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Qi Wang; Shengquan Yu; Xiaofeng Wang – Journal of Educational Computing Research, 2024
Chinese as a second language (CSL) learning has attracted more attention and supporting learners with adaptive resources becomes difficult. Some online systems recommended pre-designed resources from existing databases while the resources could not match learners' context. Designing resources dynamically according to learners' needs could be a…
Descriptors: Second Language Learning, Chinese, College Students, Online Systems
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Li, Xu; Ouyang, Fan; Chen, WenZhi – Journal of Computing in Higher Education, 2022
Group formation is a critical factor which influences collaborative processes and performances in computer-supported collaborative learning (CSCL). Automatic grouping has been widely used to generate groups with heterogeneous attributes and to maximize the diversity of students' characteristics within a group. But there are two dominant challenges…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Group Dynamics, Grouping (Instructional Purposes)
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Aydin, Gökhan; Duran, Volkan; Mertol, Hüseyin – International Journal of Curriculum and Instruction, 2021
This study aims to develop a computer program for the identification key to insect orders (Arthropoda: Hexapoda) and to investigate its effectiveness as teaching material. Secondly, this study is aiming at whether this program improves students' computational thinking skills or not longitudinal quasi-experimental design. Firstly, the study is…
Descriptors: Computer Software, Identification, Entomology, Computation
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Long Li; Mira Kim – Australasian Journal of Educational Technology, 2024
This paper explores international students' engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students' critical engagement with them for independent learning remains under-researched. The study primarily…
Descriptors: Feedback (Response), Automation, English Language Learners, English (Second Language)
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Lämsä, Joni; Uribe, Pablo; Jiménez, Abelino; Caballero, Daniela; Hämäläinen, Raija; Araya, Roberto – Journal of Learning Analytics, 2021
Scholars have applied automatic content analysis to study computer-mediated communication in computer-supported collaborative learning (CSCL). Since CSCL also takes place in face-to-face interactions, we studied the automatic coding accuracy of manually transcribed face-to-face communication. We conducted our study in an authentic higher-education…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Synchronous Communication, Learning Analytics
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Li, Rui – SAGE Open, 2021
Despite the growing attention being paid to the use of Automated Writing Evaluation (AWE) in China, it is still uncertain what factors lie behind EFL (English-as-a-foreign-language) learners' continuance intention to use it. To this end, by adding two external factors (i.e., computer self-efficacy and perceived ease of use) to the expectation…
Descriptors: Intention, Persistence, Automation, Computer Assisted Instruction
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Evers, Katerina; Chen, Sufen – Computer Assisted Language Learning, 2022
This study examined the difference in adults' pronunciation performance with peer feedback and individual practice when using an automatic speech recognition (ASR) system. The same ASR software was used in both the comparison (n = 31) and the experimental group (n = 33) for 12 weeks. The participants were working adults in Taiwan. During the…
Descriptors: Automation, Computer Assisted Instruction, Speech Communication, Peer Evaluation
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Li, Rui; Meng, Zhaokun; Tian, Mi; Zhang, Zhiyi; Ni, Chuanbin; Xiao, Wei – Computer Assisted Language Learning, 2019
Automated Writing Evaluation (AWE) has been widely applied in computer-assisted language learning (CALL) in China. However, little is known about factors that influence learners' intention to use AWE. To this end, by adding two external factors (i.e. computer self-efficacy and computer anxiety) to the technology acceptance model (TAM), we surveyed…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Automation
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Diachenko, Alla V.; Morgunov, Boris P.; Melnyk, Tetiana P.; Kravchenko, Olena I.; Zubchenko, Ludmila V. – International Journal of Higher Education, 2019
The "purpose" of this study was to find out how students and teachers perceive the automation of the specialists' professional training process and the impact factors of perceiving the learning activity of such kind by students and faculty. The experimental model of automated learning was based on an express course in the academic…
Descriptors: Automation, Teacher Attitudes, Student Attitudes, Legal Education (Professions)
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Xiao, Wenqi; Park, Moonyoung – International Journal of Computer-Assisted Language Learning and Teaching, 2021
With the advancement of automatic speech recognition (ASR) technology, ASR-based pronunciation assessment can diagnose learners' pronunciation problems. Meanwhile, ASR-based pronunciation training allows more opportunities for pronunciation practice. This study aims to investigate the effectiveness of ASR technology in diagnosing English…
Descriptors: Automation, Computer Software, Handheld Devices, Diagnostic Tests
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Evers, Katerina; Chen, Sufen – Journal of Educational Computing Research, 2021
This study investigated how learning styles (visual/verbal) and the use of Automatic Speech Recognition (ASR) software affect English as a Second Language adult learners' improvement during a 12-week course focusing on pronunciation. In the control group (n = 28), the teacher corrected and gave feedback on the adult learners' pronunciation;…
Descriptors: Automation, Computer Assisted Instruction, Computer Software, Pronunciation Instruction
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Lee, Cynthia – Computer Assisted Language Learning, 2020
The aim of this article is to reveal the ways in which six 14- to 15-year-old second language (L2) learners, two each of high, mid, and low English proficiency levels were cognitively engaged in writing while using an automated content feedback program known as the Essay Critiquing System 2.0 in three out of five workshops in a Hong Kong secondary…
Descriptors: Adolescents, Automation, Feedback (Response), Computer Assisted Instruction
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Bayne, Sian – Teaching in Higher Education, 2015
Promises of "teacher-light" tuition and of enhanced "efficiency" via the automation of teaching have been with us since the early days of digital education, sometimes embraced by academics and institutions, and sometimes resisted as a set of moves which are damaging to teacher professionalism and to the humanistic values of…
Descriptors: Foreign Countries, Higher Education, Online Courses, Group Instruction
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Sato, Takeshi; Ogura, Masa'aki; Aota, Shoma; Burden, Tyler – Research-publishing.net, 2018
This study examines the effectiveness of an automated translation chatbot used in online interactions which consequently could enhance second/foreign language (L2) competence. Based on the sociocultural perspectives of learning, such as communication to recognize the difference from others and to be involved in sense-making processes, this study…
Descriptors: Automation, Computer Mediated Communication, Educational Technology, Computer Assisted Instruction
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Fernandez Aleman, J. L. – IEEE Transactions on Education, 2011
Automated assessment systems can be useful for both students and instructors. Ranking and immediate feedback can have a strongly positive effect on student learning. This paper presents an experience using automatic assessment in a programming tools course. The proposal aims at extending the traditional use of an online judging system with a…
Descriptors: Programming, Computer Science Education, College Students, Student Evaluation
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