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Direct linkChen, Binbin; Bao, Lina; Zhang, Rui; Zhang, Jingyu; Liu, Feng; Wang, Shuai; Li, Mingjiang – Journal of Educational Computing Research, 2024
Language learning has increasingly benefited from Computer-Assisted Language Learning (CALL) technologies, especially with Artificial Intelligence involved in recent years. CALL in writing learning acknowledged as the core of language learning is being realized by technologies like Automated Writing Evaluation (AWE), and Automated Essay Scoring…
Descriptors: Computer Assisted Instruction, English (Second Language), Second Language Learning, Writing Instruction
LaVoie, Noelle; Parker, James; Legree, Peter J.; Ardison, Sharon; Kilcullen, Robert N. – Educational and Psychological Measurement, 2020
Automated scoring based on Latent Semantic Analysis (LSA) has been successfully used to score essays and constrained short answer responses. Scoring tests that capture open-ended, short answer responses poses some challenges for machine learning approaches. We used LSA techniques to score short answer responses to the Consequences Test, a measure…
Descriptors: Semantics, Evaluators, Essays, Scoring
Download full textHuang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil – Research-publishing.net, 2016
This paper presents an automatic dialogue scoring approach for a Dialogue-Based Computer-Assisted Language Learning (DB-CALL) system, which helps users learn language via interactive conversations. The system produces overall feedback according to dialogue scoring to help the learner know which parts should be more focused on. The scoring measures…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Dialogs (Language)
Heidari, Jamshid; Khodabandeh, Farzaneh; Soleimani, Hassan – JALT CALL Journal, 2018
The emergence of computer technology in English language teaching has paved the way for teachers' application of Mobile Assisted Language Learning (mall) and its advantages in teaching. This study aimed to compare the effectiveness of the face to face instruction with Telegram mobile instruction. Based on a toefl test, 60 English foreign language…
Descriptors: Comparative Analysis, Conventional Instruction, Teaching Methods, Computer Assisted Instruction
Liu, Sha; Kunnan, Antony John – CALICO Journal, 2016
This study investigated the application of "WriteToLearn" on Chinese undergraduate English majors' essays in terms of its scoring ability and the accuracy of its error feedback. Participants were 163 second-year English majors from a university located in Sichuan province who wrote 326 essays from two writing prompts. Each paper was…
Descriptors: Foreign Countries, Undergraduate Students, English (Second Language), Second Language Learning
Shim, Yae Jie – Teaching English with Technology, 2013
The error-correction program "Criterion" provides students with an immediate essay feedback using tools that can analyze and review writing automatically. This feedback covers grammar, usage, mechanics, style, organization, and development. With its diagnostic tools for scoring essays and offering relevant feedback, the error-correction…
Descriptors: Error Correction, Writing Evaluation, Essays, Scoring
Dikli, Semire – CALICO Journal, 2010
The purpose of this study is to explore the nature of feedback that English as a Second Language (ESL) students received on their writings either from an automated essay scoring (AES) system or from the teacher. The participants were 12 adult ESL students who were attending an intensive English center at a university in Florida. The drafts of the…
Descriptors: Feedback (Response), Scoring, English (Second Language), Second Language Learning
