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Victoria Kishchak; Anna Ewert; Paulina Halczak; Pawel Kleka; Marcin Szczerbinski – Reading and Writing: An Interdisciplinary Journal, 2024
RAN (Rapid Automatized Naming) is known to be a robust predictor of reading development in different languages. Much less is known about RAN predictive power in bilingual contexts. This is the first meta-analysis of research with bilingual children, assessing the strength of the RAN-reading relationship both within and across languages. It also…
Descriptors: Automation, Naming, Meta Analysis, Bilingualism
Joseph E. Aoun – MIT Press, 2024
In 2017, "Robot-Proof," the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a…
Descriptors: Artificial Intelligence, Higher Education, Educational Technology, Technology Uses in Education
UK Department for Education, 2024
Over the last year, interest in and use of generative artificial intelligence (GenAI) has rapidly increased. Although GenAI is not new, recent advances in the underlying technology and greater accessibility mean that the public can now use it more easily. This poses opportunities and challenges for the education sector. The Digital Strategy…
Descriptors: Artificial Intelligence, Technology Uses in Education, Automation, Information Technology
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Vanda Santos; Joana Teles; Pedro Quaresma – International Journal for Technology in Mathematics Education, 2024
Using a Dynamic Geometry System (DGS) students can engage in a dynamic learning process that allows them to experiment, create strategies, make conjectures, argue, and deduce mathematical properties. A DGS enables the introduction of proofs, by providing visual aids. The proof of the conjectures made emerges as the next step towards formalising…
Descriptors: Grade 7, Mathematics Education, Geometry, Validity
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Sophia Soomin Lee; Robert L. Moore – Online Learning, 2024
In this systematic review, we synthesize ten empirical peer-reviewed articles published between 2019 and 2023 that used generative artificial intelligence (GenAI) for automated feedback in higher education. There are significant opportunities and challenges to integrate these tools effectively into learning environments as the demand for timely…
Descriptors: Artificial Intelligence, Higher Education, Feedback (Response), Grading
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Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
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Saida Ulfa; Ence Surahman; Izzul Fatawi; Hirashima Tsukasa – Electronic Journal of e-Learning, 2024
The purpose of this study was to evaluate the factors that influence behavioural intention (BI) to use the Online Summary-with Automated Feedback (OSAF) in a MOOCs platform. Task-Technology Fit (TTF) was the main framework used to analyse the match between task requirements and technology characteristics, predictng the utilisation of the…
Descriptors: MOOCs, Intention, Automation, Feedback (Response)
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Xavier Ochoa; Heru Zhao – Journal of Learning Analytics, 2024
Providing automated feedback that facilitates the practice and acquisition of oral presentation skills has been one of the notable applications of multimodal learning analytics (MmLA). However, the closedness and general unavailability of existing systems have reduced their potential impact and benefits. This work introduces OpenOPAF, an…
Descriptors: Open Source Technology, Multimedia Materials, Automation, Feedback (Response)
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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
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Xieling Chen; Di Zou; Haoran Xie; Gary Cheng; Zongxi Li; Fu Lee Wang – International Review of Research in Open and Distributed Learning, 2025
Massive open online courses (MOOCs) offer rich opportunities to comprehend learners' learning experiences by examining their self-generated course evaluation content. This study investigated the effectiveness of fine-tuned BERT models for the automated classification of topics in online course reviews and explored the variations of these topics…
Descriptors: MOOCs, Distance Education, Online Courses, Course Evaluation
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Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
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Ayfer Sayin; Mark Gierl – Educational Measurement: Issues and Practice, 2024
The purpose of this study is to introduce and evaluate a method for generating reading comprehension items using template-based automatic item generation. To begin, we describe a new model for generating reading comprehension items called the text analysis cognitive model assessing inferential skills across different reading passages. Next, the…
Descriptors: Algorithms, Reading Comprehension, Item Analysis, Man Machine Systems
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Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
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Aaron Haim; Eamon Worden; Neil T. Heffernan – Grantee Submission, 2024
Since GPT-4's release it has shown novel abilities in a variety of domains. This paper explores the use of LLM-generated explanations as on-demand assistance for problems within the ASSISTments platform. In particular, we are studying whether GPT-generated explanations are better than nothing on problems that have no supports and whether…
Descriptors: Artificial Intelligence, Learning Management Systems, Computer Software, Intelligent Tutoring Systems
Emmanuel Dumbuya – Online Submission, 2025
The integration of artificial intelligence (AI) into educational ecosystems represents a paradigm shift in pedagogical practices and educational governance. While AI offers unprecedented opportunities to personalize learning, optimize administrative processes, and provide intelligent tutoring, it poses significant challenges to maintaining human…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Technology Integration
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