The innovation of teaching and learning methodologies in STEM (Science, Technology, Engineering, and Mathematics) is a priority for educational systems globally. It represents a fundamental challenge in schools to improve teaching effectiveness and the acquisition of technical, creative, digital, communication, collaboration, problem-solving, flexibility, adaptability, and critical thinking skills. Furthermore, the Ministry of Education aims to promote the establishment of laboratory spaces and the provision of suitable digital tools to support curriculum learning and the teaching of STEM subjects. The use of AI in STEM education opens new possibilities for engaging and interactive learning, fostering curiosity and exploration, and preparing students for the challenges of the digital age. This article presents a didactic approach to common problems in analytical chemistry, but also suitable for all STEM disciplines, which utilizes the foundations of the Python programming language to develop algorithms for solving various chemistry-related problems, including stoichiometry and analytical chemistry. Moreover, this educational program, divided into multiple modules, consists of laboratory sessions conducted in a computer or multimedia classroom. During these sessions, students will learn how to set up calculations and begin programming while gradually familiarizing themselves with the Python program’s commands and syntax. Among the codes developed so far by a group of students from ITIS Cannizzaro in Colleferro (Rome), there are a unit converter, a tool for calculating the pH of weak and strong acids and bases, a tool for calculating titration curves, and others currently under development such as Webapps. The utilization of AI in this approach brings numerous benefits, including personalized learning, adaptive feedback, data analysis for optimization, real-time assistance, and fostering curiosity and digital preparedness.
Imparare la chimica analitica con il coding in Python / Campagna, Jacopo; Merola, Giovanni; Celletti, Samuele; Maglia, Michele. - In: CNS LA CHIMICA NELLA SCUOLA. - ISSN 0392-8942. - 4:4(2023), pp. 49-81.
Imparare la chimica analitica con il coding in Python
Merola Giovanni
Primo
;
2023
Abstract
The innovation of teaching and learning methodologies in STEM (Science, Technology, Engineering, and Mathematics) is a priority for educational systems globally. It represents a fundamental challenge in schools to improve teaching effectiveness and the acquisition of technical, creative, digital, communication, collaboration, problem-solving, flexibility, adaptability, and critical thinking skills. Furthermore, the Ministry of Education aims to promote the establishment of laboratory spaces and the provision of suitable digital tools to support curriculum learning and the teaching of STEM subjects. The use of AI in STEM education opens new possibilities for engaging and interactive learning, fostering curiosity and exploration, and preparing students for the challenges of the digital age. This article presents a didactic approach to common problems in analytical chemistry, but also suitable for all STEM disciplines, which utilizes the foundations of the Python programming language to develop algorithms for solving various chemistry-related problems, including stoichiometry and analytical chemistry. Moreover, this educational program, divided into multiple modules, consists of laboratory sessions conducted in a computer or multimedia classroom. During these sessions, students will learn how to set up calculations and begin programming while gradually familiarizing themselves with the Python program’s commands and syntax. Among the codes developed so far by a group of students from ITIS Cannizzaro in Colleferro (Rome), there are a unit converter, a tool for calculating the pH of weak and strong acids and bases, a tool for calculating titration curves, and others currently under development such as Webapps. The utilization of AI in this approach brings numerous benefits, including personalized learning, adaptive feedback, data analysis for optimization, real-time assistance, and fostering curiosity and digital preparedness.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.