Effects of Artificial Intelligence (AI)-Powered Personalized Learning Platforms On Students' Academic Interest and Achievement.

Abstracts This study investigated the effect of AI-powered personalized learning platform on students interest and achievement in physics(electromagnetism) among secondary schools in Ogbia Local Government Area of Bayelsa state. This goal compares students academic performance in AI-powered personalized learning platform to that of students in conventional learning platform. Three research questions guided the study while three null hypotheses were tested at 0.05 level of significance. Quasi experimental research design was adopted for the study. The population of the study comprised 1564 senior secondary school (II) physics students. A sample size of 87 students were used for the study. Sample was gotten from two schools selected using simple random sampling from the population. One school serves as the experimental group while the other as the control group. The instrument for data collection were Physics Achievement Test(PAT), Reasoning Ability Test (RAT) and Physics Interest Inventory(SII), which was developed by the researcher and validated by two experts in physics education and measurement and evaluation experts. Kuder-Richardson 20 (K-20) formula was used to estimate the reliability of the instrument and a reliability index o f 0.74 and 0.73 were obtained for PAT and RAT. Mean and standard deviation were used for answering the research questions while Analysis of Covariance (ANCOVA) was used to test for the null hypotheses. The null hypothesis was rejected if probability value is less than the significant value of 0.05 (P<0.05) and if otherwise (P>0.05), it was not rejected. The findings of the study showed among others that physics student taught electromagnetism using AI-powered personalized learning platform had improved academic achievement more than those taught using conventional method. In line with the findings, the researcher recommended among others that schools should adopt the use of AI-powered personalized learning platform for teaching and learning physics (electromagnetism), to enhance students’ academic achievement.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-01
DOI
https://doi.org/10.5281/zenodo.17237430
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
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article

Effects of Artificial Intelligence (AI)-Powered Personalized Learning Platforms On Students' Academic Interest and Achievement.

Zenodo (CERN European Organization for Nuclear Research)
Diverse Scientific and Economic Studies
article

Effects of Artificial Intelligence (AI)-Powered Personalized Learning Platforms On Students' Academic Interest and Achievement.

article en

Abstract

Abstracts This study investigated the effect of AI-powered personalized learning platform on students interest and achievement in physics(electromagnetism) among secondary schools in Ogbia Local Government Area of Bayelsa state. This goal compares students academic performance in AI-powered personalized learning platform to that of students in conventional learning platform. Three research questions guided the study while three null hypotheses were tested at 0.05 level of significance. Quasi experimental research design was adopted for the study. The population of the study comprised 1564 senior secondary school (II) physics students. A sample size of 87 students were used for the study. Sample was gotten from two schools selected using simple random sampling from the population. One school serves as the experimental group while the other as the control group. The instrument for data collection were Physics Achievement Test(PAT), Reasoning Ability Test (RAT) and Physics Interest Inventory(SII), which was developed by the researcher and validated by two experts in physics education and measurement and evaluation experts. Kuder-Richardson 20 (K-20) formula was used to estimate the reliability of the instrument and a reliability index o f 0.74 and 0.73 were obtained for PAT and RAT. Mean and standard deviation were used for answering the research questions while Analysis of Covariance (ANCOVA) was used to test for the null hypotheses. The null hypothesis was rejected if probability value is less than the significant value of 0.05 (P<0.05) and if otherwise (P>0.05), it was not rejected. The findings of the study showed among others that physics student taught electromagnetism using AI-powered personalized learning platform had improved academic achievement more than those taught using conventional method. In line with the findings, the researcher recommended among others that schools should adopt the use of AI-powered personalized learning platform for teaching and learning physics (electromagnetism), to enhance students’ academic achievement.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 34%
Diverse Scientific and Economic Studies
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Effects of Artificial Intelligence (AI)-Powered Personalized Learning Platforms On Students' Academic Interest and Achievement. · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS