Diagnosing Structure of Observed Learning Outcomes in Measurement and Geometry for Gifted Students of 7th Grade through Machine Learning Platform, Khon Kaen Wittayayon School, Thailand

The objective of this research was to evaluate the dimension of mathematical conceptual structure of gifted students in science and mathematics using the structure of observed learning outcomes concept through the analysis by machine learning platform. The sample consisted of 31 7th grade students from Khon Kaen Wittayayon School. The instrument used was an open-ended situational test developed based on the construct model. The students' responses were analyzed using machine learning platform with the decision tree method. The research found that most students (38.71%) were at the advanced level 5, able to solve problems and create abstract conceptual thinking. The next highest portion (22.58%) were at the basic level 4, able to interpret mathematical symbols and perform basic operations. However, some students still lacked fundamental mathematics which were unable to construct concepts and answer open-ended questions. The structure of observed learning outcomes assessment through machine learning platform was able to demonstrate students' ability levels both overall and individually, revealing the true picture of learning in order to further promote the potential of gifted learners.