• Journal of Industrial Convergence
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• v.22 no.11
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• pp.51-61
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• 2024

This study aims to identify whether self-regulation and co-regulation predicted learning outcomes in non face-to-face cooperative learning environments. To do so, this study chose satisfaction and learning achievement for learning outcomes variables. And for learning outcomes prediction, self-regulation and co-regulation were selected. This study designed classes in accordance with the CBL and UDL guidelines and 28 undergraduate students have participated for the execution of this study. The questionnaire survey was given to students at the end of the class and the study analyzed based on the result. The results of this study were as follows: First, self-regulation did not significantly predicted co-regulation in non face-to-face cooperative learning environments. Second, co-regulation significantly predicted satisfaction, but self-regulation did not predict satisfaction, Third, self-regulation significantly predicted learning achievement, but co-regulation did not predict learning achievement. And lastly, satisfaction was associated with gender, but learning achievement was not associated with gender. This study provides its significance in expanding the understanding about the nature of non face-to-face cooperative learning environments.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.559-560
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• 2018

최근 국내 신입사원 입사시험에 NCS 직업기초능력시험을 도입함에 따라 국내 각 대학교나 교육기관에서는 NCS 기반의 전공교육 및 교양교육을 도입하고 있다. 이에 따라 프로그래머를 지향하는 공학도를 위한 NCS 기반 프로그래밍 능력을 향상시켜줄 수 있는 교수-학습 지침안이 필요하게 되었다. 본 연구에서는 학습 모듈을 도출하기 위한 분석과정을 거쳐 본 교과의 학습로드맵과 NCS능력단위요소를 기반으로 학습자 스스로 NCS 프로그래밍 능력을 향상시킬 수 있는 교수-학습 모듈을 설계하였다.

• Smart Media Journal
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• v.10 no.1
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• pp.55-62
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• 2021

We applied machine learning of semi-supervised learning, transfer learning, and federated learning as examples of AI use cases that can be applied to the three major industries(Automobile industry, Energy industry, and AI/Healthcare industry) of Gwangju Metro-city, and established an ML strategy for AI services for the major industries. Based on the ML strategy of AI service, practical approaches are suggested, the semi-supervised learning approach is used for automobile image recognition technology, and the transfer learning approach is used for diabetic retinopathy detection in the healthcare field. Finally, the case of the federated learning approach is to be used to predict electricity demand. These approaches were tested based on hardware such as single board computer Raspberry Pi, Jaetson Nano, and Intel i-7, and the validity of practical approaches was verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2785-2791
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• 2012

In this paper, a method for automatic classification of learning objects is proposed for effective management and reuse of learning contents. Proposed method will create cohesion of learning objects using cases of learning objects and perform automatic classification of learning objects by measuring their relationship based on cohesion. Application of proposed method to learning management system has the advantage of reducing the costs for developing learning contents. Simulation has shown the average accuracy of 28.20% with probability-based method and 56.38% with cohesion-based method. Simulation has proved that the method proposed in this paper is effective in automatic classification of learning objects.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.373-377
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• 2018

판례는 재판에 대한 선례로, 법적 결정에 대한 근거가 되는 핵심 단서 중 하나이다. 본 연구에서는 채권회수를 예측하는 서비스 구축을 위한 단서를 추출하기 위해 채권 회수 판례를 수집하여 이를 분석한다. 먼저 채권 회수 판례에 대한 기초 분석을 위하여, 채권 회수 사례와 비회수 사례를 각 20건씩 수집하여 분석하였으며, 이후 대법원 및 법률 지식베이스의 채권 관련 판례 12,457건을 수집하고 채권 회수 여부에 따라 가공하였다. 채권 회수 사례와 비회수 사례를 분류하기 위한 판례 내의 패턴을 분석하여 레이블링하고, 이를 자동 분류할 수 있는 Bidirectional LSTM 기반 심층학습 모델을 구성하여 학습하였다. 채권 관련 판례 가공 기준에 따라 네 가지의 데이터 셋을 구성하였으며, 각 데이터셋을 8:2의 비율로 나누어 실험한 결과, 검증 데이터에 대하여 F1 점수 89.82%의 우수한 성능을 보였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.292-300
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• 2016

