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Showing 1 to 15 of 18 results Save | Export
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Pasty Asamoah; John Serbe Marfo; Matilda Kokui Owusu-Bio; Daniel Zokpe – Education and Information Technologies, 2024
In this brief we shift the current academic integrity conversation from "detecting and preventing plagiarism" to "examining how plagiarized contents can be corrected with an objective knowledge of the number of words to modify and properly acknowledged". We proposed a simple, yet useful and powerful mathematical model that is…
Descriptors: Error Correction, Plagiarism, Integrity, Prevention
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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
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Miguel Blázquez-Carretero – ReCALL, 2023
In 2016, Lawley proposed an easy-to-build spellchecker specifically designed to help second language (L2) learners in their writing process by facilitating self-correction. The aim was to overcome the disadvantages to L2 learners posed by generic spellcheckers (GSC), such as that embedded in Microsoft Word. Drawbacks include autocorrection,…
Descriptors: Second Language Learning, Spanish, Spelling, Error Correction
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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
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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
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Woodworth, Johanathan; Barkaoui, Khaled – TESL Canada Journal, 2020
While feedback is widely considered essential for second language (L2) writing development (Bitchener & Ferris, 2012), teachers may not always be able to provide their learners with immediate and frequent corrective feedback. Automated writing evaluation (AWE) systems can help respond to this challenge by providing L2 learners with written…
Descriptors: Writing Evaluation, Feedback (Response), Error Correction, Second Language Instruction
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Brown, Neil C. C.; Altadmri, Amjad – ACM Transactions on Computing Education, 2017
Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much…
Descriptors: Novices, Programming Languages, Programming, Error Patterns
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Caputi, Peter; Chan, Amy; Jayasuriya, Rohan – British Journal of Educational Technology, 2011
This paper examined the impact of training strategies on the types of errors that novice users make when learning a commonly used spreadsheet application. Fifty participants were assigned to a counterfactual thinking training (CFT) strategy, an error management training strategy, or a combination of both strategies, and completed an easy task…
Descriptors: Spreadsheets, Training Methods, Transfer of Training, Student Evaluation
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Garousi, V. – IEEE Transactions on Education, 2010
Based on the demonstrated value of peer reviews in the engineering industry, numerous industry experts have listed it at the top of the list of desirable development practices. Experience has shown that problems (defects) are eliminated earlier if a development process incorporates peer reviews and that these reviews are as effective as or even…
Descriptors: Engineering, Industry, Quality Control, Computer Software
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Franco, Horacio; Bratt, Harry; Rossier, Romain; Rao Gadde, Venkata; Shriberg, Elizabeth; Abrash, Victor; Precoda, Kristin – Language Testing, 2010
SRI International's EduSpeak[R] system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to…
Descriptors: Feedback (Response), Sentences, Oral Language, Predictor Variables
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Chodorow, Martin; Gamon, Michael; Tetreault, Joel – Language Testing, 2010
In this paper, we describe and evaluate two state-of-the-art systems for identifying and correcting writing errors involving English articles and prepositions. Criterion[superscript SM], developed by Educational Testing Service, and "ESL Assistant", developed by Microsoft Research, both use machine learning techniques to build models of article…
Descriptors: Grammar, Feedback (Response), Form Classes (Languages), Second Language Learning
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Yeh, Shiou-Wen; Lo, Jia-Jiunn – Computers & Education, 2009
Giving feedback on second language (L2) writing is a challenging task. This research proposed an interactive environment for error correction and corrective feedback. First, we developed an online corrective feedback and error analysis system called "Online Annotator for EFL Writing". The system consisted of five facilities: Document Maker,…
Descriptors: Feedback (Response), Experimental Groups, Control Groups, College Freshmen
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Li, Kai; Akahori, Kanji – CALICO Journal, 2008
This paper describes the development and evaluation of a handwritten correction support system with audio and playback strokes used to teach Japanese writing. The study examined whether audio and playback strokes have a positive effect on students using honorific expressions in Japanese writing. The results showed that error feedback with audio…
Descriptors: Feedback (Response), Writing Skills, Japanese, Error Correction
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Simon, Beth; Bouvier, Dennis; Chen, Tzu-Yi; Lewandowski, Gary; McCartney, Robert; Sanders, Kate – Computer Science Education, 2008
We report on responses to a series of four questions designed to identify pre-existing abilities related to debugging and troubleshooting experiences of novice students before they begin programming instruction. The focus of these questions include general troubleshooting, bug location, exploring unfamiliar environments, and describing students'…
Descriptors: Troubleshooting, Teaching Methods, Computer Science Education, Programming
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Fischer, Robert – Computer Assisted Language Learning, 2007
This article presents a survey of computer-based tracking in CALL and the uses to which the analysis of tracking data can be put to address questions in CALL in particular and second language acquisition (SLA) in general. Adopting both quantitative and qualitative methods, researchers have found that students often use software in unexpected ways,…
Descriptors: Computer Mediated Communication, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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