Teacher Trainees’ Perspectives on Utilizing Artificial Intelligence for Plant Identification at a University in the Eastern Cape Province, South Africa - Vuyokazi Momoti; Nozuko Nqabeni; Yolisa Christina Majija (Journal of Education and Learning Technology)
This study explored teacher trainees’ perceptions of using artificial intelligence (AI) for plant identification. Utilizing a constructivist research paradigm and a case study approach, data was collected from Botany teacher trainees through purposeful sampling. The research employed a quantitative method, where participants were asked to install the Plantnet Application on their smartphones to identify various plants for their herbarium project. Out of 100 randomly selected students who received questionnaires with a 5-point Likert scale, 67 completed and returned them. Data analysis was conducted using SPSS software, focusing on descriptive statistics. The results show that satisfaction with AI usage has positively influenced students’ attitudes towards scientific plant name knowledge. AI demonstrates the potential to enhance learning methods and develop e-learning platforms tailored to users’ needs. The researchers recommend this identification method for its time efficiency and high reliability. Additionally, the Plantnet AI improves the accuracy of scientific names for different species. Ongoing professional development is crucial for in-service science teachers to stay updated with evolving AI technologies and instructional methods. Integrating AI into practical Life Sciences work, including Botany and Zoology, can provide students with comprehensive knowledge of plants and animals while significantly reducing the time needed for traditional species identification. This interdisciplinary approach promotes the development and application of AI technologies in plant identification. Curriculum designers should promote customized online and onsite training focusing on AI integration within science education for inservice teachers. This proactive approach ensures that pre-service teachers enter an environment where AI is already integrated when they become in-service.