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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
Vakili, Shokoufeh; Ebadi, Saman – Computer Assisted Language Learning, 2022
Theoretically grounded in Vygotsky's sociocultural theory of mind, Dynamic Assessment (DA) provides researchers with the opportunity to investigate different aspects of learners' developmental trajectory, including the ways they overcome their errors. As a qualitative inquiry into the nature of errors reflecting learners' development in academic…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Testing
Bailey, Daniel; Lee, Andrea Rakushin – TESOL International Journal, 2020
Different genres of writing entail various levels of syntactic and lexical complexity, and how this complexity influences the results of Automatic Writing Evaluation (AWE) programs like Grammarly in second language (L2) writing is unknown. This study explored the use of Grammarly in the L2 writing context by comparing error frequency, error types…
Descriptors: Grammar, Computer Assisted Instruction, Error Correction, Feedback (Response)
Grimaldi, Phillip J.; Karpicke, Jeffrey D. – Journal of Educational Psychology, 2014
Retrieval practice is a powerful way to promote long-term retention and meaningful learning. However, students do not frequently practice retrieval on their own, and when they do, they have difficulty evaluating the correctness of their responses and making effective study choices. To address these problems, we have developed a guided retrieval…
Descriptors: Information Retrieval, Computer Assisted Instruction, Electronic Learning, Evaluation Methods
Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes – Research-publishing.net, 2014
We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…
Descriptors: German, Second Language Learning, Second Language Instruction, Feedback (Response)
Cucchiarini, Catia; Nejjari, Warda; Strik, Helmer – Language Learning in Higher Education, 2012
Individualized tutoring and feedback by trained language instructors are known to be optimal for language learning. Providing them is time-consuming and costly, however, and therefore not feasible for the majority of language learners. This applies particularly to pronunciation, where corrective feedback should ideally be synchronous, which makes…
Descriptors: Pronunciation, Coaching (Performance), Computer Assisted Instruction, English (Second Language)
Flanagan, Brendan; Yin, Chengjiu; Hirokawa, Sachio; Hashimoto, Kiyota; Tabata, Yoshiyuki – International Journal of Distance Education Technologies, 2013
In this paper, the entries of Lang-8, which is a Social Networking Site (SNS) site for learning and practicing foreign languages, were analyzed and found to contain similar rates of errors for most error categories reported in previous research. These similarly rated errors were then processed using an algorithm to determine corrections suggested…
Descriptors: Social Networks, Computer Assisted Instruction, Educational Technology, Second Language Instruction
Gimeno, Ana, Ed. – European Association for Computer-Assisted Language Learning (EUROCALL), 2014
"The EUROCALL Review" is EUROCALL's open access online scientific journal. Regular sections include: (1) Reports on EUROCALL Special Interest Groups: up-to-date information on SIG activities; (2) Projects: reports on on-going CALL or CALL-related R&D projects; (3) Recommended websites: reports and reviews of examples of good practice…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Grammar
Blanchard, Alexia; Kraif, Olivier; Ponton, Claude – CALICO Journal, 2009
This paper presents a "didactic triangulation" strategy to cope with the problem of reliability of NLP applications for computer-assisted language learning (CALL) systems. It is based on the implementation of basic but well mastered NLP techniques and puts the emphasis on an adapted gearing between computable linguistic clues and didactic features…
Descriptors: Spelling, Educational Technology, Natural Language Processing, Computer Assisted Instruction
Futagi, Yoko; Deane, Paul; Chodorow, Martin; Tetreault, Joel – Computer Assisted Language Learning, 2008
This paper describes the first prototype of an automated tool for detecting collocation errors in texts written by non-native speakers of English. Candidate strings are extracted by pattern matching over POS-tagged text. Since learner texts often contain spelling and morphological errors, the tool attempts to automatically correct them in order to…
Descriptors: Native Speakers, English (Second Language), Limited English Speaking, Computational Linguistics

Heift, Trude – CALICO Journal, 2003
Describes a web-based intelligent computer assisted language learning (ICALL) system for German that provides error-specific feedback suited to learner expertise. Focuses on the Domain Knowledge and Filtering Module. Concludes with a study that supports the need for a CALL system that addresses multiple errors by considering language teaching…
Descriptors: Computer Assisted Instruction, Error Correction, Error Patterns, German

Hoppe, H. Ulrich – Journal of Artificial Intelligence in Education, 1994
Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)
Descriptors: Algorithms, Artificial Intelligence, Computer Assisted Instruction, Deduction

Dagneaux, Estelle; Denness, Sharon; Granger, Sylviane – System, 1998
Introduces the technique of computer-aided error analysis, a new approach to analyzing learner errors in second-language learning. Data used to demonstrate the technique consist of a 150,000-word corpus of English written by intermediate and advanced-level French-speaking learners. The study concludes that error analysis is worthwhile,…
Descriptors: Advanced Students, Computer Assisted Instruction, English (Second Language), Error Analysis (Language)

Chen, Judy F. – TESL-EJ, 1997
Examined a possible link between computer-generated feedback and changes in writing strategies of English-as-a-foreign-language business-writing students in Taiwan. Numerous detailed analyses were carried out using computer software that measured students' writing, including time spent on a document, amount of editing of a document, specific…
Descriptors: Business Communication, Classroom Techniques, Computer Assisted Instruction, Computer Software