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Direct linkNazanin Adhami; Mahboubeh Taghizadeh – Computer Assisted Language Learning, 2024
The objective of this study was twofold: (a) to determine the extent to which three types of instruction could improve writing performance of railway engineering students and (b) to explore students' perceptions of flipped classroom, Edmodo, and Google Docs for improving their academic writing performance. The participants were 61 undergraduate…
Descriptors: Foreign Countries, Transportation, Engineering Education, Writing Instruction
Zare, Javad; Karimpour, Sedigheh; Aqajani Delavar, Khadijeh – Computer Assisted Language Learning, 2023
The purpose of the present study was to investigate if following data-driven learning (DDL) to raise the learners' awareness of discourse organizers through concordancing improves their comprehension of English academic lectures. To address this issue, the current study adopted a quasi-experimental (comparison group, pretest-posttest) design. 96…
Descriptors: Classroom Communication, Discourse Analysis, Computational Linguistics, English for Academic Purposes
Chen, Hao-Jan Howard; Lai, Shu-Li; Lee, Ken-Yi; Yang, Christine Ting-Yu – Computer Assisted Language Learning, 2023
Knowledge of collocations is essential for English academic writing. However, there are few academic collocation referencing tools available and there is a pressing need to develop more. In this paper, we will introduce the ACOP (Academic Collocations and Phrases Search Engine), a newly developed corpus-based tool to search large academic corpora.…
Descriptors: Academic Language, English for Academic Purposes, Phrase Structure, Computational Linguistics
