Assessment of Teachers’ Attitude towards Application of ICT in Teaching Junior Secondary School Students in Selected Secondary Schools in Ilesa, Osun State Nigeria (Published)
This study assessed junior secondary school teachers’ attitudes toward the application of Information and Communication Technology (ICT) in selected schools in Ilesa, Osun State, Nigeria. Specifically, it examined teachers’ knowledge of ICT, their attitudes toward its use in teaching, the factors influencing these attitudes, and the challenges faced in ICT implementation. A cross-sectional descriptive design was adopted, involving 113 teachers from seven randomly selected secondary schools. Data were collected using a structured questionnaire and analyzed with SPSS version 23, employing descriptive and inferential statistics. Findings revealed that while teachers possessed foundational knowledge of ICT and recognized its benefits for enhancing teaching efficiency and student engagement, practical competencies were limited. Positive attitudes were evident; however, effective ICT adoption was constrained by inadequate resources, limited training, unstable power supply, technical issues, and insufficient administrative support. Factors such as access to reliable internet, training opportunities, peer collaboration, and manageable workloads significantly influenced teachers’ attitudes, whereas personal experience and interest in technology were less impactful. The study concluded that although teachers were willing to integrate ICT into teaching, structural and institutional barriers hindered its effective utilization. To enhance ICT adoption, the study recommends continuous professional development, improved infrastructure and technical support, formal curriculum integration of ICT, and supportive policies with incentives for teachers.
Keywords: Educational Technology, ICT challenges, ICT integration, Students, Teachers’ attitudes
Enhancing Student Engagement through AI-Driven Adaptive Learning and Gamification (Published)
This paper introduces the design, creation, and evaluation of a new adaptive learning system featuring virtual intelligence, fully integrated with game-motivation elements and real-time difficulty-level control to improve learners’ engagement and educational outcomes. The prototype includes a workaround combination of a Python backend based on Flask to dynamically fetch from the questions in the quiz data generator, and subsequently track the performance alongside a frontend of Unreal Engine 5.4 which provides an immersive 2D quiz interface. Content is derived from the OpenTDB API while the VaRest plugin allows easy data communication between backend and frontend. A rule-based threshold algorithm is used to personalize the difficulty of questions in real time based on learner performance. Evaluation results indicate that the system does a good job in matching the difficulty of the questions and proficiency of the user, with an average API response time of 190 ms well above standard benchmarks and increases user engagement in comparison to a conventional static quiz system. The work presented in this study contributes to the field because: (1) it introduces a new framework with innovative technical solutions that combines the technology of game engines with mechanisms of adaptive AI learning; (2) it provides proof of concept that personalization of learning in real time with interpretable rule-based algorithms is feasible; and (3) it lays down practical principles of design that can be used to create intuitive and gamified educational interfaces. While limited in terms of scale of user testing and the lack of more depth around machine learning integration, the research has left behind a foundation for adding more depth to adaptable learning platforms in the future. It features the value of low-latency architecture, the overlooked educational value of Unreal Engine, and the benefits of clear adaptation to improve the digital learning experience.
Keywords: Educational Technology, Gamification, adaptive learning, ai in education, unreal engine