Enitan Olabisi Adebayo

Work place: Department of Computer Science, Federal College of Education (Sp.), Oyo, Nigeria

E-mail: adebayoenitan2018@gmail.com

Website:

Research Interests: Data Structures and Algorithms, Computational Learning Theory, Computer systems and computational processes, Computational Science and Engineering

Biography

Enitan Olabisi Adebayo is currently working as Lecturer III in the Department of Computer Science, School of Secondary Education (Science Programmes), Federal College of Education (Special), Oyo, Nigeria. She completed her Nigeria Certificate in Education (NCE) from the Federal College of Education (Special), Oyo, Nigeria in Computer Science. She has completed her B.Sc. (Ed.) and M.Sc. degrees in Computer Science from Ekiti State University and the University of Ibadan respectively. She also completed a one-semester M.Sc. degree at Birmingham City University, United Kingdom where she obtained a Transcript of Learning and Achievement Certificate (Certificate of Achievement 2018/9 Regulations – UG). Her research interest includes Educational Technology, Knowledge Representation, Formal Ontologies, Machine Learning, ICT, and Data Science.

Author Articles
Efficacy of Assistive Technology for Improved Teaching and Learning in Computer Science

By Enitan Olabisi Adebayo Ibiyinka Temilola Ayorinde

DOI: https://doi.org/10.5815/ijeme.2022.05.02, Pub. Date: 8 Oct. 2022

This study examined the efficacy of assistive technology (AT) for improved teaching and learning in computer science (a case study of an inclusive educational system). Two (2) hypotheses were formulated and tested for this study. A descriptive survey method was adopted for this study, the population of this study comprises all Students with special needs and all teachers teaching at Durbar Grammar School, Oyo, Oyo State, Nigeria. A purposive sampling technique was used to select twenty (20) respondents (teachers) and all the Students with special needs were involved (40). A structured questionnaire of two sections (sections A and B to be answered by the Teachers and the Students respectively) which was validated and tested for reliability was used; a reliability coefficient of 0.81 was obtained. Simple percentages and the Chi-square statistical method were used to analyze the collected data which was tested with this study’s hypotheses. The results of this study revealed that AT is capable of improving the teaching and learning of computer science for Students with special needs in an inclusive education if AT is allowed to play its role. It was also discovered that both the teacher and students with special needs were exposed to very little AT and there was no periodical training programme for both the teachers and the students with special needs on the use of AT which has affected their teaching and learning ability. This paper, therefore recommends that a periodical training programme on the use of AT be organized by all the stakeholders in inclusive education for both the students with special needs and all the teachers teaching them.

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