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Investigating L2 Grammatical Accuracy in Digital Multimodal Writing
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Assim S. Alrajhi – International Journal of Computer-Assisted Language Learning and Teaching, 2024
This study examines and compares L2 grammatical accuracy in digital multimodal writing (DMW) and monomodal text-based writing (TBW). Utilizing a mixed-methods design, the research incorporates a dataset comprising 180 written texts, a questionnaire, and text-based interviews. Sixty EFL learners were assigned to two groups (TBW and DMW) and…
Descriptors: Grammar, Accuracy, Writing Strategies, Comparative Analysis
Using Automatic Speech Recognition to Facilitate English Pronunciation Assessment and Learning in an EFL Context: Pronunciation Error Diagnosis and Pedagogical Implications
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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
Machine Learning Based Taxonomy and Analysis of English Learners' Translation Errors
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Qin, Ying – International Journal of Computer-Assisted Language Learning and Teaching, 2019
This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to obtain the computational evidences of translation error taxonomy. After manually revision, ten types of English to Chinese (E2C) and eight types…
Descriptors: Taxonomy, Translation, Computer Assisted Instruction, Second Language Learning