Enhancing Gifted Identification: A Machine Learning Analysis of the HOPE Teacher Rating Scale Responses

Journal of Advanced Academics, Ahead of Print.
This study explores machine learning (ML) approaches for identifying gifted students by integrating academic and socioemotional characteristics from the data collected with the Having Opportunities Promotes Excellence teacher rating scale. By using the …

​Journal of Advanced Academics, Ahead of Print. <br/>This study explores machine learning (ML) approaches for identifying gifted students by integrating academic and socioemotional characteristics from the data collected with the Having Opportunities Promotes Excellence teacher rating scale. By using the … Read More

Related posts:

Adaptive Learning to Maximize Gifted Education: Teacher Perceptions, Practices, and Experiences Augmenting Gifted Education Through Artificial Intelligence: A Four-Dimensional Framework for AI Tutoring Integration Beyond Content: An Exploration of Teachers’ Practices for Supporting Academically Advanced Students in Elective High School Classrooms Students’ Perceptions of Mathematics Teachers’ Implementation of Problem-Based Learning Practices in Tanzania Teachers’ Perceptions of Young Gifted Children in China Generative Artificial Intelligence’s Integration for Data Analysis in Conducting Academic Research: Understanding the Perspective of Research Supervisors