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Jinsook Lee; Yann Hicke; Renzhe Yu; Christopher Brooks; René F. Kizilcec – British Journal of Educational Technology, 2024
Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…
Descriptors: Artificial Intelligence, Technology Uses in Education, Equal Education, Algorithms
Kalervo N. Gulson; Sam Sellar – Journal of Education Policy, 2024
The growing use of artificial intelligence in education extends and intensifies technologies of governing, including datafication, performativity and accountability. In this article, we outline how the use of AI and data science has the disruptive potential to create new norms in education policy and governance. We report on an ethnographic…
Descriptors: Artificial Intelligence, Educational Policy, Governance, Evidence
Karlis Kanders; Louis Stupple-Harris; Laurie Smith; Jenny Louise Gibson – Infant and Child Development, 2024
Generative artificial intelligence (GAI) is rapidly becoming ubiquitous in many contexts. There is limited scholarship, however, in the fields of Developmental Psychology and Early Childhood Education exploring the implications of generative AI for babies and young children. In this Perspectives piece, we discuss potential use cases,…
Descriptors: Artificial Intelligence, Early Childhood Education, Child Development, Infants
Richard Raymond Freda – ProQuest LLC, 2024
Despite studies showing that individuals with higher levels of emotional intelligence report higher job satisfaction and happiness, relatively few studies have looked at the relationship between higher levels of emotional intelligence and lower levels of teacher burnout, especially among music teachers. With so many music teaching positions going…
Descriptors: Correlation, Emotional Intelligence, Teacher Burnout, Music Teachers
Yang Shi; Tiffany Barnes; Min Chi; Thomas Price – International Educational Data Mining Society, 2024
Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…
Descriptors: Algorithms, Artificial Intelligence, Models, Programming
Muhammad Fawad Akbar Khan; Max Ramsdell; Erik Falor; Hamid Karimi – International Educational Data Mining Society, 2024
This paper undertakes a thorough evaluation of ChatGPT's code generation capabilities, contrasting them with those of human programmers from both educational and software engineering standpoints. The emphasis is placed on elucidating its importance in these intertwined domains. To facilitate a robust analysis, we curated a novel dataset comprising…
Descriptors: Artificial Intelligence, Automation, Computer Science Education, Programming
Meng Cao; Philip I. Pavlik Jr.; Wei Chu; Liang Zhang – International Educational Data Mining Society, 2024
In category learning, a growing body of literature has increasingly focused on exploring the impacts of interleaving in contrast to blocking. The sequential attention hypothesis posits that interleaving draws attention to the differences between categories while blocking directs attention toward similarities within categories [4, 5]. Although a…
Descriptors: Attention, Algorithms, Artificial Intelligence, Classification
Józsa, Krisztián; Amukune, Stephen; Zentai, Gabriella; Barrett, Karen Caplovitz – Journal of Intelligence, 2022
Research has shown that the development of cognitive and social skills in preschool predicts school readiness in kindergarten. However, most longitudinal studies are short-term, tracking children's development only through the early elementary school years. This study aims to investigate the long-term impact of preschool predictors, intelligence,…
Descriptors: Foreign Countries, School Readiness, Intelligence Tests, Preschool Children
Cruz, Sara; Cruz, Raquel; Alcón, Alicia; Sampaio, Adriana; Merchan-Naranjo, Jessica; Rodríguez, Elisa; Parellada, Mara; Carracedo, Ángel; Fernández-Prieto, Montse – Journal of Cognition and Development, 2022
Dysexecutive syndrome has been consistently reported in children and adolescents with autism spectrum disorders (ASD). Particularly, impairments have been documented in working memory, inhibition, and mental flexibility. However, the relationship between executive impairments and intellectual functioning is far from clear in this population. This…
Descriptors: Executive Function, Intelligence, Children, Adolescents
Acosta-Prado, Julio César; Zárate-Torres, Rodrigo Arturo; Tafur-Mendoza, Arnold Alejandro – Journal of Intelligence, 2022
Within the organizational field, emotional intelligence is linked to socially competent behaviors, which allow the development of labor and organizational abilities necessary for professional development. Thus, in workers, emotional intelligence is related to a wide range of organizational variables. The purpose of the present study was to…
Descriptors: Psychometrics, Emotional Intelligence, Intelligence Tests, Test Reliability
Jamal Eddine Rafiq; Abdelali Zakrani; Mohammed Amraouy; Said Nouh; Abdellah Bennane – Turkish Online Journal of Distance Education, 2025
The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…
Descriptors: Models, Online Courses, Educational Improvement, Learning Processes
Ercikan, Kadriye; McCaffrey, Daniel F. – Journal of Educational Measurement, 2022
Artificial-intelligence-based automated scoring is often an afterthought and is considered after assessments have been developed, resulting in nonoptimal possibility of implementing automated scoring solutions. In this article, we provide a review of Artificial intelligence (AI)-based methodologies for scoring in educational assessments. We then…
Descriptors: Artificial Intelligence, Automation, Scores, Educational Assessment
Noah L. Schroeder; Robert O. Davis; Eunbyul Yang – Journal of Educational Computing Research, 2025
Pedagogical agents are virtual characters that instructional designers include in learning environments to help students learn. Research in the area has flourished for thirty years, yet there are still critical questions about the efficacy of pedagogical agents for influencing learning and affect. As such, we conducted an umbrella review to…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Intelligent Tutoring Systems
Fatih Karatas; Bengü Aksu Ataç – Education and Information Technologies, 2025
The integration of AI into TPACK frameworks is crucial for enhancing teacher readiness in an increasingly technology-driven educational environment. However, a significant gap exists in literature regarding assessing preservice teachers' knowledge on the integration of AI into their pedagogical practices based on the TPACK framework. This study…
Descriptors: Pedagogical Content Knowledge, Technological Literacy, Artificial Intelligence, Preservice Teachers
Tinaye Des Kamukapa; Stellah Lubinga; Tyanai Masiya; Lerato Sono – Teaching Public Administration, 2025
There is an increasing call to include Artificial Intelligence (AI) competencies in academic disciplines such as Public Administration, which are not obviously related to Science, Technology, Engineering and Mathematics (STEM). However, the literature on the integration of AI in non-STEM curricula in South African higher education institutions…
Descriptors: Artificial Intelligence, Public Administration Education, College Curriculum, Undergraduate Study

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