Ivon M. Arroyo MS Ed D
In her interdisciplinary role, she has carried has carried out top research at the forefront of education, computer science and psychology, co-authoring about 50 research articles at the forefront of the three disciplines.
From the EDUCATION perspective, she has researched and created learning software for mathematics with multimedia, and worked closely with thousands of K-12 students and teachers, deployed software in public schools, while trying understand how students best learn and perceive mathematics with interactive math tutoring software, and how to support teachers in their teaching process via digital assessment tools.
From the COMPUTER SCIENCE perspective, she has created artificially intelligent tutoring software that models students knowledge and affective states, infers them from student behaviors and physiological sensors, and which acts upon those students states, as students use the software. She has used data mining methods to learn a variety of student states from past student data logs.
From the PSYCHOLOGY perspective, she has analyzed developmental gender differences in the use and benefit of math tutoring software, cognitive development issues in relation to the best representations to use while teaching mathematics, and memory retrieval studies where the training of speed of retrieval of basic math facts help students increase working memory capacity and succeed in complex math tasks. Ivon Arroyo is a PI or co-PI for NSF and Department of Education research grants that attempt to find principles for the design of digital learning environments for STEM that enhance affective and cognitive outcomes, with an emphasis on girls and students with learning disabilities. She holds a doctorate in Math and Science Education and a Masters and BS in Computer Science.
She is a Fulbright Fellow, and an elected member of the executive committee of the International Society of Artificial Intelligence in Education. Dr. Arroyo has led or actively participated in several research projects: i) Learning to Teach --using machine learning techniques to predict student learning and attitudes; ii) Customizing Resources for NSDL --customizing mathematics material within a digital library (MathForum) to individual students; iii) Wayang Outpost/AnimalWorld --enhancing high school women’s mathematical competence with a tutoring System for Standardized Tests; iv) AnimalWatch – enhancing young girls’ math competence and attitudes towards mathematics and computers; v) “What kind of Math Software Works for Girls?” –unveiling features of educational software that make it effective for girls; vi) Modeling and supporting emotion while learning with tutoring systems; and vii) Teaching Every Student: Using Intelligent Tutoring and Universal Design to Customize the Mathematics Curriculum” –customizing digital educational technologies to students with learning disabilities.