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Showing all 11 results Save | Export
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Sijia Chen; Jan-Louis Kruger – Interpreter and Translator Trainer, 2024
Following a preliminary study that examined the potential effectiveness of a computer-assisted consecutive interpreting (CACI) mode, this paper presents a further trial of the CACI workflow. The workflow involves respeaking using speech recognition (SR) in phase I and production assisted by the SR text and its machine translation (MT) output in…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Translation, Speech Communication
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Chen, Siyu; Qiu, Shiying; Li, Haoran; Zhang, Junhua; Wu, Xiaoqi; Zeng, Wenjie; Huang, Fuquan – Education and Information Technologies, 2023
Artificially intelligent robots as teachers (AI teachers) have attracted extensive attention due to their potential to relieve the challenge of global teacher shortage and realize universal elementary education by 2030. Despite mass production of service robots and discussions about their educational applications, the study of full-fledged AI…
Descriptors: Artificial Intelligence, Robotics, Student Attitudes, Elementary School Students
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Ce Song – European Journal of Education, 2025
This study examines the role of AI-powered learning tools in influencing cognitive load, well-being and academic success among music education students, with a focus on technology acceptance as a key factor. Data were collected through a random sampling of 454 Chinese music students (192 males, 262 females) aged 18-24, with varying levels of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Music Education
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Shan Li; Zuer Liu; Mengling Qiu; Jiaxin Huang; Juan Zheng; Guozhu Ding – Journal of Educational Computing Research, 2024
Educational robots represent a unique form of teacher presence. Exploring how the communication features of robot instructors affect student learning experience could contribute to the advancement of educational robots. This study examined the impact of speech rate, voice type, and emotional tone of robots on students' cognitive load, attitudes…
Descriptors: Educational Technology, Technology Uses in Education, Cognitive Processes, Difficulty Level
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Dan Wang – International Review of Research in Open and Distributed Learning, 2024
This study examines the effects of corrective feedback (CF) on language learners' writing anxiety, writing complexity, fluency, and accuracy, and compares the effectiveness of feedback from human teachers with an AI-driven application called Poe. The study included three intact classes, each with 25 language learners. Using a quasi-experimental…
Descriptors: Artificial Intelligence, Feedback (Response), Anxiety, Foreign Countries
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Wan, Haipeng; Yu, Shengquan – Interactive Learning Environments, 2023
Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Mapping
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Özcan, Halil Ziya; Batur, Zekerya – International Journal of Education and Literacy Studies, 2021
Literacy is a term generally used for adults and young people. Basically, it is an acquisition that includes the process of reading, writing and understanding symbols in any language. While this concept, whose definition and scope has expanded over time, refers to people who can only say their names in the past, today it refers to individuals who…
Descriptors: Bibliometrics, Journal Articles, Difficulty Level, Reading Comprehension
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Miaomiao Liu; Yixun Li; Yongqiang Su; Hong Li – Scientific Studies of Reading, 2024
Purpose: This study sought to 1) identify linguistic features important for Chinese text complexity with a theory-based and systematic approach, and 2) address how feature sets and algorithms affect the performance of Chinese text complexity models. Method: Texts from Chinese language arts textbooks from Grades 1 to 6 (N = 1,478) in Mainland China…
Descriptors: Difficulty Level, Textbooks, Algorithms, Artificial Intelligence
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Yuchen Chen; Xinli Zhang; Lailin Hu – Educational Technology & Society, 2024
In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate…
Descriptors: Elementary School Students, Grade 5, Poetry, Artificial Intelligence
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Yun Dai; Ziyan Lin; Ang Liu; Wenlan Wang – British Journal of Educational Technology, 2024
While AI has become more prevalent in our society than ever, many young learners are found holding various naive, erroneous conceptions of AI due to the influence of their technology and media environments. To address this issue, this study seeks to propose a novel pedagogical solution to improve upper-elementary school students' scientific…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Education, Elementary School Students
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Ye, Lu; Yuan, Yuqing – Journal of Baltic Science Education, 2022
Non-cognitive factors are considered critical aspects in shaping students' academic achievement. This study aims to analyze and explore the mechanisms of the influence of noncognitive factors on 15-year-old students' abilities in China and the United States. Based on the Programme for International Student Assessment (PISA) 2018 education dataset,…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students