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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Mengjiao Zhang – ProQuest LLC, 2024
The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While Federated Learning offers a solution by model training across decentralized devices or servers, thereby…
Descriptors: Privacy, Cooperative Learning, Natural Language Processing, Learning Processes
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Li Chen; Gen Li; Boxuan Ma; Cheng Tang; Masanori Yamada – International Association for Development of the Information Society, 2024
This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge…
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving
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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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Chia-Ju Lin; Wei-Sheng Wang; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Journal of Educational Computing Research, 2025
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…
Descriptors: Natural Language Processing, Computational Linguistics, Technology Uses in Education, STEM Education
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Jay Fie Paler Luzano – International Journal of Technology in Education, 2025
Integrating artificial intelligence (AI) technologies into various educational domains has garnered significant attention. Among these technologies, ChatGPT stands out as a powerful tool that holds the potential to revolutionize the landscape of mathematics education. This study aims to explore the emerging trends and critical issues surrounding…
Descriptors: Mathematics Education, Educational Trends, Artificial Intelligence, Technology Uses in Education
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Lee McCallum – Journal for Multicultural Education, 2024
Purpose: This paper aims to present a lesson that showcases how artificial intelligence (AI) tools may be chiefly used in L2 language classrooms to design culture-focussed telecollaboration tasks and aid their completion by students. Design/methodology/approach: The paper begins by reviewing traditional approaches and guidance for developing…
Descriptors: Artificial Intelligence, Intercultural Communication, Second Language Learning, Telecommunications
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Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Yipu Zheng – ProQuest LLC, 2024
This dissertation investigates how collective process-oriented documentation tools, combined with Natural Language Processing (NLP) techniques, can enhance knowledge construction in hands-on, open-ended learning environments, such as makerspaces. Through a three-year design-based research, the study developed and tested a collective documentation…
Descriptors: Shared Resources and Services, Open Education, Documentation, Natural Language Processing
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Colin Green; Eric Brewe; Jillian Mellen; Adrienne Traxler; Sarah Scanlin – Physical Review Physics Education Research, 2024
This project aims to understand physics faculty responses to transitioning to online teaching during the COVID-19 pandemic. We surveyed 662 physics faculty from the United States following the Spring 2020 term; of these, 258 completed a follow-up survey after the Fall 2020 term. We used natural language processing to measure the sentiment scores…
Descriptors: Teacher Attitudes, Online Courses, Physics, Science Instruction
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Yang, Jing – Journal of Advertising Education, 2023
With artificial intelligence (AI) technologies making significant evolutions over the past few years, there is a growing need for advertising students to get familiarized with the different types of AI technologies and explore and experiment with ways to adapt to such changes. This article illustrates the development and implementation of the…
Descriptors: Advertising, Professional Education, Merchandise Information, Course Descriptions
Janice D. Gobert; Michael A. Sao Pedro; Haiying Li; Christine Lott – Grantee Submission, 2023
In this entry, we define Intelligent Tutoring Systems (ITSs) and present a description of their core components. We outline a history of the development of ITSs with a focus on key issues that have driven change and innovation in ITSs from their inception to present day. We also present a brief case study on a specific ITS, Inq-ITS (Inquiry…
Descriptors: Intelligent Tutoring Systems, Student Evaluation, Evaluation Methods, Natural Language Processing
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Bozkurt, Aras; Xiao, Junhong; Lambert, Sarah; Pazurek, Angelica; Crompton, Helen; Koseoglu, Suzan; Farrow, Robert; Bond, Melissa; Nerantzi, Chrissi; Honeychurch, Sarah; Bali, Maha; Dron, Jon; Mir, Kamran; Stewart, Bonnie; Costello, Eamon; Mason, Jon; Stracke, Christian M.; Romero-Hall, Enilda; Koutropoulos, Apostolos; Toquero, Cathy Mae; Singh, Lenandlar; Tlili, Ahmed; Lee, Kyungmee; Nichols, Mark; Ossiannilsson, Ebba; Brown, Mark; Irvine, Valerie; Raffaghelli, Juliana Elisa; Santos-Hermosa, Gema; Farrell, Orna; Adam, Taskeen; Thong, Ying Li; Sani-Bozkurt, Sunagul; Sharma, Ramesh C.; Hrastinski, Stefan; Jandric, Petar – Asian Journal of Distance Education, 2023
While ChatGPT has recently become very popular, AI has a long history and philosophy. This paper intends to explore the promises and pitfalls of the Generative Pre-trained Transformer (GPT) AI and potentially future technologies by adopting a speculative methodology. Speculative future narratives with a specific focus on educational contexts are…
Descriptors: Artificial Intelligence, Technology Uses in Education, Affordances, Teacher Role
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
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