Saudi High School Mathematics Teachers’ Perceptions of Implementing Differentiated Instruction (DI) and Artificial Intelligence (AI) in Teaching Mathematics

Abstract

The rapid growth of education under Saudi Vision 2030 has emphasized the urgent need for modern teaching methods in mathematics, including addressing individual students’ learning needs and leveraging artificial intelligence to provide enriched educational opportunities and experiences. The study’s primary goal is to provide comprehensive insight into the current perceptions of high school mathematics teachers on three main research questions: implementing DI, implementing Tomlinson’s four-part DI framework, and AI as a teaching tool in their classrooms in Saudi Arabia. A quantitative research design was employed, utilizing a survey instrument, to examine the level of application of DI and the Tomlinson DI framework, usage and proficiency with AI as a teaching tool, as well as gender differences and predictive relationships among these categories. The instrument measured mathematics teachers’ knowledge, beliefs, behavior, and concerns regarding DI; perceptions of Tomlinson’s DI framework (content, process, product, and learning environment); and perceptions of AI as a teaching tool (readiness, perceived usefulness, behavioral intention, participation in professional development, and knowledge). The results show that high school mathematics teachers perceive themselves to have a high level of implementation of differentiated instruction and of differentiating content, process, product, and learning environment. A significant difference between genders was found in only the product category. Additionally, after controlling for demographic factors (gender, years of experience, qualification), both teachers’ knowledge and beliefs made significant contributions to predicting their behavior regarding DI, while their concerns were not significant. Content and process differentiation revealed no significant predictors, while product differentiation had a significant influence on learning environment differentiation. Mathematics teachers’ perceptions of readiness and perceived usefulness of leveraging AI as predictor variables demonstrated a statistically significant influence on their behavioral intention to implement AI (R² change = .525, F change observed (2, 115) = 70.720, p < .001). This research contributes to the growing body of studies related to AI and DI by offering insights specific to the Saudi mathematics context, providing recommendations for professional development programs, curriculum design, and policymakers aimed at reforming mathematics teaching in high school to achieve Saudi Vision 2030 goals.