Exploring Students’ Perceptions of AI-Assisted Learning and Its Role in Developing Procedural Understanding of Mathematics in Secondary Schools
DOI:
https://doi.org/10.58197/bxsxe770Keywords:
Artificial Intelligence, Students’ Perceptions, Procedural Understanding, Mathematics EducationAbstract
This study explored students’ perceptions of AI-assisted learning and its perceived role in supporting procedural understanding of mathematics in secondary schools. The study was guided by two objectives: to explore students’ perceptions of using AI-assisted learning in mathematics classrooms and to examine how students perceived its role in supporting procedural understanding. A qualitative research approach guided by an interpretivist paradigm was employed, using a qualitative case study design. Twelve Senior Two (S2) students (the second year of lower secondary education in Rwanda) were purposively selected from a single secondary school and participated in semi-structured interviews. The interview data were analyzed using narrative and thematic analysis, with frequencies and percentages used descriptively to indicate commonly expressed ideas within this small sample. The findings showed that students generally perceived AI-assisted learning positively. Nine students (75%) reported that AI helped them obtain mathematical explanations, while eight (66.7%) valued its convenience and accessibility. However, five students (41.7%) expressed concerns about overdependence on AI, and six (50%) emphasized the importance of teacher guidance. Regarding procedural understanding, ten students (83.3%) perceived AI as useful for providing step-by-step explanations, eight (66.7%) valued additional examples and practice opportunities, and seven (58.3%) reported that AI supported error identification and increased confidence in carrying out mathematical procedures. Within the limits of a small, single-school case, the study suggests that students perceived AI as a supplementary resource for mathematics learning, particularly for step-by-step procedural support, while also expressing concerns about overdependence, accuracy, the continuing need for teachers, and unequal access to devices and connectivity. Because these are perceptions rather than measured learning outcomes, the study offers methodological and theoretical directions for further research instead of practical prescriptions. The study contributes context-specific evidence to the emerging literature on AI-assisted mathematics education in Rwanda.
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