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Grant Cooper; Kok-Sing Tang – Journal of Science Education and Technology, 2024
The proliferation of generative artificial intelligence (GenAI) means we are witnessing transformative change in education. While GenAI offers exciting possibilities for personalised learning and innovative teaching methodologies, its potential for reinforcing biases and perpetuating stereotypes poses ethical and pedagogical concerns. This article…
Descriptors: Artificial Intelligence, Science Education, Visual Aids, Stereotypes
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Benjamin Gagl; Klara Gregorová – npj Science of Learning, 2024
Efficient reading is essential for societal participation, so reading proficiency is a central educational goal. Here, we use an individualized diagnostics and training framework to investigate processes in visual word recognition and evaluate its usefulness for detecting training responders. We (i) motivated a training procedure based on the…
Descriptors: Reading, Reading Rate, Language Acquisition, Artificial Intelligence
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Li Chen; Gen Li; Boxuan Ma; Cheng Tang; Masanori Yamada – International Association for Development of the Information Society, 2024
This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge…
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving
Ruth Grube – ProQuest LLC, 2024
The COVID-19 crisis was a global upheaval that significantly impacted the education systems--in the face of this, district and school leadership demonstrated remarkable resilience, overcoming the challenge of educating students through these uncertain times. They drew upon their existing leadership skills while also acquiring new ones they never…
Descriptors: COVID-19, Pandemics, Leadership Styles, Emotional Intelligence
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Eyüp Yurt – International Society for Technology, Education, and Science, 2024
This study addresses the opportunities presented by AI applications in education and the ethical issues brought about by this technology. AI in education holds excellent potential in personalized learning, automated assessment and feedback, and monitoring and analyzing student performance. However, using these technologies also raises ethical…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Ethics
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Beatriz Carbajal-Carrera – Australian Review of Applied Linguistics, 2024
The growing implementation of Generative AI (GenAI) in education has implications on the representation of knowledge and identity across languages. In a context where content biases have been reported in AI-generated content, it becomes relevant to interrogate the ways in which AI technologies represent different linguistic identities. This…
Descriptors: Artificial Intelligence, Sociolinguistics, Language Usage, Bias
Bryant Lopez – ProQuest LLC, 2024
Early in 2020, the United States was faced with the global impact of the COVID-19 pandemic resulting in several school districts across the country shutting down. What began as a temporary school closure morphed into one of the most creative and labor-intensive restructurings of schools. Leading the dramatic changes were elementary school…
Descriptors: COVID-19, Pandemics, School Closing, Principals
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Seth King; Anne Estapa; Tyler Bell; Joseph Boyer – Journal of Behavioral Education, 2024
Researchers increasingly identify virtual reality (VR) simulations as a potentially effective professional development tool. However, simulations used in education and behavior analysis typically require active oversight from technicians and instructors. "Smart" VR integrated with artificial intelligence could independently administer…
Descriptors: Computer Simulation, Skill Development, Behavior Modification, Verbal Communication
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Nicholas Leonard; Johnson Kwame Wor – Art Education, 2024
This article intends to empower and equip art educators to artistically address the functioning of facial detection algorithms through critical race theory (CRT). By highlighting how biometric data, a specific form of data that measures the physical qualities of individuals, is used in common social media facial detection algorithms like Snapchat,…
Descriptors: Art Education, Artificial Intelligence, Racism, Social Media
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Domenico Tullo; Bianca Levy; Jocelyn Faubert; Armando Bertone – Journal of Autism and Developmental Disorders, 2024
The extant literature aimed at characterizing attentional capability in autistics has presented inconsistent findings. This inconsistency and uncertainty may be the product of different theoretical and methodological approaches used to define attention in autism. In the current study, we investigate whether the allocation of attentional resources…
Descriptors: Autism Spectrum Disorders, Attention, Thinking Skills, Capacity Building
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José Luis Rodríguez Illera – Digital Education Review, 2024
The article reviews some of the relationships between AI and education, emphasizing the metaphors used, the difficulties in finding points of agreement, as well as aspects of the social criticism that is made of AI (e.g. considering that it can be a form of unwanted deviation). AI appears as one more case of technology that comes to improve…
Descriptors: Artificial Intelligence, Technology Uses in Education, Thinking Skills, Ethics
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Adronisha T. Frazier – Research Issues in Contemporary Education, 2024
This position paper explores the current state of artificial intelligence (AI) tools, educator support of and opposition to AI tools in teaching and learning, and the ethical and social implications of AI tools in higher education. As technology continuously develops in the educational community, educators must have a voice in how AI exists in the…
Descriptors: Artificial Intelligence, Higher Education, Technology Uses in Education, Inclusion
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Shin-Yu Kim; Inseong Jeon; Seong-Joo Kang – Journal of Chemical Education, 2024
Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…
Descriptors: Chemistry, Science Instruction, Laboratory Experiments, Artificial Intelligence
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Andres Felipe Zambrano; Nidhi Nasiar; Jaclyn Ocumpaugh; Alex Goslen; Jiayi Zhang; Jonathan Rowe; Jordan Esiason; Jessica Vandenberg; Stephen Hutt – International Educational Data Mining Society, 2024
Research into student affect detection has historically relied on ground truth measures of emotion that utilize one of three sources of data: (1) self-report data, (2) classroom observations, or (3) sensor data that is retrospectively labeled. Although a few studies have compared sensor- and observation-based approaches to student affective…
Descriptors: Psychological Patterns, Measurement Techniques, Observation, Middle School Students
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Napol Rachatasumrit; Paulo F. Carvalho; Kenneth R. Koedinger – International Educational Data Mining Society, 2024
What does it mean for a model to be a better model? One conceptualization, indeed a common one in Educational Data Mining, is that a better model is the one that fits the data better, that is, higher prediction accuracy. However, oftentimes, models that maximize prediction accuracy do not provide meaningful parameter estimates, making them less…
Descriptors: Data Analysis, Models, Prediction, Accuracy
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