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Showing 1 to 15 of 18 results Save | Export
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Hunkoog Jho; Minsu Ha – Journal of Baltic Science Education, 2024
This study aimed at examining the performance of generative artificial intelligence to extract argumentation elements from text. Thus, the researchers developed a web-based framework to provide automated assessment and feedback relying on a large language model, ChatGPT. The results produced by ChatGPT were compared to human experts across…
Descriptors: Feedback (Response), Artificial Intelligence, Persuasive Discourse, Models
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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
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Moriah Ariely; Tanya Nazaretsky; Giora Alexandron – Journal of Research in Science Teaching, 2024
One of the core practices of science is constructing scientific explanations. However, numerous studies have shown that constructing scientific explanations poses significant challenges to students. Proper assessment of scientific explanations is costly and time-consuming, and teachers often do not have a clear definition of the educational goals…
Descriptors: Biology, Automation, Individualized Instruction, Science Instruction
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David W. Brown; Dean Jensen – International Society for Technology, Education, and Science, 2023
The growth of Artificial Intelligence (AI) chatbots has created a great deal of discussion in the education community. While many have gravitated towards the ability of these bots to make learning more interactive, others have grave concerns that student created essays, long used as a means of assessing the subject comprehension of students, may…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Software, Writing (Composition)
McCaffrey, Daniel F.; Zhang, Mo; Burstein, Jill – Grantee Submission, 2022
Background: This exploratory writing analytics study uses argumentative writing samples from two performance contexts--standardized writing assessments and university English course writing assignments--to compare: (1) linguistic features in argumentative writing; and (2) relationships between linguistic characteristics and academic performance…
Descriptors: Persuasive Discourse, Academic Language, Writing (Composition), Academic Achievement
Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2023
This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…
Descriptors: Scaffolding (Teaching Technique), Writing Instruction, Writing Processes, Writing (Composition)
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McKnight, Lucinda – Changing English: Studies in Culture and Education, 2021
With artificial intelligence (AI) now producing human-quality text in seconds via natural language generation, urgent questions arise about the nature and purpose of the teaching of writing in English. Humans have already been co-composing with digital tools for decades, in the form of spelling and grammar checkers built into word processing…
Descriptors: Robotics, Artificial Intelligence, Writing (Composition), Writing Instruction
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Sumie Tsz Sum Chan; Noble Po Kan Lo; Alan Man Him Wong – Contemporary Educational Technology, 2024
This paper investigates the effects of large language model (LLM) based feedback on the essay writing proficiency of university students in Hong Kong. It focuses on exploring the potential improvements that generative artificial intelligence (AI) can bring to student essay revisions, its effect on student engagement with writing tasks, and the…
Descriptors: English (Second Language), Second Language Learning, Language Proficiency, Foreign Countries
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Miranty, Delsa; Widiati, Utami – Pegem Journal of Education and Instruction, 2021
Automated Writing Evaluation (AWE) has been considered a potential pedagogical technique that exploits technology to assist the students' writing. However, little attention has been devoted to examining students' perceptions of Grammarly use in higher education context. This paper aims to obtain information regarding the writing process and the…
Descriptors: Foreign Countries, Technology Uses in Education, Writing (Composition), Student Attitudes
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L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
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Huang, Eddie; Valdiviejas, Hannah; Bosch, Nigel – Grantee Submission, 2019
Metacognition is a valuable tool for learning, since it is closely related to self-regulation and awareness of one's own affect. However, methods for automatically detecting and studying metacognition are scarce. Thus, in this paper we describe an algorithm for automatic detection of metacognitive language in writing. We analyzed text from the…
Descriptors: Metacognition, Mathematics, Language Usage, Writing (Composition)
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Tansomboon, Charissa; Gerard, Libby F.; Vitale, Jonathan M.; Linn, Marcia C. – International Journal of Artificial Intelligence in Education, 2017
Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student written work, we compare forms of automated guidance designed to motivate productive revision and help…
Descriptors: Automation, Guidance, Revision (Written Composition), Natural Language Processing
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Rahimi, Zahra; Litman, Diane; Correnti, Richard; Wang, Elaine; Matsumura, Lindsay Clare – International Journal of Artificial Intelligence in Education, 2017
This paper presents an investigation of score prediction based on natural language processing for two targeted constructs within analytic text-based writing: 1) students' effective use of evidence and, 2) their organization of ideas and evidence in support of their claim. With the long-term goal of producing feedback for students and teachers, we…
Descriptors: Scoring, Automation, Scoring Rubrics, Natural Language Processing
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Allen, Laura K.; Perret, Cecile; McNamara, Danielle S. – Grantee Submission, 2016
The relationship between working memory capacity and writing ability was examined via a linguistic analysis of student essays. Undergraduate students (n = 108) wrote timed, prompt-based essays and completed a battery of cognitive assessments. The surface- and discourse-level linguistic features of students' essays were then analyzed using natural…
Descriptors: Cognitive Processes, Writing (Composition), Short Term Memory, Writing Ability
Allen, Laura K.; Likens, Aaron D.; McNamara, Danielle S. – Grantee Submission, 2018
The assessment of argumentative writing generally includes analyses of the specific linguistic and rhetorical features contained in the individual essays produced by students. However, researchers have recently proposed that an individual's ability to flexibly adapt the linguistic properties of their writing may more accurately capture their…
Descriptors: Writing (Composition), Persuasive Discourse, Essays, Language Usage
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