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Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
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Guher Gorgun; Okan Bulut – Education and Information Technologies, 2024
In light of the widespread adoption of technology-enhanced learning and assessment platforms, there is a growing demand for innovative, high-quality, and diverse assessment questions. Automatic Question Generation (AQG) has emerged as a valuable solution, enabling educators and assessment developers to efficiently produce a large volume of test…
Descriptors: Computer Assisted Testing, Test Construction, Test Items, Automation
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Daniel J. Carragher; Daniel Sturman; Peter J. B. Hancock – Cognitive Research: Principles and Implications, 2024
The human face is commonly used for identity verification. While this task was once exclusively performed by humans, technological advancements have seen automated facial recognition systems (AFRS) integrated into many identification scenarios. Although many state-of-the-art AFRS are exceptionally accurate, they often require human oversight or…
Descriptors: Automation, Human Body, Man Machine Systems, Accuracy
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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
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Ikkyu Choi; Jiangang Hao; Chen Li; Michael Fauss; Jakub Novák – ETS Research Report Series, 2024
A frequently encountered security issue in writing tests is nonauthentic text submission: Test takers submit texts that are not their own but rather are copies of texts prepared by someone else. In this report, we propose AutoESD, a human-in-the-loop and automated system to detect nonauthentic texts for a large-scale writing tests, and report its…
Descriptors: Writing Tests, Automation, Cheating, Plagiarism
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Zheng, Lanqin; Long, Miaolang; Niu, Jiayu; Zhong, Lu – International Journal of Computer-Supported Collaborative Learning, 2023
Learning engagement has gained increasing attention in the field of education. Previous studies have adopted conventional methods to analyze learning engagement, but these methods cannot provide timely feedback for learners. This study analyzed automated group learning engagement via deep neural network models in a computer-supported collaborative…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Learner Engagement, Automation
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Inceoglu, Solène; Chen, Wen-Hsin; Lim, Hyojung – ReCALL, 2023
An increasing number of studies are exploring the benefits of automatic speech recognition (ASR)-based dictation programs for second language (L2) pronunciation learning (e.g. Chen, Inceoglu & Lim, 2020; Liakin, Cardoso & Liakina, 2015; McCrocklin, 2019), but how ASR recognizes accented speech and the nature of the feedback it provides to…
Descriptors: Second Language Learning, Intelligibility, Automation, Speech Communication
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Francisco Tigre Moura; Chiara Castrucci; Clare Hindley – Journal of Creative Behavior, 2023
This paper presents a study analyzing the perception of artistic products created by or with the support of artificial intelligence (AI). The research builds on previous studies revealing that the output of artificial creativity processes can indeed rival human-made products, satisfy consumer expectations, and derive enjoyment. However, in…
Descriptors: Creativity, Artificial Intelligence, Art, Automation
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Hanxiang Du; Wanli Xing; Bo Pei – Interactive Learning Environments, 2023
Participating in online communities has significant benefits to students learning in terms of students' motivation, persistence, and learning outcomes. However, maintaining and supporting online learning communities is very challenging and requires tremendous work. Automatic support is desirable in this situation. The purpose of this work is to…
Descriptors: Electronic Learning, Communities of Practice, Automation, Artificial Intelligence
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Ragheb Al-Ghezi; Katja Voskoboinik; Yaroslav Getman; Anna Von Zansen; Heini Kallio; Mikko Kurimo; Ari Huhta; Raili Hildén – Language Assessment Quarterly, 2023
The development of automated systems for evaluating spontaneous speech is desirable for L2 learning, as it can be used as a facilitating tool for self-regulated learning, language proficiency assessment, and teacher training programs. However, languages with fewer learners face challenges due to the scarcity of training data. Recent advancements…
Descriptors: Speech Tests, Automation, Artificial Intelligence, Finno Ugric Languages
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Rodrigues, Luiz; Toda, Armando M.; Oliveira, Wilk; Palomino, Paula Toledo; Vassileva, Julita; Isotani, Seiji – IEEE Transactions on Learning Technologies, 2022
Personalized gamification explores user models to tailor gamification designs to mitigate cases wherein the one-size-fits-all approach ineffectively improves learning outcomes. The tailoring process should simultaneously consider user and contextual characteristics (e.g., activity to be done and geographic location), which leads to several…
Descriptors: Automation, Game Based Learning, Individualized Instruction, Attitudes
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Yousef, Ahmed M.; Deliyski, Dimitar D.; Zacharias, Stephanie R. C.; de Alarcon, Alessandro; Orlikoff, Robert F.; Naghibolhosseini, Maryam – Journal of Speech, Language, and Hearing Research, 2022
Purpose: Voice disorders are best assessed by examining vocal fold dynamics in connected speech. This can be achieved using flexible laryngeal high-speed videoendoscopy (HSV), which enables us to study vocal fold mechanics with high temporal details. Analysis of vocal fold vibration using HSV requires accurate segmentation of the vocal fold edges.…
Descriptors: Voice Disorders, Speech, Video Technology, Equipment
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Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Rebecca L. Pharmer; Christopher D. Wickens; Benjamin A. Clegg – Cognitive Research: Principles and Implications, 2025
In two experiments, we examine how features of an imperfect automated decision aid influence compliance with the aid in a simplified, simulated nautical collision avoidance task. Experiment 1 examined the impact of providing transparency in the pre-task instructions regarding which attributes of the task that the aid uses to provide its…
Descriptors: Accountability, Automation, Compliance (Psychology), Task Analysis
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Konstantinos Gavriil; Ioannis Giannikos – Education Policy Analysis Archives, 2025
This paper presents a model for automatically selecting and allocating secondary education teachers to schools while considering various factors such as the diversity of sections and lessons, school distances, teacher specializations, teaching workloads, and other constraints. This poses a complex challenge that educational authorities in…
Descriptors: Foreign Countries, Secondary School Teachers, Teacher Placement, Teacher Distribution
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