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Direct linkNi, Aohua; Cheung, Alan – Education and Information Technologies, 2023
Previous studies have demonstrated the effectiveness of intelligent tutoring systems (ITS) in facilitating English learning. However, no empirical research has been conducted on secondary students' intention to use ITSs in the language domain. This study proposes an extended technology acceptance model (TAM) to predict secondary students'…
Descriptors: Intelligent Tutoring Systems, English (Second Language), Second Language Learning, Second Language Instruction
Chen-Chung Liu; Wan-Jun Chen; Fang-ying Lo; Chia-Hui Chang; Hung-Ming Lin – Journal of Educational Computing Research, 2024
Reading requires appropriate strategies to spark initial interest and sustain engagement. One promising strategy is the pedagogical approach of learning-by-teaching, transforming learners into active participants. Integrating this approach into digitalized and individualized reading contexts has the potential to foster the development of young…
Descriptors: Reading Interests, Active Learning, Intelligent Tutoring Systems, Artificial Intelligence
Whitehill, Jacob; Movellan, Javier – IEEE Transactions on Learning Technologies, 2018
We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Educational Policy, Comparative Analysis
L2 Learner Cognitive Psychological Factors about Artificial Intelligence Writing Corrective Feedback
Download full textWu, LiQin; Wu, Yong; Zhang, XiangYang – English Language Teaching, 2021
Although the study of artificial intelligence (AI) used in language teaching and learning is increasingly prevailing, research on language two (L2) learner cognitive psychological factors about AI writing corrective feedback (WCF) is scarce. This paper explores L2 learner cognitive psychology of pigai, an AI evaluating system for English writings…
Descriptors: Artificial Intelligence, Error Correction, Feedback (Response), Second Language Instruction
Ridgeway, Karl; Mozer, Michael C.; Bowles, Anita R. – Cognitive Science, 2017
We explore the nature of forgetting in a corpus of 125,000 students learning Spanish using the Rosetta Stone® foreign-language instruction software across 48 lessons. Students are tested on a lesson after its initial study and are then retested after a variable time lag. We observe forgetting consistent with power function decay at a rate that…
Descriptors: Computational Linguistics, Second Language Learning, Second Language Instruction, Computer Software
Yang, Yu-Fen; Hung, Ya-Chen – Educational Technology & Society, 2009
The purpose of this study is to examine readers' comprehension as they develop their mental representation of reference in four sequential online texts. A total of 92 college students from three reading classes were recruited to complete the following steps in each text: (1) identify references, (2) draw the relationships between references, and…
Descriptors: Feedback (Response), Reading Comprehension, Reading Tests, College Students
