutayo K. Boyinbode Fisayo N. Oluwayemi

DOI: https://doi.org/10.5815/ijmecs.2021.05.04, Pub. Date: 8 Oct. 2021

Digital game based learning (DGBL) system is a promising area of research and debate, as it promotes contextualized learning, creates and harnesses motivation in learning capacities and encourages curiosity. DGBL takes place in a technological-mediated environment while engaging players in a learning activity through the support of computers. Several digital game based learning systems have been deployed for educational purposes to aid or support students in hands-on-learning experiences and constructive knowledge that involves mental reasoning processes. Hence, the research paper presented a development of digital game based fraction algebra learning system which is associated with game principle of snakes and ladders with underpinned concept of step-by-step procedure of solving mathematical problems. The system was tested by participants of FUTA staff primary school and the results of performance evaluation showed that the system could greatly support students to learn effectively the fraction algebra through game technology and would increase the students’ thinking process.

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Genetic Algorithm-based Curriculum Sequencing Model For Personalised E-Learning System

By Oluwatoyin C. Agbonifo Olanrewaju A. Obolo

DOI: https://doi.org/10.5815/ijmecs.2018.05.04, Pub. Date: 8 May 2018

Personalised learning is a way of organising the learning content and to be accessed by the individual learner in a manner that is suitable to learner’s requirements. There are existing related works on personalised e-learning systems that focused on learner’s preference without considering the difficulty level and the relationship degree that exists between various course concepts. Hence, these affect the learning ability and the overall performance of learners. This research paper presents a genetic algorithm-based curriculum sequencing model in a personalised e-learning environment. It helps learners to identify the difficulty level of each of the curriculum or course concepts and the relationship degree that exists between the course concepts in order to provide an optimal personalised learning pattern to learners based on curriculum sequencing to improve the learning performance of the learners. The result of the implementation showed that the genetic algorithm is suitable to generate the optimal learning path using the values of difficulty level and relationship degree of course concepts. Furthermore, the system classified the learners into three different understanding levels of the course concepts such as partially, moderately and highly successful.

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