Analysis of the Necessity of AI Utilization and Digital Competencies and Use Cases for Science Teachers

Abstract

This exploratory qualitative study aimed to investigate the specific practices and the necessity of cultivating AI utilization capabilities and digital competencies among science teachers. The research involved interviews and focus group interviews with nine science teachers in secondary schools who incorporated AI and digital tools in their science classes. This study revealed that science teachers' need for AI literacy and digital competence can be categorized into the following key motivations: personal curiosity, a sense of fulfillment as educators, a passion for enhancing student engagement in lessons, and the evaluation of students' evolving competencies from a trans-disciplinary perspective. Furthermore, the study identified several implementation measures, including the utilization of AI tools for visualization, comprehension of AI tool principles at an accessible level, employment of computer languages for statistical data processing and visualization, adoption of platforms for identifying information sources and sharing information, utilization of diverse sensors while assessing their advantages and disadvantages, and the design of interdisciplinary science inquiry lessons that leverage the capabilities of AI tools and digital resources. The outcomes of this research contribute to enhancing the practicality of new scientific investigations and offer insights for formulating policy guidelines to foster science teachers' proficiency in AI utilization and digital competencies.