Comparative Effects of Generative AI-Assisted and Teacher-Guided Problem-Solving Approaches on Senior Secondary School Students’ Achievement and Problem-Solving Skills in Stoichiometry in Anambra State

Anekwe; Christopher Ejike; Okonkwo Chidiebere Christiana

doi:10.56201/ijccp.vol.12.no7.2026.pg24.36

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Comparative Effects of Generative AI-Assisted and Teacher-Guided Problem-Solving Approaches on Senior Secondary School Students’ Achievement and Problem-Solving Skills in Stoichiometry in Anambra State

Anekwe, Christopher Ejike, Okonkwo Chidiebere Christiana

Abstract

Stoichiometry is a key concept in Chemistry that involves conceptual understanding, quantitative reasoning and sequential problem solving. In secondary school Chemistry, generative artificial intelligence can enable interactive explanations and immediate feedback, but its effectiveness compared with teacher-guided problem-solving needs empirical research. This study examined the comparative effects of GenAI-assisted and teacher-guided problem-solving approaches on students’ achievement and problem-solving skills in stoichiometry in Onitsha and Otuocha education zones, Anambra State. The study population was 5,274 SS2 Chemistry students. A quasi-experimental pretest–posttest, non-equivalent control-group design was used. A sample of 495 SS2 Chemistry students (260 females and 245 males) was selected through multi-stage sampling. Data were collected with the Stoichiometry Achievement Test and the Stoichiometry Problem-Solving Skills Test , which were validated; reliability was 0.84 (KR- 20) for SAT and 0.82 (Cronbach’s alpha) for SPST. Research questions were answered using regression analysis, and hypotheses were tested using regression ANOVA at the 0.05 significance level. Analysis of covariance compared posttest performance while controlling for pretest scores. The GenAI-assisted group obtained an adjusted achievement mean of 54.89, compared with 52.32 for the teacher-guided group, F(1,117) = 4.86, p = .029, partial η2 = .040. For problem-solving skills, the adjusted means were 55.54 and 51.64, F(1,117) = 8.15, p = .005, partial η2 = .065. These illustrative results suggest modest advantages for structured GenAI- assisted problem-solving. The study framework highlights the importance of controlled comparisons, independent assessment, and responsible AI integration in Chemistry Education.

Keywords

Generative AI-AssistedTeacher-GuidedStudents’ AchievementProblem-Solving SkillsStoichiometry. IJCCP

References

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Comparative Effects of Generative AI-Assisted and Teacher-Guided Problem-Solving Approaches on Senior Secondary School Students’ Achievement and Problem-Solving Skills in Stoichiometry in Anambra State

Abstract

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