Effect of AI-assisted microscope for plant anatomy learning to enhance students’ logical–mathematical intelligence

ABSTRACT

Guided by the PISA framework, logical–mathematical intelligence is recognized as a key competence in situational problem solving. In plant anatomy practicum, applying logical–mathematical reasoning to analyze observational data is essential for drawing accurate conclusions about cells and tissues. However, preliminary observations in SMAN 1 and SMAN 2 Indramayu indicated that students’ logical–mathematical intelligence was still relatively low. To address this, a Smart AI Microscope was developed to provide automated object recognition, measurement, and calibration features that support more accurate observations. This study aimed to develop a Smart AI Microscope for plant anatomy learning to enhance students’ logical–mathematical intelligence. The research employed the ADDIE development model, consisting of analysis, design, development, implementation, and evaluation stages. The study was conducted over one year, focusing on the design and application of the Smart AI microscope in plant anatomy practicums. The results showed that the system achieved a “very valid” category based on expert validation by three instructional media specialists. Furthermore, the implementation of the Smart AI microscope in practicum activities was found to be sufficiently effective in improving students’ logical–mathematical intelligence. It can be concluded that the Smart AI microscope is a valid and effective learning innovation, with implications for improving analytical skills and supporting technology-integrated biology practicums.