• 제목/요약/키워드: teachable agent

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대화형 Teachable Agent를 이용한 영어말하기학습 시스템 (An interactive teachable agent system for EFL learners )

  • 이경아;임순범
    • 문화기술의 융합
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    • 제9권3호
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    • pp.797-802
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    • 2023
  • 영어가 외국어로서 사용되는 환경에서 영어 말하기 연습 활동에 AI 음성 챗봇을 사용했을 때 영어학습자들은 발화 동기가 높아지고 의사소통 연습의 기회가 많아져 결과적으로 영어 말하기 능력을 향상 시킬 수 있다. 본 연구에서는 초등학생 저학년의 경우에도 쉽게 활용 가능하고 학습효과를 높일 수 있는 가르치기 방식의 AI 음성 챗봇을 제안한다. 시제와 맥락과 기억에 기반한 활동인 언어학습에 Teachable Agent 시스템을 적용하기 위해 Teachable Agent에 학습자의 영어 발음과 수준을 반영하고, 학습자 오류에 맞추어 에이전트의 답변을 생성하는 방식을 적용하여 새로운 방식의 TA를 제안하고 이를 적용한 Teachable Agent AI 챗봇 프로토타입을 구현하였다. 실제 초등 영어 선생님과 초등학생을 대상으로 사용성 평가를 진행하여 학습 효과를 입증하였다. 본 연구 결과는 역할 전환을 통해 학습에 흥미가 없는 학생 또는 초등 저학년들이 학습에 스스로 참여할 수 있는 동기부여를 할 수 있도록 적용할 수 있다.

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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교수가능 에이전트(Teachable Agent)의 개념적 이해와 설계방안 (Understanding and Designing Teachable Agent)

  • 김성일;김원식;윤미선;소연희;권은주;최정선;김문숙;이명진;박태진
    • 인지과학
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    • 제14권3호
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    • pp.13-21
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    • 2003
  • 이 연구에서는 기존의 지능형 교수기계와 또래 튜터링의 단점을 보완하여 '가르치기를 통한 학습'을 위한 교수가능 에이전트(Teachable Agent, 이하 TA) 의 이론적 배경 및 설계방안을 제시하고자 한다. TA는 학습자가 컴퓨터 에이전트를 가르치는 과정을 통해 학습하는 시스템으로 교수 Module, 묻고 답하기 Module, 테스트 Module, 학습자료 Module 등의 4 가지 Module로 구성된다. 교수 Module에서는 개념도(concept map)의 구성을 통해 튜터 역할을 하는 학습자가 TA 의 심성모형 (mental model)을 수정하고 update하게 되며, 묻고 답하기 Module에서는 인터렉티브 창을 통해 튜터와 TA가 제한된 방식으로 학습내용에 관한 질문과 응답을 함으로써 개념도를 수정보완하게 된다. 테스트 Module에서는 튜터가 가르친 TA가 미리 정해놓은 학습목표에 도달하였는지를 평가하게 된다. 테스트 결과 TA가 일정 수준에 도달하지 못한 경우에는 개념도의 재수정 과정을 통해 계속적인 학습이 이루어지도록 한다. 학습자료 Module은 튜터가 참고할 자료를 제공해 주는 Module이다. 이러한 TA는 튜터의 역할을 담당하는 학습자에게 깊이 있는 인지적 처리와 능동적인 학습동기를 경험하도록 함으로써 실제 교육현장에서의 유용한 교수/학습도구로 활용될 수 있을 것으로 기대된다.

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The Relationship between Learner and Interest in Teachable Characteristic Agent

  • 권순구;우연경;조은수;정윤경;전훈;연은모;정해천;박성민;소연희;김성일
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 2부
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    • pp.78-84
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    • 2008
  • The traditional intelligent teachable system has mainly focused on knowledge and cognition. It has overlooked motivational aspects of learners. Motivation is an important factor in learning making learners to have interests in a given task and persist it. Although the systems include cognitive as well as motivational factors, the effects of ITS on interest are not equivalent depending on individual characteristics. This study is to investigate how influence learners' response patterns to their interests and also examined effects of individual characteristics on interest in teachable agent (TA). In this experiment, we used KORI which is a new type of ITS that learner teach computer agent based on the instructional method of learning by teaching'. In the beginning of experiments, metacognition, achievement goal orientation and self-efficacy were measured as individual characteristics. Then, participants were asked to use KORI at home during 10 days. After using KORI the level of interest were measured. The result showed that metacognition was positively related with interest, whereas performance goal orientation and mastery goal orientation were negatively related to interest. It suggests t hat different individual characteristics should be considered to promote learners' intrinsic motivation in TA.

