EFFECT OF ARTIFICIAL INTELLIGENCE–DRIVEN PERSONALIZED LEARNING ON SECONDARY SCHOOL STUDENTS’ ACHIEVEMENT, RETENTION, AND ATTITUDES TOWARD PHYSICS IN ABAK LOCAL GOVERNMENT AREA, AKWA IBOM STATE, NIGERIA
Keywords:
Artificial Intelligence, Personalized Learning, Physics Education, Achievement, Retention, AttitudeAbstract
This study investigated the effect of Artificial Intelligence–Driven Personalized Learning (AIDPL) on secondary school students’ achievement, retention, and attitudes toward Physics in Abak Local Government Area of Akwa Ibom State, Nigeria. A quasi-experimental pretest–posttest non-equivalent control group design was adopted. The population comprised all Senior Secondary School II (SS II) Physics students in public secondary schools in Abak. A sample of 120 students drawn from two intact classes was used for the study. One class served as the experimental group and was taught using AI-driven personalized learning, while the control group was taught using the conventional lecture method. Three instruments were used for data collection: Physics Achievement Test (PAT), Physics Retention Test (PRT), and Students’ Attitude toward Physics Questionnaire (SAPQ). The instruments were validated by experts and their reliability indices ranged from 0.78 to 0.86. Mean and standard deviation were used to answer the research questions, while Analysis of Covariance (ANCOVA) was used to test the hypotheses at 0.05 level of significance. The findings revealed that students exposed to AI-driven personalized learning performed significantly better in achievement and retention and demonstrated more positive attitudes toward Physics than those taught using the conventional method. The study concludes that AI-driven personalized learning enhances students’ learning outcomes in Physics and recommends its integration into secondary school Physics instruction.
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