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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
Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Lin, Pei-Hsin – Computer Assisted Language Learning, 2021
Remote association requires players to use their mental transformation to identify objects' relationships by activating knowledge application. A Chinese Remote Association game was designed (example question: [characters omitted], where the answer is [character omitted]) to explore learners' cognitive and affective effects, and then eighth grade…
Descriptors: Computer Games, Grade 8, Telecommunications, Handheld Devices
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)
Hsu, Liwei – Computer Assisted Language Learning, 2016
This study aims to explore the structural relationships among the variables of EFL (English as a foreign language) learners' perceptual learning styles and Technology Acceptance Model (TAM). Three hundred and forty-one (n = 341) EFL learners were invited to join a self-regulated English pronunciation training program through automatic speech…
Descriptors: Pronunciation, Pronunciation Instruction, Cognitive Style, Statistical Analysis
Lai, Chun; Hu, Xiao; Lyu, Boning – Computer Assisted Language Learning, 2018
Out-of-class learning with technology comprises an essential context of second language development. Understanding the nature of out-of-class language learning with technology is the initial step towards safeguarding its quality. This study examined the types of learning experiences that language learners engaged in outside the classroom and the…
Descriptors: Second Language Learning, Learning Experience, Incentives, Interviews
Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Lin, Pei-Hsin – Computer Assisted Language Learning, 2017
Students of Southeast Asian Heritage Learning Chinese (SSAHLC) in Taiwan have frequently demonstrated difficulty with traditional Chinese (a graphical character) radical recognition due to their limited exposure to the written language form since childhood. In this study, we designed a Chinese radical learning game (CRLG), which adopted a drill…
Descriptors: Motivation, Electronic Learning, Self Efficacy, Academic Achievement
Vandewaetere, M.; Desmet, P. – Computer Assisted Language Learning, 2009
The great majority of questionnaires measuring non-observable constructs such as attitude towards CALL are often developed from a specific point of view and are seldom followed by psychometrical validation. Psychometrical properties of the questionnaire, such as construct validity and reliability, then remain unanswered too often, laying a heavy…
Descriptors: Computer Assisted Instruction, Construct Validity, Psychometrics, Second Language Learning

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