Publication Date
In 2025 | 1 |
Since 2024 | 8 |
Since 2021 (last 5 years) | 28 |
Since 2016 (last 10 years) | 51 |
Since 2006 (last 20 years) | 69 |
Descriptor
Computer Software | 73 |
Error Correction | 73 |
Teaching Methods | 73 |
Second Language Learning | 47 |
Second Language Instruction | 44 |
Feedback (Response) | 40 |
English (Second Language) | 37 |
Foreign Countries | 31 |
Computer Assisted Instruction | 18 |
Writing Instruction | 18 |
Computational Linguistics | 17 |
More ▼ |
Source
Author
Lewandowski, Gary | 3 |
Simon, Beth | 3 |
Chukharev-Hudilainen, Evgeny | 2 |
Fitzgerald, Sue | 2 |
McCauley, Renee | 2 |
Mohsen, Mohammed Ali | 2 |
Murphy, Laurie | 2 |
Thomas, Lynda | 2 |
Zander, Carol | 2 |
AbuSeileek, A. F. | 1 |
Ades, Tal | 1 |
More ▼ |
Publication Type
Education Level
Higher Education | 44 |
Postsecondary Education | 32 |
Secondary Education | 7 |
Elementary Education | 6 |
High Schools | 5 |
Middle Schools | 5 |
Junior High Schools | 4 |
Early Childhood Education | 2 |
Adult Education | 1 |
Grade 4 | 1 |
Grade 7 | 1 |
More ▼ |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Test of English for… | 2 |
Flesch Kincaid Grade Level… | 1 |
Test of English as a Foreign… | 1 |
What Works Clearinghouse Rating
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
Pham Sy Nam; Ngoc-Giang Nguyen; Hoa Anh Tuong; Ben Haas; Zsolt Lavicza; Yves Kreis – International Journal for Technology in Mathematics Education, 2023
Problem-based learning puts students in situations that suggest problems without providing instructions and available knowledge. Therefore, when using problem-based learning, students need to be flexible, self-disciplined, active and self-occupied with knowledge and turn the knowledge the teacher intends to impart into their knowledge. For locus…
Descriptors: Computer Software, Mathematics Instruction, Teaching Methods, Problem Based Learning
Wen Liu – Language Teaching Research Quarterly, 2024
Automated writing evaluation feedback (AWE) has become popular in writing classrooms. However, few studies have conducted a comprehensive review of the employment of AWE in learning areas. This study aimed to provide a systematic review of the current research on AWE feedback, including its validity, effects, and students' engagement with AWE…
Descriptors: Writing Instruction, Learner Engagement, Feedback (Response), Teaching Methods
Zeng, Mini; Zhu, Feng – Journal of Cybersecurity Education, Research and Practice, 2021
Software vulnerabilities have become a severe cybersecurity issue. There are numerous resources of industry best practices available, but it is still challenging to effectively teach secure coding practices. The resources are not designed for classroom usage because the amount of information is overwhelming for students. There are efforts in…
Descriptors: Computer Software, Coding, Computer Security, Computer Science Education
Elsayed Issa; Gus Hahn-Powell – Language Learning & Technology, 2025
This study investigates the effectiveness of a computer-assisted pronunciation training (CAPT) system on second language learners' acquisition of three grammatical features. It presents a CAPT system on top of a phoneme-based, fine-tuned speech recognition model, and is intended to deliver explicit, corrective feedback on the pronunciation of the…
Descriptors: Grammar, Computer Assisted Instruction, Arabic, Second Language Instruction
Phung, Tung; Cambronero, José; Gulwani, Sumit; Kohn, Tobias; Majumdarm, Rupak; Singla, Adish; Soares, Gustavo – International Educational Data Mining Society, 2023
Large language models (LLMs), such as Codex, hold great promise in enhancing programming education by automatically generating feedback for students. We investigate using LLMs to generate feedback for fixing syntax errors in Python programs, a key scenario in introductory programming. More concretely, given a student's buggy program, our goal is…
Descriptors: Computational Linguistics, Feedback (Response), Programming, Computer Science Education
Rakhun Kim – Language Learning & Technology, 2024
This study investigated the instructional effects of learner uptake following automatic corrective recast from artificial intelligence (AI) chatbots on the learning of the English caused-motion construction. 69 novice-level EFL learners in a Korean high school were recruited to investigate the instructional effects of corrective recast from AI…
Descriptors: Artificial Intelligence, Error Correction, Second Language Learning, Second Language Instruction
Adriana Guanuche; Osana Eiriz; Roberto Espi – International Association for Development of the Information Society, 2023
The increasing technological development of computers, tablets and smartphones has enabled a rapid increase in the adoption of mobile technology for language teaching and learning, and numerous applications that provide easy access for any learner without limitations of place and time have been developed. This paper shows the study of grammatical…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Telecommunications
Süleyman Emre Aktas; Çaglar Naci Hidiroglu – Journal of Pedagogical Research, 2024
The study aims to investigate prospective middle school mathematics teachers' mental actions related to debugging, which is one of the computational thinking skills in the modeling process. The study was conducted with a single-case embedded model. The collaborative working group consisted of three prospective mathematics teachers selected by…
Descriptors: Preservice Teachers, Mathematics Teachers, Mathematical Models, Mathematics Instruction
Kuo, Yu-Chen; Chen, Yun-An – Education and Information Technologies, 2023
With the development of science and technology, the demand for programmers has increased. However, learning computer programs is not an easy task. It might cause a significant impact on programming if misconceptions exist at the beginning of the study. Hence, it is important to discover and correct them immediately. Chatbots are effective teaching…
Descriptors: Programming, Artificial Intelligence, Computer Science Education, Misconceptions
Shabnam Behzad – ProQuest LLC, 2024
Second language learners constitute a significant and expanding portion of the global population and there is a growing demand for tools that facilitate language learning and instruction across various levels and in different countries. The development of large language models (LLMs) has brought about a significant impact on the domains of natural…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Second Language Learning
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
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
Murphy, Bridget; Mackay, Jessica; Tragant, Elsa – Language Learning Journal, 2023
Given the prominence of online teaching over the last few years, mobile instant messaging (MIM) has grown in importance for students studying English outside of class. Applications like WhatsApp have the potential to provide language learners the opportunity to practise communicative strategies while receiving feedback from a teacher. To explore…
Descriptors: Second Language Learning, Second Language Instruction, Error Correction, Feedback (Response)
Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software