• Korean Journal of Cognitive Science
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• v.14 no.3
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• pp.13-21
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• 2003

This study presents a design of Teachable Agent(TA) and its theoretical background. TA is an intelligent agent to which students as tutors teach, pose questions, and provide feedbacks using a concept map. TA consists of four independent Modules, Teach Module, Q&A Module, Test Module, and Resource Module. In Teach Module, students teach TA by constructing concept map. In Q&A Module, both students and TA ask questions and answer questions each other through an interactive window. To assess TA's knowledge and provide feedback to students, Test Module consists of a set of predetermined questions which TA should pass. From Resource Module, students can search and look up important information to teach, ask questions, and provide feedbacks whenever they want. It is expected that TA should provide student tutors with an active role in learning and positive attitude toward the subject matter by enhancing their cognition as well as motivation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.797-802
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• 2023

In an environment where English is a foreign language, English learners can use AI voice chatbots in English-speaking practice activities to enhance their speaking motivation, provide opportunities for communication practice, and improve their English speaking ability. In this study, we propose a teaching-style AI voice chatbot that can be easily utilized by lower elementary school students and enhance their learning. To apply the Teachable Agent system to language learning, which is an activity based on tense, context, and memory, we proposed a new method of TA by applying the Teachable Agent to reflect the learner's English pronunciation and level and generate the agent's answers according to the learner's errors and implemented a Teachable Agent AI chatbot prototype. We conducted usability evaluations with actual elementary English teachers and elementary school students to demonstrate learning effects. The results of this study can be applied to motivate students who are not interested in learning or elementary school students to voluntarily participate in learning through role-switching.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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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.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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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.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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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.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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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.