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Paiheng Xu; Jing Liu; Nathan Jones; Julie Cohen; Wei Ai – Annenberg Institute for School Reform at Brown University, 2024
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers' expertise and idiosyncratic factors, preventing teachers from getting timely and frequent feedback. Different from prior research that…
Descriptors: Educational Quality, Educational Assessment, Teacher Effectiveness, Natural Language Processing
Rui Guan; Mladen Rakovic; Guanliang Chen; Dragan Gaševic – Education and Information Technologies, 2025
Engagement in self-regulated learning (SRL) may improve academic achievements and support development of lifelong learning skills. Despite its educational potential, many students find SRL challenging. Educational chatbots have a potential to scaffold or externally regulate SRL processes by interacting with students in an adaptive way. However, to…
Descriptors: Literature Reviews, Artificial Intelligence, Technology Uses in Education, Educational Technology
Maria Dimeli; Apostolos Kostas – Journal of Information Technology Education: Research, 2025
Aim/Purpose: The purpose of this systematic review is to identify and analyze the current findings of empirical research on the use of ChatGPT in school and higher education. Background: As AI reshapes education, the adoption of ChatGPT has the potential to revolutionize teaching and learning in school and higher educational settings. Meanwhile,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Barriers
Omar Albaloul; Risto Marttinen; Chad Killian – Journal of Physical Education, Recreation & Dance, 2024
The recent emergence of artificial intelligence (AI) tools has significantly influenced different fields, including education. One notable example is ChatGPT, an AI-driven large language model (LLM) developed by OpenAI. This tool holds potential for supporting both teachers and students in the teaching and learning process. While some fields of…
Descriptors: Physical Education, Artificial Intelligence, Natural Language Processing, Man Machine Systems
Dorottya Demszky; Jing Liu; Heather C. Hill; Shyamoli Sanghi; Ariel Chung – Annenberg Institute for School Reform at Brown University, 2023
While recent studies have demonstrated the potential of automated feedback to enhance teacher instruction in virtual settings, its efficacy in traditional classrooms remains unexplored. In collaboration with TeachFX, we conducted a pre-registered randomized controlled trial involving 523 Utah mathematics and science teachers to assess the impact…
Descriptors: Elementary Secondary Education, Mathematics Teachers, Science Teachers, Automation
Mustafa Taktak; Mehmet Sükrü Bellibas; Mustafa Özgenel – Educational Process: International Journal, 2024
Background/Purpose: Integrating artificial intelligence tools within educational settings has generated considerable debate, yet empirical research that offers implications of its usage remains scarce. This study aims to qualitatively assess the perceptions and experiences of school principals and teachers regarding the use of ChatGPT in K-12…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Futures (of Society)
Douglas Harris; Jamie Carroll; Debbie Kim; Nicholas Mattei; Olivia Carr – National Center for Research on Education Access and Choice, 2024
Massive online user review platforms, with their star ratings and text reviews, are reshaping the information available for consumer and public service decisions. We study the leading K-12 schooling platform, GreatSchools, applying machine learning (Natural Language Processing, NLP) to 600,000 reviews that encompass the vast majority of the…
Descriptors: Elementary Secondary Education, School Effectiveness, Parents, Teachers

Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing
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
Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Grantee Submission, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Teacher Education Programs, Preservice Teachers
Gillani, Nabeel; Eynon, Rebecca; Chiabaut, Catherine; Finkel, Kelsey – Educational Technology & Society, 2023
Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations--many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Educational Benefits
Haesol Bae; Jaesung Hur; Jaesung Park; Gi Woong Choi; Jewoong Moon – Online Learning, 2024
This study examined pre-service teachers' perspectives on integrating generative AI (GenAI) tools into their own learning and teaching practices. Discussion posts from asynchronous online courses on ChatGPT were analyzed using the Diffusion of Innovations framework to explore awareness, willingness to apply ChatGPT to instruction, and potential…
Descriptors: Preservice Teachers, Teacher Attitudes, Artificial Intelligence, Technology Uses in Education
Shah, Priten – Jossey-Bass, An Imprint of Wiley, 2023
Among teachers, there is a cloud of rumors, confusion, and fear surrounding the rise of artificial intelligence. "AI and the Future of Education" is a timely response to this general state of panic, showing you that AI is a tool to leverage, not a threat to teaching and learning. By understanding what AI is, what it does, and how it can…
Descriptors: Artificial Intelligence, Futures (of Society), Teaching (Occupation), Ethics
Terzopoulos, George; Satratzemi, Maya – Informatics in Education, 2020
In recent years, Artificial Intelligence (AI) has shown significant progress and its potential is growing. An application area of AI is Natural Language Processing (NLP). Voice assistants incorporate AI by using cloud computing and can communicate with the users in natural language. Voice assistants are easy to use and thus there are millions of…
Descriptors: Artificial Intelligence, Natural Language Processing, Assistive Technology, Technology Uses in Education
Editorial Projects in Education, 2023
Artificial Intelligence (AI) is transforming traditional learning landscapes. This Spotlight will empower you with steps educators can take to be prepared for teaching in an AI-powered world; tips for using AI to plan lessons, email parents, and help struggling students; insights on principles to consider when crafting AI guidance; a guide to the…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Educational Change