ARTIFICIAL INTELLIGENCE AND INSTRUCTIONAL PURPOSES: ENHANCING SENIOR SCHOOL STUDENTS’ PRACTICAL PHYSICS LEARNING OUTCOMES USING AI-DRIVEN MOTION GRAPHICS TECHNIQUE IN ILORIN, NIGERIA

Abstract

The study determined the use of AI-driven motion graphics technique on students’ performance on projectile motion in Ilorin, in the 2024/2025 academic session. Population of the study include all senior school students in Ilorin, Kwara State The target population comprised only senior school II (SSII) students in public secondary schools in Ilorin South. A multistage sampling technique was adopted for the study. In the first stage, an intact class of 80 SSII students (36 males and 44 females) was randomly sampled from two different public single sex schools. The schools were then grouped into experimental and control groups based on gender, as male and female students respectively. The schools were purposively selected based on gender. The experimental group received instruction with motion graphics aided with Knewton as AI for adaptive learning platform and Reelminda.ai for visuals. The control group received instructions using conventional method. Data were collected through pre-tests, post-tests, engagement questionnaires, and retention assessments guide. Data were analysed using descriptive statistics of mean and standard deviation. T-tests was used for hypotheses tested at the 0.05 level of significance. Findings from the study revealed significant improvement in students’ academic performance, engagement, and retention when exposed to AI-driven motion graphics instructions. The study concluded that motion graphics effectively enhanced practical Physics learning when integrated with AI tools and recommends its integration into other Physics instructions at different levels for sustainable educational development.