93887 research outputs found
Sort by
Evaluating LLM-Generated Personalized Text Content for Middle School Science Students
Get PDFGenerative artificial intelligence and large language models (LLMs) have proven to be disruptors in education due to their ability to produce human-like text, placing these models under heavy scrutiny. However, LLMs embody a diverse knowledge base and have been shown to be few-shot learners (Brown et al., 2020) that can quickly adapt their output in response to user-provided context. Together, these facets situate LLMs as powerful tools capable of developing personalized learning materials for K-12 students without the need for expansive training data. As this potential has yet to be evaluated in literature, this study aims to investigate the ability of LLMs to adapt science texts to middle school students’ learning preferences
A Comparative Study of AI Integration Barriers in K–12 Education in South Korea, Taiwan, and the United States
Get PDFThis comparative study investigated barriers to AI integration in K-12 education across South Korea, Taiwan, and the United States, addressing a gap in understanding educators\u27 perspectives (Casal-Otero et al., 2023). Semi-structured interviews with 45 educators were conducted and analyzed using Ertmer\u27s first-and-second-order barriers to change framework (1999), revealing first-order and second-order barriers. Despite challenges, participants expressed positive views toward AI integration. The study identified four themes and highlighted differences between countries with and without clear AI integration policies. This contributes to a comprehensive understanding of AI integration in K-12 education across different national contexts
Artificial Intelligence in ELL Classrooms: A Qualitative Study of Pre-Service Teachers’ Perspectives
No full textThis study examines pre-service teachers’(PSTs) perspectives on the use of Artificial Intelligence (AI) in classrooms with English Language Learners (ELLs). Ninety PSTs from a U.S. university completed written journal reflections on the implications of AI for teaching and assessing ELLs, as well as how teacher education programs could prepare them for the integration of AI into future classrooms. Thematic analysis showed positive and negative perspectives about AI and a call for curricular integration of AI-related content and opportunities to experiment with it. Participants also viewed human connection as central to teaching, confirming recent calls that warn against AI as a replacement for human teachers
