BLENDED PEDAGOGY OF ARTIFICIAL INTELLIGENCE - HUMAN INSTRUCTIONAL INTEGRATION: EFFECT ON ACADEMIC ACHIEVEMENT AND MOTIVATION OF UNDERGRADUATE PHYSICS STUDENTS

Abstract

This study examines the effectiveness of blended pedagogy - an instructional approach that integrates human teaching with Artificial Intelligence (AI) tutoring tools, on students’ academic achievement and motivation in undergraduate Physics and Chemistry classrooms. A quasi experimental research design was adopted, with a study sample of 135 undergraduate science students, treated both as control groups (Physics control group, n = 66 and Chemistry control group, n = 69) and experimental groups (Physics experimental group, n = 66 and Chemistry experimental group, n = 69). The control groups were taught using the conventional teacher-led instruction, while the experimental groups were taught using the blended pedagogy. Data were collected using Science Achievement Test and Science Learning Motivation Scale which have reliability coefficients of 0.88 and 0.91 obtained using Kuder-Richardson and Cronbach’s alpha, respectively. Collected data were analyzed using descriptive and inferential statistics at 0.05 significance level. Results showed significant differences in mean scores between the experimental and the control group (Experimental: MS = 34.21, SD = 5.02; Control: MS = 26.83, SD = 6.18; t(130) = 7.53, p < 0.001). Similarly, students in the experimental group reported significantly higher motivation levels (n = 135, MS = 3.78, SD = 0.51) compared to the control group (n = 135, MS = 2.87, SD = 0.62), t(268) = 13.17, p < 0.001. These results indicate a positive effect of blended pedagogy on students’ academic achievement and motivation. It is therefore recommended that school authorities should organize training workshops for science lecturers on AI tools for teaching-learning and support them with necessary needed facilities.