Innovative Teaching Methods Supported by Artificial Intelligence and Students’ Mathematical Problem-Solving: The Mediating Role of Student Engagement

Abstract

The study investigated how innovative, AI-supported teaching methods relate to the mathematics problem-solving ability of Senior High School (SHS) students in Ghana. This study examined how teachers’ AI-supported pedagogical practices relate to students’ problem-solving ability, the extent to which student engagement serves as an explanatory variable for that relationship, and whether students’ mathematical self-belief (MSB) moderates that relationship. A quantitative cross-sectional design was employed; participants comprised 385 students from both public and private SHS. Data were collected from a structured questionnaire and analysed with structural equation modeling (SEM). The study results show that AI-supported pedagogical practices of teachers significantly enhance both student engagement in mathematics and problem-solving ability. Student engagement partially mediates the relationship between instructional practices and problem-solving ability, underscoring engagement as a critical mechanism through which effective teaching methods shape learning outcomes. MSB has a meaningful direct influence on problem-solving ability, but does not significantly modify the relationship between pedagogical practices and problem-solving ability. The study emphasises the added value of integrating AI-enhanced teaching methods with effective pedagogical principles to enhance instructional effectiveness and students’ higher-order math skills in secondary education.