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Showing 1 to 15 of 54 results Save | Export
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Michelle Ronksley-Pavia; Steven Ronksley-Pavia; Chris Bigum – Journal of Advanced Academics, 2025
In many general education classrooms across the world, educators struggle to meet the educational needs of twice-exceptional and multi-exceptional neurodivergent learners, with their confluence of exceptional strengths and exceptional challenges. This article reports the process, findings, and implications of research that implemented a series of…
Descriptors: Elementary Secondary Education, Artificial Intelligence, Twice Exceptional, Gifted Education
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Alexandra S. Dylman; Marie-France Champoux-Larsson; Candice Frances – Educational Psychology, 2025
We report four experiments investigating the effect of prosody on listening comprehension in 11-13-year-old children. Across all experiments, participants listened to short object descriptions and answered content-based questions about said objects. In Experiments 1-3, the descriptions were read in an emotionally positive or neutral tone of voice.…
Descriptors: Intonation, Middle School Students, Foreign Countries, Listening Comprehension
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Torres-Jimenez, Jose; Lescano, Germán; Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo – Education and Information Technologies, 2023
Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language…
Descriptors: Conflict, Identification, Computer Assisted Instruction, Cooperative Learning
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Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
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Sam O'Neill; David Mulgrew; Ovidiu Bagdasar – Open Education Studies, 2025
Large language models (LLMs) hold great promise for enhancing teaching and learning in higher education, yet educators and administrators still lack practical examples to guide their adoption. This article presents insights and use cases from the integration of LLMs into a first-year undergraduate computer science cohort. By employing LLMs as…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, College Faculty
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Jaurès S. H. Kameni; Bernabé Batchakui; Roger Nkambou – International Journal of Artificial Intelligence in Education, 2025
The majority of Sub-Saharan African countries are facing a very negative teacher-learner ratio: one teacher for over 120 learners. In order to support the learner training, we propose optimizing search engines for learning contexts, to enable learners to take optimal advantage of the vast reservoir of Open Educational Resources (OER) available on…
Descriptors: Foreign Countries, Teacher Shortage, Open Educational Resources, Computer Assisted Instruction
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Feifei Wang; Alan C. K. Cheung; Amanda J. Neitzel; Ching Sing Chai – Review of Educational Research, 2025
Given the importance of conversation practice in language learning, chatbots, especially ChatGPT, have attracted considerable attention for their ability to converse with learners using natural language. This review contributes to the literature by examining the currently unclear overall effect of using chatbots on language learning performance…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Learning
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Jaeho Jeon; Seongyong Lee – Education and Information Technologies, 2024
Research has demonstrated the promising potential of chatbots in education. Moreover, technological advancements, such as ChatGPT, prompted us to reexamine distinctions between pedagogical roles that humans and chatbots assume. In this context, a systematic review of 11 experimental studies on human-chatbot comparisons in language education was…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Computer Assisted Instruction
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Albertson, Brendon – Research-publishing.net, 2021
A Computer-Assisted Language Learning (CALL) application, TextMix, was developed as a proof-of-concept for applying Natural Language Processing (NLP) sentence chunking techniques to creating 'sentence scramble' learning tasks. TextMix addresses limitations of existing applications for creating sentence scrambles by using NLP to parse and scramble…
Descriptors: Computer Assisted Instruction, Second Language Learning, Natural Language Processing, Sentences
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Philip Slobodsky; Mariana Durcheva – International Journal of Mathematical Education in Science and Technology, 2025
AI-based bots (ChatGPT) are capable of solving mathematics problems, and students often use them for homework preparation, self-learning, etc. This raises a number of didactical and technical questions: How can students submit assignments containing complex mathematical expressions using only a keyboard? How should mathematics errors in ChatGPT's…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Mathematics Instruction
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Jacqueline Zammit – Technology in Language Teaching & Learning, 2024
The Chat Generative Pretrained Transformer (ChatGPT) is a state-of-the-art artificial intelligence (AI) language model developed by OpenAI. It employs advanced deep-learning algorithms to generate text that mimics human language. ChatGPT, launched on November 30, 2022, has rapidly gained widespread recognition. Its influence on the future of…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Second Language Learning
Charalampos-S Charitsis – ProQuest LLC, 2023
The employment rate of software developers has risen significantly over the last 30 years. As a result, more students are considering computer science as a potential career path. Over the last 15 years, introductory programming course (CS1) enrollment has been increasing at a much faster rate than the increase in the number of CS faculty, with no…
Descriptors: Computer Science Education, Programming, Natural Language Processing, Computer Software
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José Luís Araújo; Isabel Saúde – Journal of Chemical Education, 2024
The rapid evolution of Artificial Intelligence (AI) is profoundly shaping our society. Among various AI tools, ChatGPT stands out for its user-friendly nature and wide accessibility to the public. However, despite their countless potential benefits, these tools also face significant challenges, especially in sensitive areas like Education. In this…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Chemistry
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
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Prapasiri Klayklung; Piyawatjana Chocksathaporn; Pongsakorn Limna; Tanpat Kraiwanit; Kris Jangjarat – Online Submission, 2023
The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper…
Descriptors: Artificial Intelligence, Interaction, Foreign Countries, Technology Integration
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