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Christopher Saarna – International Journal of Technology in Education, 2024
This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays…
Descriptors: Identification, Artificial Intelligence, Computer Software, Grammar
Tim Vandenhoek – International Journal of Education and Development using Information and Communication Technology, 2023
Plagiarism in academic writing is known to be an issue of concern for educators, administrators, and students alike. Using self-reporting studies and plagiarism detection software, previous research has established that plagiarism in university-level academic writing is relatively common amongst the work of L1 and particularly L2 writers and that…
Descriptors: Plagiarism, Writing (Composition), College Students, Virtual Classrooms
Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
Dizon, Gilbert; Gayed, John M. – JALT CALL Journal, 2021
While the use of automated writing evaluation software has received much attention in CALL literature, as Frankenberg-Garcia (2019) notes, empirical research on predictive text and intelligent writing assistants is lacking. Thus, this study addressed this gap in the literature by examining the impact of Grammarly, an intelligent writing assistant…
Descriptors: Foreign Countries, College Students, Writing Evaluation, Computer Software
Blake, John – RELC Journal: A Journal of Language Teaching and Research, 2020
A purpose-built online error detection tool was developed to provide genre-specific corpus-based feedback on errors occurring in draft research articles and graduation theses. The primary envisaged users were computer science majors studying at a public university in Japan. This article discusses the development and evaluation of this interactive,…
Descriptors: Feedback (Response), Usability, Error Analysis (Language), Computational Linguistics
Daniels, Paul; Iwago, Koji – JALT CALL Journal, 2017
As online automatic speech recognition (ASR) engines become more accurate and more widely implemented with call software, it becomes important to evaluate the effectiveness and the accuracy of these recognition engines using authentic speech samples. This study investigates two of the most prominent cloud-based speech recognition engines--Apple's…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Computer Software
Shintani, Natsuko; Aubrey, Scott – Modern Language Journal, 2016
This study extends research on written corrective feedback (CF) by investigating how timing of CF affects grammar acquisition. Specifically, it examined the relative effects of synchronous and asynchronous CF on the accurate use of the hypothetical conditional structure. Participants were 68 intermediate-level students of English at a university…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
Ashwell, Tim; Elam, Jesse R. – JALT CALL Journal, 2017
The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Language Tests

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