Abstract
This paper delves into the role of artificial intelligence (AI) in assessing early math skills, showcasing how AI technology is reshaping educational assessment practices. AI provides dynamic tools for individualized learning experiences, offering real-time feedback and adaptive assessments that uncover learning gaps more precisely than traditional methods. We will explore how AI-powered assessments assist educators by providing detailed insights into student progress, pinpointing areas for targeted intervention, and enhancing the development of foundational math competencies in young learners. Additionally, we present case studies and real-world examples that demonstrate how AI is currently being utilized in early math education, emphasizing its capacity to revolutionize the evaluation and support of early mathematical learning. By integrating AI, we can create more responsive, data-driven approaches that foster both student engagement and academic growth in early childhood education. The study offers a forward-looking perspective on how AI could shape the future of math assessments, helping to better address individual learning needs and improve educational outcomes.
Presenters
Jose I. Navarro GuzmanProfessor, Psychology, University of Cádiz, Cádiz, Spain Manuel Aguilar Villagran
University of Cádiz Gonzalo Ruiz Cagigas
University of Cádiz
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Considering Digital Pedagogies
KEYWORDS
AI, Early Math Skills, Adaptive Assessments, Personalized Learning
