Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 5 |
Descriptor
Source
Computer Assisted Language… | 5 |
Author
Chang, Jason S. | 1 |
Chang, Yu-Chia | 1 |
Chen, Hao-Jan | 1 |
Chukharev-Hudilainen, Evgeny | 1 |
Goh, Tiong-Thye | 1 |
Huang, Ping-Yu | 1 |
Katushemererwe, Fridah | 1 |
Liou, Hsien-Chin | 1 |
Nerbonne, John | 1 |
Saricaoglu, Aysel | 1 |
Sun, Hui | 1 |
More ▼ |
Publication Type
Journal Articles | 5 |
Reports - Research | 3 |
Reports - Descriptive | 2 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Dale Chall Readability Formula | 1 |
Flesch Kincaid Grade Level… | 1 |
Flesch Reading Ease Formula | 1 |
SAT (College Admission Test) | 1 |
What Works Clearinghouse Rating
Huang, Ping-Yu; Tsao, Nai-Lung – Computer Assisted Language Learning, 2021
In this article, we describe an online English collocation explorer developed to help English L2 learners produce correct and appropriate collocations. Our tool, which is able to visually represent relevant correct/incorrect collocations on a single webpage, was designed based on the notions of collocation clusters and intercollocability proposed…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Error Correction
Goh, Tiong-Thye; Sun, Hui; Yang, Bing – Computer Assisted Language Learning, 2020
This study investigates the extent to which microfeatures -- such as basic text features, readability, cohesion, and lexical diversity based on specific word lists -- affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268…
Descriptors: Essays, Writing Tests, English (Second Language), Second Language Learning
Katushemererwe, Fridah; Nerbonne, John – Computer Assisted Language Learning, 2015
This study presents the results from a computer-assisted language learning (CALL) system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system…
Descriptors: Computer Assisted Instruction, Native Language Instruction, Grammar, Language Maintenance
Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
Chang, Yu-Chia; Chang, Jason S.; Chen, Hao-Jan; Liou, Hsien-Chin – Computer Assisted Language Learning, 2008
Previous work in the literature reveals that EFL learners were deficient in collocations that are a hallmark of near native fluency in learner's writing. Among different types of collocations, the verb-noun (V-N) one was found to be particularly difficult to master, and learners' first language was also found to heavily influence their collocation…
Descriptors: Sentence Structure, Verbs, Nouns, Foreign Countries