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Niki Chatzipanagiotou; Anita Mirijamdotter; Christina Mörtberg – Learning Organization, 2025
Purpose: This paper aims to focus on academic library managers' learning practices in the context of cooperative work supported by computational artefacts. Academic library managers' everyday work is mainly cooperative. Their cooperation is supported predominantly by computational artefacts. Learning how to use the computational artefacts…
Descriptors: Foreign Countries, Research Libraries, Librarians, Cooperative Planning
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Xinming Chen; Ziqian Zhou; Malila Prado – International Journal of Assessment Tools in Education, 2025
This study explores the efficacy of ChatGPT-3.5, an AI chatbot, used as an Automatic Essay Scoring (AES) system and feedback provider for IELTS essay preparation. It investigates the alignment between scores given by ChatGPT-3.5 and those assigned by official IELTS examiners to establish its reliability as an AES. It also identifies the strategies…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Bei Cai; Ziyu He; Hong Fu; Yang Zheng; Yanjie Song – IEEE Transactions on Learning Technologies, 2025
Much research has applied automated writing evaluation (AWE) systems to English writing instruction; however, understanding how students internalize and apply this feedback to reduce writing errors is difficult, largely due to the personal and private nature of this process. Therefore, this research utilized eye-tracking technology to explore the…
Descriptors: Undergraduate Students, Majors (Students), Writing (Composition), Writing Evaluation
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Johan Syahbrudin; Edi Istiyono; Moh. Khairudin; Anita Anggraini; Indah Urwatin Wusqo; Metta Mariam; Yenni Muflihan – Contemporary Educational Technology, 2025
Computer-based assessment (CBA) is a top-rated tool for conducting assessments, mapping learning outcomes, and selecting new candidates. Research that examines the development and use of CBA is also increasing from year to year, so without bibliometric analysis, it would be quite challenging to keep up with all of these studies. This study aims to…
Descriptors: Computer Assisted Testing, Educational Research, Educational Trends, Bibliometrics
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Ruth Irwin – Educational Philosophy and Theory, 2025
Education is concerned with the production of intelligence. Is AI intelligent? and what are the implications for educating humanity? Samuel Butler makes the case that machinery emerges in co-relation with the evolution of humanity. In other words, the evolution of machines relies on the human intervention for reproduction, and the evolution of…
Descriptors: Computer Software, Artificial Intelligence, Educational Philosophy, Humanism
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Ali Sartaz Khan; Tolulope Ogunremi; Ahmed Attia; Dorottya Demszky – International Educational Data Mining Society, 2025
Speaker diarization, the process of identifying "who spoke when" in audio recordings, is essential for understanding classroom dynamics. However, classroom settings present distinct challenges, including poor recording quality, high levels of background noise, overlapping speech, and the difficulty of accurately capturing children's…
Descriptors: Audio Equipment, Acoustics, Classroom Environment, Models
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Chen-Chen Liu; Gwo-Jen Hwang; Peng Yu; Yun-Fang Tu; Youmei Wang – Educational Technology Research and Development, 2025
Oral practice is challenging for foreign language education, and Corrective Feedback (CF) is often used to point out learners' pronunciation errors and to help them improve their oral skills in foreign language courses. CF is generally considered as a necessary condition for foreign language acquisition, and "reflection" and…
Descriptors: Automation, Error Correction, Feedback (Response), Peer Evaluation
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Fromm, Davida; MacWhinney, Brian; Thompson, Cynthia K. – Journal of Speech, Language, and Hearing Research, 2020
Purpose: Analysis of spontaneous speech samples is important for determining patterns of language production in people with aphasia. To accomplish this, researchers and clinicians can use either hand coding or computer-automated methods. In a comparison of the two methods using the hand-coding NNLA (Northwestern Narrative Language Analysis) and…
Descriptors: Automation, Computational Linguistics, Aphasia, Coding
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Nuijten, Michèle B.; Polanin, Joshua R. – Research Synthesis Methods, 2020
We present the R package and web app "statcheck" to automatically detect statistical reporting inconsistencies in primary studies and meta-analyses. Previous research has shown a high prevalence of reported p-values that are inconsistent--meaning a re-calculated p-value, based on the reported test statistic and degrees of freedom, does…
Descriptors: Meta Analysis, Statistical Analysis, Reliability, Replication (Evaluation)
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Ioannidou, Alexandra; Parma, Andrea – Adult Education Quarterly: A Journal of Research and Theory, 2022
This study explores the relation between risk of job automation and participation in adult education and training (AET) and examines variation in that relation across welfare regimes distinguishing between situational and institutional barriers. Using microdata of PIAAC, we analyze participation in formal or nonformal AET for job-related reasons…
Descriptors: Automation, Risk, Adult Education, Participation
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Tavares, Paula Correia; Gomes, Elsa Ferreira; Henriques, Pedro Rangel; Vieira, Diogo Manuel – Open Education Studies, 2022
Computer Programming Learners usually fail to get approved in introductory courses because solving problems using computers is a complex task. The most important reason for that failure is concerned with motivation; motivation strongly impacts on the learning process. In this paper we discuss how techniques like program animation, and automatic…
Descriptors: Learner Engagement, Programming, Computer Science Education, Problem Solving
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Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Journal of Educational Technology in Higher Education, 2022
Automatic analysis of the myriad discussion messages in large online courses can support effective educator-learner interaction at scale. Robust classifiers are an essential foundation for the use of automatic analysis of cognitive presence in practice. This study reports on the application of a revised machine learning approach, which was…
Descriptors: MOOCs, Philosophy, Artificial Intelligence, Computer Mediated Communication
Danielle S. McNamara; Panayiota Kendeou – Grantee Submission, 2022
We propose a framework designed to guide the development of automated writing practice and formative evaluation and feedback for young children (K-5 th grade) -- the early Automated Writing Evaluation (early-AWE) Framework. e-AWE is grounded on the fundamental assumption that e-AWE is needed for young developing readers, but must incorporate…
Descriptors: Writing Evaluation, Automation, Formative Evaluation, Feedback (Response)
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Danielle S. McNamara; Panayiota Kendeou – Assessment in Education: Principles, Policy & Practice, 2022
We propose a framework designed to guide the development of automated writing practice and formative evaluation and feedback for young children (K-5th grade) -- the early Automated Writing Evaluation (early-AWE) Framework. e-AWE is grounded on the fundamental assumption that e-AWE is needed for young developing readers, but must incorporate…
Descriptors: Writing Evaluation, Automation, Formative Evaluation, Feedback (Response)
Laura A. Warner; Alicia L. Rihn; Amy Fulcher; Susan Schexnayder; Anthony V. LeBude – Journal of Agricultural Education, 2022
This study examined factors that shape how nursery growers perceive automated nursery technologies and evaluate how these perceptions relate to growers' adoption. We applied Rogers' (2003) Diffusion of Innovations to understand growers' perceptions of automated technologies to inform Extension programming serving niche audiences in the nursery and…
Descriptors: Agricultural Occupations, Automation, Agricultural Production, Innovation
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