In the context of mathematics education, the integration of artificial intelligence (AI) in teaching calculus is revolutionizing instructional methodologies and enhancing learning experiences both inside and outside the classroom. This study explores the use of specific AI tools, including ChatGPT, MathGPT, Gemini, and Wolfram Alpha, to deepen students’ understanding of key mathematical concepts such as derivatives and rates of change through continuous interaction with a virtual tutor. By employing well-designed prompts, these tools facilitated problem-solving exercises that were verified and refined by AI, fostering both precision in calculations and conceptual clarity. Observations from the classroom implementation reveal that students not only improved their accuracy in performing derivative calculations but also developed a clear understanding of the distinctions between average and instantaneous rates of change. The AI tools created a dynamic, adaptive learning environment, providing immediate feedback and simulations that significantly boosted student engagement and motivation. These findings underscore the potential of AI to transform mathematics education by making learning more personalized and accessible, ultimately enhancing educational outcomes and preparing students for future academic and professional challenges. Furthermore, this study introduces an innovative approach to refining AI prompts and interactions, highlighting the importance of iterative improvement to enhance the quality of AI feedback. This approach is crucial for developing better problem-solving skills and ensuring a comprehensive understanding of mathematical concepts.

Purpose: This study aims to enhance production quality by applying Quality Control (QC) principles through acceptance sampling, specifically analyzing the efficacy of attribute acceptance sampling plans in final lot receptions.Design/methodology/approach: Through a comprehensive review and critical evaluation of various sampling methodologies found in literature, this paper assesses their efficiency under distinct administrative and operational conditions. It emphasizes the comparison of different attribute acceptance sampling plans by examining variations in parameters and key performance indicators, such as Average Outgoing Quality (AOQ) and inspection time allocation percentage. Furthermore, it proposes a model for Continuous Sampling Plans (CSP) to evaluate these plans' performance in response to operational characteristic variations.Findings: The analysis reveals that the selected methodologies significantly aid in decision-making processes for lot acceptance, utilizing non-conforming rates depicted by the Average Quality Level (AQL). This provides a robust framework for improving Quality Control strategies, demonstrating the potential of these methodologies to optimize production quality through strategic lot acceptance.Practical implications: This paper outlines a practical approach for industry practitioners to enhance decision-making in lot acceptance, offering a method to balance quality control with operational efficiency effectively.Originality/value: By comparing a wide range of attribute acceptance sampling plans and introducing a novel CSP model, this research contributes valuable insights into the optimization of QC strategies. It offers a unique perspective on enhancing production quality, marking a significant advancement in the field of Quality Control and management.

Las TIC han generado nuevas maneras de dirigir el proceso enseñanza-aprendizaje de la Matemática Superior. Sin embargo, a pesar de la socialización del acceso a los recursos informáticos y telemáticos estos no han impactado como se esperaba en los resultados del aprendizaje de los estudiantes que cursan la formación de pregrado en las carreras ingenierías en Cuba. Por tal razón, el objetivo de este trabajo consistió en modelar el proceso de enseñanza-aprendizaje de los conceptos, con la mediación de las TIC, para revelar cualidades que posibiliten su perfeccionamiento. Para desarrollar la investigación se emplearon los métodos de análisis-síntesis, inducción-deducción, la modelación con enfoque de sistema, taller de socialización con especialistas y el criterio de expertos los que permitieron el diseño del modelo y la valoración de su pertinencia y factibilidad.

This qualitative research aimed to characterize the perceptions of engineering students in preparatory courses regarding the STEAM approach and its relationship to mathematics learning at an educational institution in Barranquilla, Atlántico (Colombia). A single-case study design was applied with a purposive sample of eight mechatronics, systems, and electronics engineering students, using semi-structured interviews as the primary data collection technique. The qualitative analysis revealed that the students recognize the STEAM approach as an integrative framework that strengthens mathematical understanding by linking it to other disciplines. Participants identified key benefits such as the development of creative thinking, the contextualized application of mathematical concepts, the strategic use of technological tools, and the promotion of collaborative work. Overall, the findings demonstrate a positive assessment of the STEAM approach as a pedagogical strategy that promotes essential interdisciplinary competencies for 21st-century engineering education.

TASK EVALUATION MODEL USED IN ENVIRONMENTAL OLYMPIADS TO DEVELOP MATHEMATICAL THINKING TASK EVALUATION MODEL USED IN ENVIRONMENTAL OLYMPIADS TO DEVELOP MATHEMATICAL THINKING