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Showing 1 to 15 of 31 results Save | Export
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Wang, Tingting; Zheng, Juan; Tan, Chengyi; Lajoie, Susanne P. – Journal of Computer Assisted Learning, 2023
Background: Computer-based scaffolding has been intensively used to facilitate students' self-regulated learning (SRL). However, most previous studies investigated how computer-based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Computer Assisted Instruction, Intelligent Tutoring Systems
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Hamed Asgari; Georges Antoniadis – International Association for Development of the Information Society, 2022
Mobile artifacts are the objects that increasingly surround us in life. They provide us with the opportunity to engage in activities outside the traditional context and at our own pace. In this article, we present the results of the tests of our mobile application intended for the learning of the French language with the concept of SPOC with a…
Descriptors: French, Second Language Learning, Second Language Instruction, Natural Language Processing
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Assim S. Alrajhi – International Journal of Computer-Assisted Language Learning and Teaching, 2024
This study examines and compares L2 grammatical accuracy in digital multimodal writing (DMW) and monomodal text-based writing (TBW). Utilizing a mixed-methods design, the research incorporates a dataset comprising 180 written texts, a questionnaire, and text-based interviews. Sixty EFL learners were assigned to two groups (TBW and DMW) and…
Descriptors: Grammar, Accuracy, Writing Strategies, Comparative Analysis
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Degraeuwe, Jasper; Goethals, Patrick – Research-publishing.net, 2022
This paper presents a reflection on the design of an Intelligent Computer-Assisted Language Learning (ICALL) 'ecosystem', integrated into an online learning environment for Spanish as a Foreign Language (SFL). The innovative dimension of the ecosystem lies in its triple focus: apart from enabling users to create and use intelligent language…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Spanish
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Yin, Qinghua; Satar, Müge – International Online Journal of Education and Teaching, 2020
Chatbots, whose potential for language learning have caused controversy among Second Language Acquisition (SLA) researchers (Atwell, 1999; Fryer & Carpenter, 2006; Fryer & Nakao, 2009; Parker, 2005, Coniam, 2014; Jia, 2004; Chantarotwong, 2005) are intelligent conversational systems stimulating human interlocutors with voice or text. In…
Descriptors: English (Second Language), Second Language Learning, Computer Mediated Communication, Content Analysis
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Benzie, Helen Joy; Harper, Rowena – Teaching in Higher Education, 2020
Academic literacies research emphasizes the importance of social context for understanding student writing development in higher education. In particular, students' choices of textual practices are shaped by perceptions of disciplinary norms and institutional expectations. In contemporary online learning environments, however, student writing is…
Descriptors: Academic Language, Writing Instruction, Teaching Methods, Student Attitudes
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Ayedoun, Emmanuel; Hayashi, Yuki; Seta, Kazuhisa – IEEE Transactions on Learning Technologies, 2020
This article proposes a computer-based approach to effectively enhance second language learners' willingness to communicate in the target language. To do so, we implemented a conversational agent embedding a dialogue management model based on two conversational strategies (i.e., communication strategies and affective backchannels), serving as…
Descriptors: Scaffolding (Teaching Technique), Teaching Methods, Second Language Learning, Second Language Instruction
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Li, Kuo-Chen; Chang, Maiga; Wu, Kuan-Hsing – Education Sciences, 2020
This research involved the design of a task-based dialogue system and evaluation of its learning effectiveness. Dialogue training still heavily depends on human communication with instant feedback or correction. However, it is not possible to provide a personal tutor for every English learner. With the rapid development of information technology,…
Descriptors: Task Analysis, Teaching Methods, Second Language Learning, Second Language Instruction
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McCarthy, Kathryn S.; Soto, Christian Marcelo; Gutierrez de Blume, Antonio P.; Palma, Diego; González, Jordan Ignacio; McNamara, Danielle S. – International Journal of Computer-Assisted Language Learning and Teaching, 2020
iSTART-E is a web-based intelligent tutor developed for Spanish-speaking students to improve their reading comprehension through self-explanation strategy training. This study examined the effects of a blended comprehension strategy intervention on students' reading comprehension skill. Chilean high school students (N = 22) completed nine iSTART-E…
Descriptors: Reading Comprehension, High School Students, Computer Assisted Instruction, Teaching Methods
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Ai, Haiyang – ReCALL, 2017
Corrective feedback (CF), a response to linguistic errors made by second language (L2) learners, has received extensive scholarly attention in second language acquisition. While much of the previous research in the field has focused on whether CF facilitates or impedes L2 development, few studies have examined the efficacy of gradually modifying…
Descriptors: Error Correction, Feedback (Response), Computer Assisted Instruction, Second Language Learning
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Bontogon, Megan; Arppe, Antti; Antonsen, Lene; Thunder, Dorothy; Lachler, Jordan – Canadian Modern Language Review, 2018
Intelligent computer assisted language learning (ICALL) applications for Indigenous languages are a relatively new avenue for computer assisted language learning (CALL). CALL allows language learners to practise a wide range of grammatical exercises and receive feedback on their answers outside of class time. ICALL is essential for dynamically…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Computer Assisted Instruction
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Huang, 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)
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Martins, Igor; de Morais, Felipe; Schaab, Bruno; Jaques, Patricia – International Journal of Information and Communication Technology Education, 2016
In most Intelligent Tutoring Systems, the help messages (hints) are not very clear for students as they are only presented textually and have little connection with the task elements. This can lead to students' undesired behaviors, like gaming the system, associated with low performance. In this paper, the authors aim at evaluating if the gestures…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Problem Solving, Equations (Mathematics)
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Gearhart, Christopher – International Journal of Teaching and Learning in Higher Education, 2016
This study examines McGraw-Hill Higher Education's LearnSmart online textbook supplement and its effect on student exam performance in an interpersonal communication course. Students (N = 62) in two sections were either enrolled in a control group with no required LearnSmart usage or a treatment group with requisite LearnSmart assignments.…
Descriptors: Textbook Content, Interpersonal Communication, Comparative Analysis, Experimental Groups
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Forbes-Riley, Kate; Litman, Diane – International Journal of Artificial Intelligence in Education, 2013
In this paper we investigate how student disengagement relates to two performance metrics in a spoken dialog computer tutoring corpus, both when disengagement is measured through manual annotation by a trained human judge, and also when disengagement is measured through automatic annotation by the system based on a machine learning model. First,…
Descriptors: Correlation, Learner Engagement, Oral Language, Computer Assisted Instruction
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