• 제목/요약/키워드: tutoring system

검색결과 135건 처리시간 0.023초

지능형 튜터링 시스템 실행에 관한 연구 (A Study on the Implementation of an Intelligent Tutoring System)

  • 임기영;김형래
    • 대한전자공학회논문지
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    • 제27권9호
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    • pp.1372-1377
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    • 1990
  • We constructed an intelligent tutoring system that compose four devices i.e. intelligent interface, acqusition module, tutoring controller and tutorial knowledge. We implemented the intelligent tutoring system using prolog as an authoring language in the ultrix os under VAX-11/750, and we propose goal opriented tutoring system algorithm.

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지능형 교수 시스템 지원을 위한 멀티미디어 인터페이스의 설계 (Design of Multimedia Interface for Intelligent Tutoring System)

  • 정상목;이완복
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2006년도 추계 종합학술대회 논문집
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    • pp.575-579
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    • 2006
  • 지능형 교수 시스템의 주요 구성 요소인 교수 모듈, 학습자 모듈, 전문가 모듈, 인터페이스 모듈 중에서 학습자와 가장 긴밀한 연관이 있으며 학습 시스템의 가장 큰 표현 부분에 해당하는 모듈이 인터페이스 모듈이다. 학습자에게 있어 인터페이스 모듈은 일반 이러닝 시스템뿐만 아니라 지능형 교수 시스템에서도 큰 비중을 차지하는데 아직까지 인터페이스의 개선에 관한 연구는 그리 활발하지 못한 실정이다. 이에 따라 본 연구에서는 이러닝시 학습자와 가장 상호작용이 많은 인터페이스의 개선에 관한 연구를 수행하였다. 본 연구를 위해 기존의 인터페이스의 주요 구성 요소에 대해 살펴보았으며 선행 연구의 문제점을 개선한 멀티미디어 인터페이스를 설계 구현 하였다.

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AI-based language tutoring systems with end-to-end automatic speech recognition and proficiency evaluation

  • Byung Ok Kang;Hyung-Bae Jeon;Yun Kyung Lee
    • ETRI Journal
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    • 제46권1호
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    • pp.48-58
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    • 2024
  • This paper presents the development of language tutoring systems for nonnative speakers by leveraging advanced end-to-end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non-native speech, high-performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End-to-end ASR is implemented and enhanced by using diverse non-native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI Peng-Talk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies.

UML-ITS Usability Evaluation of Intelligent Tutoring System

  • Sehrish Abrejo;Amber Baig;Mutee U Rahman;Adnan Asghar Ali
    • International Journal of Computer Science & Network Security
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    • 제23권3호
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    • pp.123-129
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    • 2023
  • The most effective tutoring method is one-on-one, face-to-face in-person human tutoring. However, due to the limited availability of human tutors, computer-based alternatives have been developed. These software based alternatives are called Intelligent Tutoring Systems (ITS) which are used to tutor students in different domains. Although ITS performance is inferior to that of human teachers, the field is growing and has recently become very popular. User interfaces play key role in usability perspective of ITS. Even though ITS research has advanced, the majority of the work has concentrated on learning sciences while mostly disregarding user interfaces. Because of this, the present ITS includes effective learning modules but a less effective interface design. Usability is one approach to gauge a software's performance, while "ease of use" is one way to assess a software's quality. This paper measures the usability effectiveness of an ITS which is designed to teach Object-Oriented (OO) analysis and design concepts using Unified Modeling Language (UML). Computer Supported Usability Questionnaire (CSUQ) survey was conducted for usability evaluation of UML-ITS. According to participants' responses to the system's usability survey, all responses lie between 1 to 3 scale points which indicate that the participants were satisfied and comfortable with most of the system's interface features.

Human Tutoring vs. Teachable Agent Tutoring: The Effectiveness of "Learning by Teaching" in TA Program on Cognition and Motivation

  • Lim, Ka-Ram;So, Yeon-Hee;Han, Cheon-Woo;Hwang, Su-Young;Ryu, Ki-Gon;Shin, Mo-Ran;Kim, Sung-Il
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2006년도 학술대회 1부
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    • pp.945-953
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    • 2006
  • The researchers in the field of cognitive science and learning science suggest that the teaching activity induces the elaborative and meaningful learning. Actually, lots of research findings have shown the beneficial effect of learning by teaching such as peer tutoring. But peer tutoring has some limitations in the practical learning context. To overcome some limitations, the new concept of "learning by teaching" through the agent called Teachable Agent. The teachable agent is a modified version of traditional intelligent tutoring system that assigns a role of tutor to teach the agent. The teachable agent monitors individual difference and provides a student with a chance for deep learning and motivation to learn by allowing them to play an active role in the process of learning. That is, The teaching activity induces the elaborative and meaningful learning. This study compared the effects of our teachable agent, KORI, and peer tutoring on the cognition and motivation. The field experiment was conducted to examine whether learning by teaching the teachable agent would be more effective than peer tutoring and reading condition. In the experiment, all participants took 30 minutes lesson on rock and rock cycle together to acquire the base knowledge in the domain. After the lesson, participants were randomly assigned to one of the three experimental conditions; reading condition, peer tutoring condition, and teachable agent condition. Next, participants of each condition moved into separated place and performed their own learning activity. After finishing all of the learning activities in each condition, all participants were instructed to rate the interestingness using a 5-point scale on their own learning activity and leaning material, and were given the comprehension test. The results indicated that the teachable agent condition and the peer tutoring condition showed more interests in the learning than the reading condition. It is suggested that teachable agent has more advantages in overcoming the several practical limitations of peer tutoring such as restrictions in time and place, tutor's cognitive burden, unnecessary interaction during peer tutoring. The applicability and prospects of the teachable agent as an efficient substitute for peer tutoring and traditional intelligent tutoring system were also discussed.

