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Paul P. Martin; David Kranz; Peter Wulff; Nicole Graulich – Journal of Research in Science Teaching, 2024
Constructing arguments is essential in science subjects like chemistry. For example, students in organic chemistry should learn to argue about the plausibility of competing chemical reactions by including various sources of evidence and justifying the derived information with reasoning. While doing so, students face significant challenges in…
Descriptors: Science Education, Chemistry, Persuasive Discourse, Writing Evaluation
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Karin Tengler; Gerhard Brandhofer – Discover Education, 2025
Generative Artificial Intelligence (GenAI) models have grown increasingly popular among pre-service teachers (PSTs) and have become their constant companions, primarily assisting them in scientific writing. This article presents a study that investigates the differences and benefits of GenAI in the scientific writing process. Essays generated by…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Writing (Composition)
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Xuefan Li; Tingsong Li; Minjuan Wang; Sining Tao; Xiaoxu Zhou; Xiaoqing Wei; Naiqing Guan – IEEE Transactions on Learning Technologies, 2025
With the rapid advancement of generative artificial intelligence (GAI), its application in educational settings has increasingly become a focal point, particularly in enhancing students' analytical capabilities. This study examines the effectiveness of the ChatGPT prompt framework in improving text analysis skills among students, specifically…
Descriptors: Artificial Intelligence, Technology Uses in Education, High School Students, Foreign Countries
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Zhang, Ruofei; Zou, Di; Cheng, Gary – Innovation in Language Learning and Teaching, 2023
EFL learners generally have the problem of logical fallacies in EFL argumentative writings. Logical fallacies are errors in reasoning that can undermine EFL argumentative writing quality. Explicit training on logical fallacies may help learners deal with the problem and enhance their self-efficacy and proficiency in EFL argumentative writing,…
Descriptors: English (Second Language), Second Language Learning, Persuasive Discourse, Writing Instruction
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Eli Bagno; Thierry Dana-Picard; Shulamit Reches – Open Education Studies, 2024
As soon as a new technology emerges, the education community explores its affordances and the possibilities to apply it in education. In this article, we analyze sessions with ChatGPT around topics in basic linear algebra. We reflect on the affordances and changes between two versions of ChatGPT since its worldwide publication in our area of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Algebra
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Patac, Adriano Villarosa, Jr.; Patac, Louida Penera; Crispo, Nicolas Ensomo, Jr. – Journal of Research and Advances in Mathematics Education, 2022
Teaching axiomatic representation of mathematical objects in all grades can and should be done. The paper analyzes students' understanding and how they perceive theorems using problem posing. We looked at how English-language learners create questions about four geometric theorems from a 9th-grade math textbook. The analysis looks at the…
Descriptors: Foreign Countries, High School Students, Grade 9, Second Language Learning
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Talan, Tarik; Kalinkara, Yusuf – International Society for Technology, Education, and Science, 2022
With the rapid development of science and technology in recent years, the application areas of fuzzy logic have also gained speed. Fuzzy logic is a frequently preferred approach in the educational process, and it can be said that scientific publications on this topic have recently gained momentum in the literature. In this context, the present…
Descriptors: Databases, Research Reports, Foreign Countries, Universities
Khashabi, Daniel – ProQuest LLC, 2019
"Natural language understanding" (NLU) of text is a fundamental challenge in AI, and it has received significant attention throughout the history of NLP research. This primary goal has been studied under different tasks, such as Question Answering (QA) and Textual Entailment (TE). In this thesis, we investigate the NLU problem through…
Descriptors: Natural Language Processing, Artificial Intelligence, Task Analysis, Questioning Techniques
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Perikos, Isidoros; Grivokostopoulou, Foteini; Hatzilygeroudis, Ioannis – International Journal of Artificial Intelligence in Education, 2017
Logic as a knowledge representation and reasoning language is a fundamental topic of an Artificial Intelligence (AI) course and includes a number of sub-topics. One of them, which brings difficulties to students to deal with, is converting natural language (NL) sentences into first-order logic (FOL) formulas. To assist students to overcome those…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Natural Language Processing, Logical Thinking
Barker-Plummer, Dave; Dale, Robert; Cox, Richard; Romanczuk, Alex – International Educational Data Mining Society, 2012
We have assembled a large corpus of student submissions to an automatic grading system, where the subject matter involves the translation of natural language sentences into propositional logic. Of the 2.3 million translation instances in the corpus, 286,000 (approximately 12%) are categorized as being in error. We want to understand the nature of…
Descriptors: Logical Thinking, Grading, Natural Language Processing, Translation
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Lin, Marcia C.; Eylon, Bat-Sheva; Rafferty, Anna; Vitale, Jonathan M. – EURASIA Journal of Mathematics, Science & Technology Education, 2015
Citizens need the capability to conduct their own inquiry projects so that they can make sense of claims about new energy policies, health remedies, or financial opportunities. To develop the lifelong capability to grapple with these dilemmas, we report on ways to design precollege units that engage students in realistic, personally relevant…
Descriptors: Lifelong Learning, Inquiry, Learning Strategies, Constructivism (Learning)
Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – Grantee Submission, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
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Benjamin D. Nye; Arthur C. Graesser; Xiangen Hu – International Journal of Artificial Intelligence in Education, 2014
AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Software, Artificial Intelligence
Florio, Salvatore – ProQuest LLC, 2010
In this dissertation, I defend "semantic singularism", which is the view that syntactically plural terms, such as "they" or "Russell and Whitehead", are semantically singular. A semantically singular term is a term that denotes a single entity. Semantic singularism is to be distinguished from "syntactic singularism", according to which…
Descriptors: Semantics, Natural Language Processing, Semiotics, Morphemes
Katz, Sandra; Jordan, Pamela; Litman, Diane – Society for Research on Educational Effectiveness, 2011
The natural-language tutorial dialogue system that the authors are developing will allow them to focus on the nature of interactivity during tutoring as a malleable factor. Specifically, it will serve as a research platform for studies that manipulate the frequency and types of verbal alignment processes that take place during tutoring, such as…
Descriptors: Natural Language Processing, Physics, Logical Thinking, Intelligent Tutoring Systems
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