This work introduces an innovative approach to teaching statistical inference, leveraging generative AI tools and computational simulations to enhance the understanding of critical topics. The intervention followed three structured phases. In the first phase, generative AI tools (e.g., ChatGPT) were used to explore theoretical and practical aspects of statistical inference, complemented by computational simulations to deepen understanding and compare results with AI-generated insights. The second phase involved classroom discussions to address conceptual questions and reinforce learning with additional exercises. In the final phase, quizzes were administered to assess mastery of the studied concepts.

The research adopts an experimental design with two groups: a control group receiving traditional instruction and an experimental group engaging in AI-driven interactive simulations. The instructional framework for the experimental group adhered to the ACE cycle (Exploratory Activity, Classroom Instruction, Exercises) and was grounded in the APOS theoretical model (Actions, Processes, Objects, Schemas). Activities focused on confidence intervals and hypothesis testing for differences in means, proportions, and variance ratios, as well as hypothesis testing for attribute independence using contingency tables. The impact of these instructional methods was evaluated through pre- and post-tests measuring conceptual understanding and algorithmic skills. Student activities were assessed using purpose-built rubrics, and the overall classroom environment was evaluated via a climate survey.

Results demonstrate significant improvements in the experimental group’s conceptual understanding and problem-solving abilities. Students engaging with AI-driven simulations exhibited a deeper grasp of confidence intervals, hypothesis tests, and the independence of attributes. These findings highlight the potential of integrating generative AI tools and pedagogical frameworks, offering broader implications for transforming teaching and learning practices in statistics and related disciplines.

Keywords: Higher education, Tec21 model, IA Technology, Inference Statistics.