Effect of AI-Enhanced Personalized Instruction on Pre- Service Teacher’s Problem- Solving Skills in Biology in Alvan Ikoku Federal University of Education Owerri Imo State

Catherine I. Evans-Kemka; Abel Idoko Onoja; MaryJoan O. Ngumah; Ivy N. Awurum; Queeneth C. Ugoeze; Agaezi V. Azoro

doi:10.56201/wjimt.v10.no4.2026.pg156.162

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Effect of AI-Enhanced Personalized Instruction on Pre- Service Teacher’s Problem- Solving Skills in Biology in Alvan Ikoku Federal University of Education Owerri Imo State

Catherine I. Evans-Kemka, Abel Idoko Onoja, MaryJoan O. Ngumah, Ivy N. Awurum, Queeneth C. Ugoeze, Agaezi V. Azoro

Abstract

The development of problem-solving skills is a central goal of Biology education programmes. Recent advances in Artificial Intelligence (AI) have introduced AI-enhanced personalized instruction as a promising approach for improving learning outcomes. This study investigated the effect of AI-enhanced personalized instruction on pre-service teachers’ problem-solving skills in Biology in Alvan Ikoku Federal University of Education Owerri, Imo State. The study adopted a quasi-experimental pre-test, post-test non-equivalent control group design. The study population comprised 175 pre-service teachers offering Biology education, from which a sample of 86 pre- service teachers were used for the study. The experimental group was taught using AI-enhanced personalized instructional strategy, while the control group received instruction through conventional teaching method. Data were collected using Biology Problem-Solving Skills Test , validated by experts, with reliability of 0.82 established using appropriate test – retest method. Mean and standard deviation were used to answer the research questions, while an independent samples t-test was used to test the hypothesis at 0.05 level of significance. The findings revealed that AI-enhanced personalized instruction significantly improved pre-service teachers’ interpretation of data and application of theoretical knowledge to practical situations. A statistically significant difference was found between the mean problem-solving skills scores of students taught using AI-enhanced personalized instruction and those taught using conventional methods, in favour of the experimental group. The study concludes that AI-enhanced personalized instruction is more effective than conventional teaching method in improving problem-solving skills in Biology. It was therefore recommended that AI-based instructional approaches be integrated into Biology teacher education programmes.

Keywords

Artificial IntelligencePersonalized InstructionProblem-Solving SkillsBiology EducationPre-service Teachers.

References

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Effect of AI-Enhanced Personalized Instruction on Pre- Service Teacher’s Problem- Solving Skills in Biology in Alvan Ikoku Federal University of Education Owerri Imo State

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