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Levy, Ben; Hershkovitz, Arnon; Tabach, Michal; Cohen, Anat; Segal, Avi; Gal, Kobi – IEEE Transactions on Learning Technologies, 2023
This report describes a randomized controlled study that compared the personalization of educational content based on neural networks to personalization by human experts. The study was conducted in a graphically rich online learning environment for elementary school mathematics, in which N = 135 fourth- and sixth-grade students learn via…
Descriptors: Online Courses, Elementary School Students, Grade 4, Grade 6
Pedagogical Framework for Cultivating Children's Data Agency and Creative Abilities in the Age of AI
Juho Kahila; Henriikka Vartiainen; Matti Tedre; Eetu Arkko; Anssi Lin; Nicolas Pope; Ilkka Jormanainen; Teemu Valtonen – Informatics in Education, 2024
The integration of artificial intelligence (AI) topics into K-12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and…
Descriptors: Personal Autonomy, Data, Children, Creativity
Rose E. Wang; Ana T. Ribeiro; Carly D. Robinson; Susanna Loeb; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2024
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Tutors, Elementary School Students
L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
Mat Roni, Saiyidi; Merga, Margaret Kristin – Australian Journal of Education, 2019
Children's attitudes towards, and frequency of recreational reading influence their reading skill level. The aim of this study was to determine the relative influence of research-supported intrinsic and extrinsic variables that can shape this attitude and practice, and to investigate the use of artificial neural network as an adjunct approach in…
Descriptors: Children, Elementary School Students, Grade 4, Grade 6