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Soonri Choi; Soomin Kang; Kyungmin Lee; Hongjoo Ju; Jihoon Song – Contemporary Educational Technology, 2024
This study proposes that the gestures of an agent tutor in a multimedia learning environment can generate positive and negative emotions in learners and influence their cognitive processes. To achieve this, we developed and integrated positive and negative agent tutor gestures in a multimedia learning environment directed by cognitive gestures.…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Processes, Difficulty Level
Schmucker, Robin; Wang, Jingbo; Hu, Shijia; Mitchell, Tom M. – Journal of Educational Data Mining, 2022
We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…
Descriptors: Academic Achievement, Electronic Learning, Artificial Intelligence, Predictor Variables
Seongyune Choi; Yeonju Jang; Hyeoncheol Kim – Interactive Learning Environments, 2024
Intelligent Personal Assistants (IPAs) are becoming more prevalent in daily and educational contexts, increasing the possibility of using them as learning partners that can provide more personalized and learner-centric learning opportunities. However, research has primarily focused on educational advantages that IPAs may provide, overlooking…
Descriptors: Intelligent Tutoring Systems, Foreign Countries, Technology Uses in Education, Independent Study
Lee, Youngnam; Kim, Byungsoo; Shin, Dongmin; Kim, JungHoon; Baek, Jineon; Lee, Jinhwan; Choi, Youngduck – International Educational Data Mining Society, 2020
Intelligent Tutoring Systems (ITSs) have been developed to provide students with personalized learning experiences by adaptively generating learning paths optimized for each individual. Within the vast scope of ITS, score prediction stands out as an area of study that enables students to construct individually realistic goals based on their…
Descriptors: Intelligent Tutoring Systems, Prediction, Scores, Learner Engagement
Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
Huang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil – Research-publishing.net, 2017
This paper presents a chatbot for a Dialogue-Based Computer-Assisted second Language Learning (DB-CALL) system. A DB-CALL system normally leads dialogues by asking questions according to given scenarios. User utterances outside the scenarios are normally considered as semantically improper and simply rejected. In this paper, we assume that raising…
Descriptors: Second Language Learning, Dialogs (Language), Intelligent Tutoring Systems, Freedom
Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
Kim, Young Chun; Jung, Jung-Hoon – Journal of Curriculum Studies, 2019
This article presents a new conceptualization of 'shadow curriculum', one component of the worldwide phenomenon of shadow education, i.e. learning outside of school. Traditional conceptions of curriculum are not applicable to shadow education, and so this article begins by exploring how shadow education practices qualify as a new focus of…
Descriptors: Educational Practices, Academic Achievement, Supplementary Education, Foreign Countries
Huang, Jin-Xia; Kwon, Oh-Woog; Lee, Kyung-Soon; Kim, Young-Kil – Research-publishing.net, 2018
This paper presents a chatbot for a Dialogue-Based Computer Assisted Language Learning (DB-CALL) system. The chatbot helps users learn language via free conversations. To improve the chatbot performance, this paper adopts a Neural Machine Translation (NMT) engine to combine with an existing search-based engine, and also extracts a small domain…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Computer Mediated Communication
Merlo, Jarrad R.; Gruba, Paul A. – Australian Review of Applied Linguistics, 2015
Despite an increased emphasis on form-focused instruction (FFI), the use of the computer as a grammar tutor has remained largely unexamined for nearly two decades. With new technologies at hand, there is a need to take a fresh look at online grammar tutors and link designs more strongly to contemporary second language acquisition (SLA) principles…
Descriptors: Video Technology, Grammar, Second Language Learning, Second Language Instruction
Kwon, Oh-Woog; Lee, Kiyoung; Kim, Young-Kil; Lee, Yunkeun – Research-publishing.net, 2015
This paper introduces a Dialog-Based Computer-Assisted second-Language Learning (DB-CALL) system using semantic and grammar correctness evaluations and the results of its experiment. While the system dialogues with English learners about a given topic, it automatically evaluates the grammar and content properness of their English utterances, then…
Descriptors: Computer Assisted Instruction, Semantics, Grammar, Teaching Methods