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Showing 1 to 15 of 27 results Save | Export
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Bauer, Elisabeth; Greisel, Martin; Kuznetsov, Ilia; Berndt, Markus; Kollar, Ingo; Dresel, Markus; Fischer, Martin R.; Fischer, Frank – British Journal of Educational Technology, 2023
Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a…
Descriptors: Peer Relationship, Feedback (Response), Artificial Intelligence, Natural Language Processing
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
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Jessie S. Barrot – Technology, Knowledge and Learning, 2024
This emerging technology report delves into the role of ChatGPT, an OpenAI conversational AI, in language learning. The initial section introduces ChatGPT's nature and highlights its features, including accessibility, personalization, immersive learning, and instant feedback, which render it a valuable asset for language learners and educators…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Acquisition
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Wongvorachan, Tarid; Lai, Ka Wing; Bulut, Okan; Tsai, Yi-Shan; Chen, Guanliang – Journal of Applied Testing Technology, 2022
Feedback is a crucial component of student learning. As advancements in technology have enabled the adoption of digital learning environments with assessment capabilities, the frequency, delivery format, and timeliness of feedback derived from educational assessments have also changed progressively. Advanced technologies powered by Artificial…
Descriptors: Artificial Intelligence, Feedback (Response), Learning Analytics, Natural Language Processing
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Jacob Holster – Music Educators Journal, 2024
ChatGPT is emerging as a formidable asset for music educators, poised to enhance student engagement, refine assessment methods, and automate repetitive tasks related to music teaching. The core of this perspective revolves around the use of custom prompt templates that support individualized and reflexive teaching practices. The broader…
Descriptors: Music Education, Artificial Intelligence, Natural Language Processing, Man Machine Systems
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Adam Keath; James Wyant; Brooke Towner – Journal of Physical Education, Recreation & Dance, 2024
AI tools can revolutionize physical education (PE) by assisting teachers in various ways, such as curriculum development, providing feedback, enhancing content knowledge and data analysis, and promoting student engagement. This article explores various ways in which PE teachers can utilize AI tools like ChatGPT to improve their instruction and…
Descriptors: Physical Education, Physical Education Teachers, Technology Uses in Education, Artificial Intelligence
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Jacob Whitehill; Jennifer LoCasale-Crouch – Journal of Educational Data Mining, 2024
With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…
Descriptors: Artificial Intelligence, Teacher Evaluation, Models, Transcripts (Written Records)
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Philip Slobodsky; Mariana Durcheva; Leonid Kugel – International Journal for Technology in Mathematics Education, 2024
This paper highlights the new enhancements of the Halomda platform designed to improve students' learning and exam preparation. The new features include a Graph Plotter, Algebraic Calculator and Context ChatGPT Recommended Key Guidelines. The use of these features is demonstrated though a working example of solving a double integral, illustrating…
Descriptors: Test Preparation, Mathematics Tests, Student Improvement, Graphs
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Xiaoming Xi – Language Assessment Quarterly, 2023
Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…
Descriptors: Artificial Intelligence, Theory Practice Relationship, Language Tests, Man Machine Systems
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Qian Du; Tamara Tate – CATESOL Journal, 2024
ChatGPT has been at the center of media coverage since its public release at the end of 2022. Given ChatGPT's capacity for generating human-like text on a wide range of subjects, it is not surprising that educators, especially those who teach writing, have raised concerns regarding the implications of generative AI tools on issues of plagiarism…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Plagiarism
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Pérez Castillejo, Susana – Research-publishing.net, 2021
Automatic Speech Recognition (ASR) is a digital communication method that transforms spoken discourse into written text. This rapidly evolving technology is used in email, text messaging, or live video captioning. Current ASR systems operate in conjunction with Natural Language Processing (NLP) technology to transform speech into text that people…
Descriptors: Automation, Assistive Technology, Educational Technology, Speech Communication
Pavlik, Philip I., Jr.; Olney, Andrew M.; Banker, Amanda; Eglington, Luke; Yarbro, Jeffrey – Grantee Submission, 2020
An intelligent textbook may be considered to be an interaction layer that lies between the text and the student, helping the student to master the content in the text. The Mobile Fact and Concept Training System (MoFaCTS) is an adaptive instructional system for simple content that has been developed into an interaction layer to mediate textbook…
Descriptors: Textbooks, Intelligent Tutoring Systems, Electronic Learning, Instructional Design
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Akamoglu, Yusuf; Dinnebeil, Laurie – Young Exceptional Children, 2017
Naturalistic language and communication strategies (i.e., naturalistic teaching strategies) refer to practices that are used to promote the child's language and communication skills either through verbal (e.g., spoken words) or nonverbal (e.g., gestures, signs) interactions between an adult (e.g., parent, teacher) and a child. Use of naturalistic…
Descriptors: Early Intervention, Coaching (Performance), Feedback (Response), Communication Strategies
Allen, Laura K. – International Educational Data Mining Society, 2015
The purpose of intelligent tutoring systems is to provide students with personalized instruction and feedback. The focus of these systems typically rests in the adaptability of the feedback provided to students, which relies on automated assessments of performance in the system. A large focus of my previous work has been to determine how natural…
Descriptors: Intelligent Tutoring Systems, Individual Differences, Natural Language Processing, Student Evaluation
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Chun, Dorothy M. – Educational Technology & Society, 2019
Based on my role as Editor in Chief of the journal Language Learning & Technology since 2000 and on my experiences as a technology-enhanced language learning (TELL) researcher, developer and teacher, I will provide an overview of recent cutting-edge research on the uses of technologies for second language teaching and learning. I suggest that…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Second Language Learning, Educational Technology
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