Impact of Artificial Intelligence Tools on Sentiment, Language Use and Cultural Interpretation among Secondary School Science Students in Makurdi, Benue State, Nigeria
Abstract
This research investigated the impact of AI-mediated online science education discourse on students' sentiment, language use, and cultural interpretation in Makurdi Local Government Area of Benue State using a descriptive survey design. Three research questions and three hypotheses guided the study. The population of the study consisted of 1,840 senior secondary science students in the study area. The sample comprised of 134 male students and 116 female students totaling 250 students drawn through stratified random sampling technique. A structured five-point scale questionnaire titled AI-Mediated Discourse Impact Questionnaire (AMDIQ) which yielded a reliability coefficient of 0.88 through Cronbach's alpha, was used to collect data from respondents. Data obtained were analyzed using mean and standard deviation to answer the research questions while chi-square test was used to test the hypotheses at 0.05 level of significance. The findings revealed that AI-mediated online science education discourse significantly impacted students' sentiment, significantly influenced students' language use patterns in science education, and significantly affected students' cultural interpretation of scientific concepts. It was recommended among others that science educators should integrate AI-mediated discourse platforms that are culturally sensitive and promote positive sentiment in online learning environments. Educational technology developers should design AI systems that recognize and accommodate diverse linguistic patterns and cultural contexts in science education. The Ministry of Education should establish guidelines for implementing AI-mediated discourse tools that enhance rather than compromise students' cultural identity and scientific understanding.
Fields of Study & Subjects
Artificial Intelligence in Education
Sentiment Analysis and Opinion Mining
Intelligent Tutoring Systems and Adaptive Learning
Publication details
- Journal / source
- Federal University Gusau Faculty of Education Journal
- Volume
- 6
- Issue
- 2
- Pages
- 115–122
- Publication date
- 4 March 2026
- Language
- EN