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< Modeling Study for Developing Motivational and Cognitive Adaptive Agent >

  • Lee, Woo-Gul;Lee, Myung-Jin;Lim, Ka-Ram;Han, Cheon-Woo;So, Yeon-Hee;Hwang, Su-Young;Ryu, Ki-Gon;Yun, Sung-Hyun;Choi, Dong-Seong;Kim, Sung-Il
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2006년도 학술대회 1부
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    • pp.918-925
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    • 2006
  • Recent development of teachable agent provides learners with active roles as knowledge constructors and focuses on the individualization. The aim of this adaptive agent is not only to maximize the learner's cognitive functions but also to enhance the interests and motivation to learn. In order to establish the relationships among user characteristics and response patterns and to extract the algorithm among variables, we measured the individual characteristics and analyzed logs of the teachable agent named KORI (KORea university Intelligent agent) through the student modeling. A correlation analysis was conducted to identify the relationships among individual characteristics, user responses, and learning outcomes. Among hundreds of possible relationships between numerous variables in three dimensions, nine key user responses were extracted, which were highly correlated with either individual characteristics and learning outcomes. The results suggest that certain type of learner responses or the combination of the responses would be useful indices to predict the learners' individual characteristics and ongoing learning outcome. This study proposed a new type of dynamic assessment for individual differences and ongoing cognitive/motivational learning outcomes through the computation of responses without measuring them directly. The construction of individualized student model based on the ongoing response pattern of the user that are highly correlated with the individual differences and learning outcome may be the useful methodology to understand the learner's dynamic change during learning.

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The Characteristic of Reward in Computer Assisted Learning

  • 연은모;이선영;정윤경;조은수;권순구;전훈;이계형;윤성현;소연희;김성일
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 2부
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    • pp.64-70
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    • 2008
  • Computer Assisted Learning (CAL) is quite different from in many aspects. CAL provides individualistic learning environment and facilitates autonomy of the learner. Thus the learners who uses CAL program has more sense of control and engages in more strategic learning than conventional learning environment. In this experiment, we used KORI (KORea university intelligent agent) which is a new type of ITS adopting TA (Teachable Agent) that fosters learning by teaching, So, we investigated the critical motivational factor that have influences in CAL learning and the effects of reward in CAL are another area of our interest. Thus, we divided two conditions that presence of reward and absence of reward. The 174 elementary school students(5th) were participated and they are randomly assigned the one of the reward conditions. Before entering the experimental instruction, all participants measured about metacognition, self-efficacy and goal orientation questionnaire as independent variables. Then, Participants were instructed of method of using KORI program and asked to study for ten days with KORI program at least 20 minutes everyday in their home, about 10 days. After 10 days, they were rated interest and comprehension. Regression results suggest that regardless of the presence of reward, metacognition is a positive predictor in interestingness. It indicate that metacognitive skills are required in CAL learning situation irrespective of reward. But on comprehension in the absence of reward, only self- efficacy appeared to be a positive predictor. In the presence of reward, performance goal orientation showed as a negative predictor of comprehension, whereas self-efficacy was a positive predictor. This result suggest that presence of reward especially interferes learning process of performance goal orientation in CAL learning situation. It could be interpreted that reward interferes the learning process of performance goal orientation by debilitating intrinsic motivation.

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A way of measuring learner's ongoing changes of interest and comprehension

  • 전훈;백선희;정윤경;조은수;권순구;연은모;이민혜;소연희;최동성;김성일
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2008년도 학술대회 2부
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    • pp.71-77
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    • 2008
  • This study conducted to tried to find a way of on-line assessment of learner's interest and comprehension during interactive learning process. The result of experiment confirmed hat learners' behavior patterns acquired from log data could be good predictors of learner's level of interest and comprehension in actual performance on KORI program. To predict learning outcome depending on the behaviors of individual learners, self-efficacy and mastery goal orientation were measured as individual differences. Then, participants were asked to use TA program KORI program at home for ten days and their response patterns were recorded through network. After using KORI, the levels of interest and comprehension were measured. As the result of multiple regression analysis, each learner's interest and comprehension were predicted depending on the combination of log data captured on real-time. This prediction process was done differently depending on learners' characteristics. Since equations which predict learners' interest and comprehension are different depending on learners' characteristics, differential interfaces should be provided depending upon changes in their level of interest and comprehension.

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