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Asma Almusharraf; Daniel Bailey – Computer Assisted Language Learning, 2025
Machine translation (MT) practice and activity development in education are possible when students with diverse backgrounds contribute to helping define how MT can best be used for language learning. This study employed a questionnaire based on an adapted version of the technology acceptance model (TAM) to gain perspective on the perceptions,…
Descriptors: Web Sites, Student Attitudes, Language Proficiency, Second Language Learning
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Zhai, Na; Ma, Xiaomei – Computer Assisted Language Learning, 2022
Automated writing evaluation (AWE) has been used increasingly to provide feedback on student writing. Previous research typically focused on its inter-rater reliability with human graders and validation frameworks. The limited body of research has only discussed students' attitudes or perceptions in general. A systematic investigation of the…
Descriptors: Automation, Writing Evaluation, Feedback (Response), College Students
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Sun, Peijian Paul; Mei, Bing – Computer Assisted Language Learning, 2022
This study focuses on preservice Chinese-as-a-second/foreign-language (L2 Chinese) teachers with a theoretical perspective based on prior technology acceptance research in the educational context, to investigate factors influencing preservice L2 Chinese teachers' intention to use educational technology in their future classrooms. Six relevant…
Descriptors: Chinese, Second Language Instruction, Preservice Teachers, Language Teachers
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Bin Zou; Qinglang Lyu; Yining Han; Zijing Li; Weilei Zhang – Computer Assisted Language Learning, 2025
Adapted from the Technology Acceptance Model (TAM), the Integrated Model of Technology Acceptance (IMTA) has been used to examine the perceptions and acceptance of computer-assisted language learning (CALL), such as online learning, mobile learning, and learning management systems. However, whether IMTA can be applied to empirical research on…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
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Zhang, Danyang; Pérez-Paredes, Pascual – Computer Assisted Language Learning, 2021
Despite the increasing ownership of mobile devices among Chinese postgraduate EFL learners, relevant studies regarding mobile English learning resources (MELR) use by postgraduate learners are still lacking. This study tries to understand the uses and the motivation behind language learners' selection of MALL resources. In this research, 95…
Descriptors: Graduate Students, Handheld Devices, Telecommunications, Second Language Learning
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Rafiee, Marzieh; Abbasian-Naghneh, Salman – Computer Assisted Language Learning, 2021
In recent decades, the rapid advances in technology have led many researchers to investigate the factors influencing its successful implementation in different fields. The current study, hence, aimed to identify the factors affecting e-learning acceptance and readiness in the context of foreign language learning. By reviewing the related…
Descriptors: Electronic Learning, Models, Technology Integration, Readiness
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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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Bai, Barry; Wang, Jing; Zhou, Huixuan – Computer Assisted Language Learning, 2022
The present study reports on the effects of a self-regulated (SRL) writing strategy-based intervention supported with e-learning tools on SRL strategy use in English writing with 468 Hong Kong primary school students. The changes to the students' motivation in English writing, and their e-learning acceptance were also measured. The study adopted a…
Descriptors: Metacognition, Writing Instruction, Elementary School Students, Intervention
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Bai, Barry; Wang, Jing; Chai, Ching-Sing – Computer Assisted Language Learning, 2021
There has been an increasing concern on teachers' adoption of information and communication technology (ICT) in their teaching practices. However, little has been explored about English as a second language (ESL) teachers' ICT adoption. This study synthesizes the technology acceptance model (TAM), the value-expectancy theory, and a learning…
Descriptors: Elementary School Teachers, Second Language Learning, Second Language Instruction, English (Second Language)
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García Botero, Gustavo; Questier, Frederik; Zhu, Chang – Computer Assisted Language Learning, 2019
Can mobile-assisted language learning (MALL) foster self-directed learning outside the classroom? This article examines informal, out-of-class engagement with a MALL tool: Duolingo. After being invited to use Duolingo, 118 higher education language students agreed to have their activity in the application tracked. In addition to the data collected…
Descriptors: Telecommunications, Handheld Devices, College Students, Educational Technology
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Liu, Haixia; Lin, Chin-Hsi; Zhang, Dongbo – Computer Assisted Language Learning, 2017
Though pedagogical beliefs have been identified as critical factors in the success of technology integration, very few studies have included them in technology-adoption models. The present study revises the Technology Acceptance Model (TAM) by adding teachers' pedagogical beliefs, and tests the revised model among university-level…
Descriptors: Beliefs, Information Technology, Teacher Attitudes, Language Teachers
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Cárdenas-Claros, Mónica Stella – Computer Assisted Language Learning, 2015
This paper reports on the findings of two qualitative exploratory studies that sought to investigate design features of help options in computer-based L2 listening materials. Informed by principles of participatory design, language learners, software designers, language teachers, and a computer programmer worked collaboratively in a series of…
Descriptors: Second Language Learning, Qualitative Research, Listening Skills, Computer Assisted Instruction
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Jin, Li – Computer Assisted Language Learning, 2018
Different from the traditional term language input, affordance, an ecological term, has been deployed to analyze the perceived opportunities for second language (L2) learning an environment provides to L2 learners. L2 learning occurs only when the semiotic resources in the environment resonate with the learner's capacities such as their abilities,…
Descriptors: Chinese, Second Language Learning, Educational Environment, Linguistic Input
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Yu, Ping; Pan, Yingxin; Li, Chen; Zhang, Zengxiu; Shi, Qin; Chu, Wenpei; Liu, Mingzhuo; Zhu, Zhiting – Computer Assisted Language Learning, 2016
Oral production is an important part in English learning. Lack of a language environment with efficient instruction and feedback is a big issue for non-native speakers' English spoken skill improvement. A computer-assisted language learning system can provide many potential benefits to language learners. It allows adequate instructions and instant…
Descriptors: English (Second Language), Foreign Countries, Second Language Instruction, Computer Assisted Instruction
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Roy, Debopriyo; Brine, John; Murasawa, Fuyuki – Computer Assisted Language Learning, 2016
The act of note-taking offloads cognitive pressure and note-taking applications could be used as an important tool for foreign language acquisition. Its use, importance, and efficacy in a foreign language learning context could be justifiably debated. However, existing computer-assisted language learning literature is almost silent on the topic.…
Descriptors: Foreign Countries, Usability, English (Second Language), Second Language Learning
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