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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
Rania Abdelghani; Yen-Hsiang Wang; Xingdi Yuan; Tong Wang; Pauline Lucas; Hélène Sauzéon; Pierre-Yves Oudeyer – International Journal of Artificial Intelligence in Education, 2024
The ability of children to ask curiosity-driven questions is an important skill that helps improve their learning. For this reason, previous research has explored designing specific exercises to train this skill. Several of these studies relied on providing semantic and linguistic cues to train them to ask more of such questions (also called…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Inquiry
Paul Deane; Duanli Yan; Katherine Castellano; Yigal Attali; Michelle Lamar; Mo Zhang; Ian Blood; James V. Bruno; Chen Li; Wenju Cui; Chunyi Ruan; Colleen Appel; Kofi James; Rodolfo Long; Farah Qureshi – ETS Research Report Series, 2024
This paper presents a multidimensional model of variation in writing quality, register, and genre in student essays, trained and tested via confirmatory factor analysis of 1.37 million essay submissions to ETS' digital writing service, Criterion®. The model was also validated with several other corpora, which indicated that it provides a…
Descriptors: Writing (Composition), Essays, Models, Elementary School Students
Muhammet Remzi Karaman; I?dris Göksu – International Journal of Technology in Education, 2024
In this research, we aimed to determine whether students' math achievements improved using ChatGPT, one of the chatbot tools, to prepare lesson plans in primary school math courses. The research was conducted with a pretest-posttest control group experimental design. The study comprises 39 third-grade students (experimental group = 24, control…
Descriptors: Artificial Intelligence, Natural Language Processing, Lesson Plans, Instructional Effectiveness
Urrutia, Felipe; Araya, Roberto – Journal of Educational Computing Research, 2024
Written answers to open-ended questions can have a higher long-term effect on learning than multiple-choice questions. However, it is critical that teachers immediately review the answers, and ask to redo those that are incoherent. This can be a difficult task and can be time-consuming for teachers. A possible solution is to automate the detection…
Descriptors: Elementary School Students, Grade 4, Elementary School Mathematics, Mathematics Tests
Lei Du; Beibei Lv – Education and Information Technologies, 2024
This research examines the influence of integrating generative artificial intelligence (GAI) in education, focusing on its acceptance and utilization among elementary education students. Grounded in the Task-Technology Fit (TTF) Theory and an expanded iteration of the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study…
Descriptors: Influences, Student Attitudes, Artificial Intelligence, Technology Uses in Education
Xiaohong Liu; Baoxin Guo; Wei He; Xiaoyong Hu – Journal of Educational Computing Research, 2025
Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students' learning outcomes remains controversial. This study aimed to examine the impact of GenAI on the learning outcomes of K-12 and higher education students, and explore the moderating factors influencing this impact. A…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Yu Bai; Jun Li; Jun Shen; Liang Zhao – IEEE Transactions on Learning Technologies, 2024
The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Julia Lademann; Jannik Henze; Sebastian Becker-Genschow – Physical Review Physics Education Research, 2025
This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Irene Picton; Christina Clark – National Literacy Trust, 2024
Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The National Literacy Trust is interested in exploring how such platforms might influence, and potentially redefine, what it means to be literate in the digital age. Based on data from more than 50,000 children and young people taking…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Irene Picton; Christina Clark – National Literacy Trust, 2024
Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The ability of generative-AI tools such as ChatGPT, Gemini and Claude to both 'write' and 'read' texts in a human-like manner means they are set to play an increasingly important role in the literacy lives of children, young people and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education