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Showing 1 to 15 of 27 results Save | Export
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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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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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Monica Tatasciore; Luke Strickland; Shayne Loft – Cognitive Research: Principles and Implications, 2024
Increased automation transparency can improve the accuracy of automation use but can lead to increased bias towards agreeing with advice. Information about the automation's confidence in its advice may also increase the predictability of automation errors. We examined the effects of providing automation transparency, automation confidence…
Descriptors: Automation, Access to Information, Information Technology, Bias
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Monika Lohani; Joel M. Cooper; Amy S. McDonnell; Gus G. Erickson; Trent G. Simmons; Amanda E. Carriero; Kaedyn W. Crabtree; David L. Strayer – Cognitive Research: Principles and Implications, 2024
The reliability of cognitive demand measures in controlled laboratory settings is well-documented; however, limited research has directly established their stability under real-life and high-stakes conditions, such as operating automated technology on actual highways. Partially automated vehicles have advanced to become an everyday mode of…
Descriptors: Cognitive Processes, Difficulty Level, Automation, Psychophysiology
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Xu Chen; Di Wu – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) is widely recognized as one of the most influential technologies for the future, having sparked a paradigm shift in scientific research. The field of education has also been greatly impacted by this transformative technology, with researchers exploring the applications of generative AI, particularly ChatGPT,…
Descriptors: Automation, Multimedia Materials, Instructional Materials, Artificial Intelligence
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Jiang, Michael Yi-Chao; Jong, Morris Siu-Yung; Lau, Wilfred Wing-Fat; Chai, Ching-Sing; Wu, Na – Journal of Computer Assisted Learning, 2023
Background: While automatic speech recognition (ASR) is increasingly used for commercial purposes, its influence on the learners' linguistic performance in terms of oral complexity, accuracy and fluency was under-explored. To date, few studies have been conducted to investigate how the dictation ASR technology could be incorporated into language…
Descriptors: Speech Communication, Automation, Accuracy, Language Fluency
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Malakul, Sivakorn; Park, Innwoo – Smart Learning Environments, 2023
While subtitles are considered a primary learning support tool for people who cannot understand video narration in foreign languages, recent advancements in artificial intelligence (AI) technologies have played a pivotal role in automatic subtitling on online video platforms such as YouTube. This study examines the effects of three different types…
Descriptors: Captions, Automation, Video Technology, Secondary School Students
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Wu-Yuin Hwang; Ika Qutsiati Utami – Education and Information Technologies, 2024
Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Mathematics Education, Word Problems (Mathematics)
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Li Dong – Reading and Writing: An Interdisciplinary Journal, 2024
Within the context of Chinese university education, effective communication in the field of second language writing heavily relies on lexical complexity, yet the role of writing feedback perception in relation to lexical complexity remains elusive. This study introduces a comprehensive writing feedback perception model encompassing perceptions of…
Descriptors: Foreign Countries, College Students, Feedback (Response), Writing Instruction
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Ajabshir, Zahra Fakher; Ebadi, Saman – Asian-Pacific Journal of Second and Foreign Language Education, 2023
This study investigates the effects of teacher-focused feedback (TF) and automatic writing evaluation (AWE) on global writing performance as well as syntactic complexity, accuracy, lexical diversity, and fluency (CALF) of English as a foreign language (EFL) learners' narrative and argumentative writings. The participants were randomly assigned to…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Syntax
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Boehm, Udo; Matzke, Dora; Gretton, Matthew; Castro, Spencer; Cooper, Joel; Skinner, Michael; Strayer, David; Heathcote, Andrew – Cognitive Research: Principles and Implications, 2021
Human operators often experience large fluctuations in cognitive workload over seconds timescales that can lead to sub-optimal performance, ranging from overload to neglect. Adaptive automation could potentially address this issue, but to do so it needs to be aware of real-time changes in operators' spare cognitive capacity, so it can provide help…
Descriptors: Prediction, Cognitive Processes, Difficulty Level, Automation
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Qian, Leyi; Yang, Yong; Zhao, Yali – Reading and Writing: An Interdisciplinary Journal, 2021
This study aims to explore to what extent syntactic complexity predicts holistic scores generated by China's two prominent automated writing evaluation systems--"pigai" and "iWrite," the results of which will have some implications for the validity of these two systems. In the meanwhile, this study targets how syntactic…
Descriptors: Foreign Countries, Syntax, Difficulty Level, Scores
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Fengkai Liu; Yishi Jiang; Chun Lai; Tan Jin – Language Learning & Technology, 2024
Differentiated instruction is much demanded yet quite challenging in face of the growing student diversity in today's K-12 classrooms. One major challenge is the provision of differentiated materials to students. Automated text simplification (ATS) tools fueled by natural language processing may serve as a useful assistant for teachers. However,…
Descriptors: Automation, Individualized Instruction, Natural Language Processing, Technology Uses in Education
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Xizhe Wang; Yihua Zhong; Changqin Huang; Xiaodi Huang – IEEE Transactions on Learning Technologies, 2024
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Synchronous Communication
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Ayfer Sayin; Sabiha Bozdag; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The purpose of this study is to generate non-verbal items for a visual reasoning test using templated-based automatic item generation (AIG). The fundamental research method involved following the three stages of template-based AIG. An item from the 2016 4th-grade entrance exam of the Science and Art Center (known as BILSEM) was chosen as the…
Descriptors: Test Items, Test Format, Nonverbal Tests, Visual Measures
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