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Godwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
Wu, Yi-ju – Language Learning & Technology, 2021
Adopting the approaches of "pattern hunting" and "pattern refining" (Kennedy & Miceli, 2001, 2010, 2017), this study investigates how seven freshman English students from Taiwan used the Corpus of Contemporary American English to discover collocation patterns for 30 near-synonymous change-of-state verbs and new ideas about…
Descriptors: Phrase Structure, Teaching Methods, Second Language Learning, Second Language Instruction
Shi, Zhan; Liu, Fengkai; Lai, Chun; Jin, Tan – Language Learning & Technology, 2022
Automated Writing Evaluation (AWE) systems have been found to enhance the accuracy, readability, and cohesion of writing responses (Stevenson & Phakiti, 2019). Previous research indicates that individual learners may have difficulty utilizing content-based AWE feedback and collaborative processing of feedback might help to cope with this…
Descriptors: Writing Instruction, Writing Evaluation, Feedback (Response), Accuracy
Matthews, Joshua; Wijeyewardene, Ingrid – Language Learning & Technology, 2018
Despite the current potential to use computers to automatically generate a large range of text-based indices, many issues remain unresolved about how to apply these data in established language teaching and assessment contexts. One way to resolve these issues is to explore the degree to which automatically generated indices, which are reflective…
Descriptors: Correlation, Robotics, Second Language Learning, Second Language Instruction
Cotos, Elena; Link, Stephanie; Huffman, Sarah – Language Learning & Technology, 2017
To better understand the promising effects of data-driven learning (DDL) on language learning processes and outcomes, this study explored DDL learning events enabled by the Research Writing Tutor (RWT), a web-based platform containing an English language corpus annotated to enhance rhetorical input, a concordancer that was searchable for…
Descriptors: Data, Computer Assisted Instruction, Mixed Methods Research, Graduate Students
Cowan, Ron; Choo, Jinhee; Lee, Gabseon Sunny – Language Learning & Technology, 2014
This study illustrates how a synergy of two technologies--Intelligent Computer-Assisted Language Learning (ICALL) and corpus linguistic analysis--can produce a lasting improvement in L2 learners' ability to edit persistent grammatical errors from their writing. A large written English corpus produced by Korean undergraduate and graduate students…
Descriptors: Computational Linguistics, Computer Assisted Instruction, Second Language Instruction, Second Language Learning
Kennedy, Claire; Miceli, Tiziana – Language Learning & Technology, 2010
In much of the literature on the exploitation of corpora for language learning, the learners are viewed as researchers, who formulate and test their own hypotheses about language use. Having identified difficulties encountered in corpus investigations by our intermediate-level students of Italian in a previous study, we have designed a…
Descriptors: Computational Linguistics, Second Language Learning, Language Usage, Italian
Yoon, Hyunsook – Language Learning & Technology, 2008
This paper reports on a qualitative study that investigated the changes in students' writing process associated with corpus use over an extended period of time. The primary purpose of this study was to examine how corpus technology affects students' development of competence as second language (L2) writers. The research was mainly based on case…
Descriptors: Metalinguistics, Writing Processes, Writing Instruction, English for Academic Purposes