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James McGibney – ProQuest LLC, 2024
This phenomenological study's objective was to review the existing initiatives for cybersecurity awareness and training that are in place for the K-12 education system throughout the United States. Every facet of life is now plagued by the potential, perceived, and real threat of cyber warfare, which includes, but is not limited to, K-12 schools…
Descriptors: Information Security, Computer Security, Crime, Kindergarten
National Council of Teachers of Mathematics, 2025
Get a deeper understanding of teaching functions, 9-12 with our concise and comprehensive Go-To Guide. Based on "Developing Essential Understanding of Functions 9-12" and "Putting Essential Understanding of Functions into Practice 9-12," this summary distills the key concepts and ideas into a quick-reference guide that's…
Descriptors: Mathematics Instruction, Teaching Methods, Kindergarten, Elementary Secondary Education
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Alison L. Zagona; Jennifer A. Kurth; Virginia L. Walker; Andrea Ruppar; Sheldon Loman; Sarah Bubash – Research and Practice for Persons with Severe Disabilities, 2024
Students with extensive support needs are at risk of demonstrating challenging behavior due to inadequate support of their individual needs or class-wide factors such as low quality of instruction. Students with extensive support needs are also among the students who are most likely to experience aversive interventions and be placed in segregated…
Descriptors: Student Behavior, Intervention, Behavior Problems, Behavior Modification
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
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Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change