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INTERFACE DEVELOPMENT ENVIRONMENT BASED ON CHARACTER AGENT

  • Park, Young-Mee;Choo, Moon-Won
    • 한국멀티미디어학회논문지
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    • 제6권4호
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    • pp.650-657
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    • 2003
  • We describe a scheme for developing character-based interface within the context of an agent-based tutoring system in the Web environment. The ideas in this paper stem from original work representing aspects of human emotion in tutoring computer models, where may provide mote natural ways for students to communicate with digital learning materials. The proposed system model is a set of software services that enable developers to incorporate interactive animated characters into their Web pages designed for on-line lectures. The prototypical application is developed and shown for validating the applicability and the effectiveness of this model in real tutoring settings.

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학습자 행위 선호도에 기반한 적응적 학습 시스템 (An Adaptive Learning System based on Learner's Behavior Preferences)

  • 김용세;차현진;박선희;조윤정;윤태복;정영모;이지형
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2006년도 학술대회 1부
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    • pp.519-525
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    • 2006
  • Advances in information and telecommunication technology increasingly reveal the potential of computer supported education. However, most computer supported learning systems until recently did not pay much attention to different characteristics of individual learners. Intelligent learning environments adaptive to learner's preferences and tasks are desired. Each learner has different preferences and needs, so it is very crucial to provide the different styles of learners with different learning environments that are more preferred and more efficient to them. This paper reports a study of the intelligent learning environment where the learner's preferences are diagnosed using learner models, and then user interfaces are customized in an adaptive manner to accommodate the preferences. In this research, the learning user interfaces were designed based on a learning-style model by Felder & Silverman, so that different learner preferences are revealed through user interactions with the system. Then, a learning style modeling is done from learner behavior patterns using Decision Tree and Neural Network approaches. In this way, an intelligent learning system adaptive to learning styles can be built. Further research efforts are being made to accommodate various other kinds of learner characteristics such as emotion and motivation as well as learning mastery in providing adaptive learning support.

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상호 동료 교수법이 학업성취도와 만족도에 미치는 영향에 관한 연구: 컴퓨터 운영체제 실습 수업 적용 방안을 중심으로 (Effects of Reciprocal Peer Tutoring on Academic Achievement and Satisfaction: Focused on Application Practices in Computer Operating System Lab Education)

  • 이만희
    • 컴퓨터교육학회논문지
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    • 제16권3호
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    • pp.61-70
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    • 2013
  • 본 연구는 대학교 컴퓨터 실습 교육의 내실화를 위해 학습자의 적극적인 활동과 상호 교수를 통한 효과적인 학습을 유도할 수 있는 상호 동료 교수 모형(Reciprocal Peer Tutoring)을 적용하였다. 본 연구에서는 컴퓨터 운영체제를 교육함에 있어 상호 동료 교수 모형을 최소한의 준비 과정으로 단기간 적용하는데 초점을 두었다. 대학교 컴퓨터공학과 2학년 61명의 학습자가 본 연구에 참여하였으며, 학습자의 반은 상호 동료 교수 모형을 나머지는 일반 교육 방법을 적용하였다. 연구 결과, 상호 동료 교수 모형을 적용한 학습자가 높은 학업성취도 뿐만 아니라 수업 및 교수 만족도도 높게 나왔다. 본 연구에서 사용한 상호 동료 교수 모형 적용법은 실제 대학 실습 교육 현장에 쉽게 사용될 수 있을 것으로 기대된다.

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개인 맞춤형 수학 학습을 위한 인공지능 교육시스템의 기능과 적용 사례 분석 (Analysis of functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics)

  • 성지현
    • 한국수학교육학회지시리즈A:수학교육
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    • 제62권3호
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    • pp.303-326
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    • 2023
  • 수학은 계통성이 강한 학문으로 이전 단계에서의 학습 결손이 다음 학습에 큰 영향을 주기 때문에 학생들의 학습이 잘 이루어졌는지 수시로 확인하고, 즉각적으로 피드백을 제공해 주는 것이 필요하며, 이를 위해 수학교육에서 인공지능 교육시스템(ITS)을 활용할 수 있다. 이에 본 연구에서는 개인 맞춤형 수학 학습을 실행하기 위해 적용될 수 있는 인공지능 교육시스템의 기능이 무엇인지 살펴보고, 이를 실제로 적용해 본 결과를 분석하여 인공지능 교육시스템을 활용한 개인 맞춤형 수학 학습의 효과성을 구체적으로 살펴보는 것을 목적으로 하였다. 이를 위해 개인 맞춤형 학습과 수학교육에서 인공지능이 활용된 선행연구 내용을 분석하여 개인 맞춤형 수학 학습을 위한 인공지능 교육시스템의 기능을 추출하고, 이것을 반영한 학습 및 수업을 설계하여 초등학교 5학년 학생들에게 약 3개월 간 적용해 본 결과를 분석하였다. 그 결과, 개인 맞춤형 수학 학습을 위해 활용될 수 있는 인공지능 교육시스템의 기능은 크게 진단 및 평가, 분석 및 예측, 피드백 및 콘텐츠 제공으로 나눌 수 있었다. 또한 이러한 기능을 반영한 학습 설계를 초등학생들에게 적용한 결과, 개인 맞춤형 수학 학습에 인공지능 교육시스템이 어떻게 효과적으로 활용될 수 있는지에 대한 시사점을 얻었다. 그리고 앞으로 인공지능 교육시스템을 활용한 개인 맞춤형 수학 학습이 더욱 효과적으로 이루어질 수 있기 위해 더 정교한 기술과 자료 개발이 필요하다는 점을 제언하였다.