The purpose of this study was to investigate the effects of case-based learning about infants and toddlers on healthcare department students, using a video in an emergency care environment. A total of 57 students from a healthcare department of D university in J city were enrolled. They were divided into two groups: The experimental group (n=29) and the control group (n=28). This study is pre-post designed with a non-equivalent control group. The experimental group received a 1-week education for a duration of 3 weeks (3 sessions in total) with 180 minutes per session. The control group received a traditional curriculum of lecture. Before and after the education, we measured the knowledge and skill confidence of emergency care toward infants and toddlers, the academic self-efficacy, and problem solving ability. Data collection and intervention were carried out from November to December of 2014. Data were analyzed with x2-test, paired t-test, unpaired t-test with SPSS version 20.0 Program. The experimental group showed a significantly higher improvement of skill confidence of emergency care toward infants and toddlers (P<001), as well as preferred task difficulty among sub-items of academic self-efficacy (p=.029), approach avoidance style (P=.001), and problem solving confidence (p=.040) among sub-items of problem solving ability on preference compared with the control group. In this study, a case-based learning was verified to be an effective teaching method to enhance professional competency of healthcare department students. The findings from this study suggest that a case-based learning using various educational contents should be developed, expanded, and carried out to promote better learning.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.978-982
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• 2009

This paper proposes a potential-based reinforcement learning, called "RLs-CBDT", which combines multiple RL agents and case-base decision theory designed for decision making in uncertain environment as an expert knowledge in RL. We empirically show that RLs-CBDT converges to an optimal policy faster than pre-existing RL algorithms through a Tetris experiment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.207-210
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• 2022

최근 자연어 처리 분야에서 기계학습 독해 관련 연구가 활발하게 이루어지고 있다. 그러나 그 중에서 한국어 기계독해 학습을 통해 문제풀이에 적용한 사례를 찾아보기 힘들었다. 기존 연구에서도 수능 영어와 수능 수학 문제를 인공지능(AI) 모델을 활용하여 문제풀이에 적용했던 사례는 있었지만, 수능 국어에 이를 적용하였던 사례는 존재하지 않았다. 또한, 수능 영어와 수능 수학 문제를 AI 문제풀이를 통해 도출한 결괏값이 각각 12점, 16점으로 객관식이라는 수능의 특수성을 고려했을 때 기대에 못 미치는 결과를 나타냈다. 이에 본 논문은 한국어 기계독해 데이터셋을 트랜스포머(Transformer) 기반 모델에 학습하여 수능 국어 문제 풀이에 적용하였다. 이를 위해 객관식으로 이루어진 수능 문항의 각각의 선택지들을 질문 형태로 변형하여 모델이 답을 도출해낼 수 있도록 데이터셋을 변형하였다. 또한 BERT(Bidirectional Encoder Representations from Transformer)가 가진 입력값 개수의 한계를 극복하기 위해 더 큰 입력값을 처리할 수 있는 트랜스포머 기반 모델 중에서 한국어 기계독해 학습에 적합한 KoBigBird를 사전학습모델로 설정하여 성능을 높였다.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.73-81
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• 2016

This paper deals with the practical experience and lessons to develop a method of course-embedded assessment for program outcomes in Computer Science & Information Engineering. In engineering education, ABEEK(Accreditation Board for Engineering Education of Korea) has been nominated as an official accreditation from Korean government under some conditions of fulfillment. One of the conditions is enforcement of course-embedded assessment for program outcomes. In this paper, a method of course-embedded assessment in Computer Science & Information Engineering is suggested. The case study was done in a basic project course which includes the special assessment methods in project courses. The case study of course-embedded assessment in a basic project course was given with consideration for each step, that is, set up of program outcomes which are highly related to the course, selection of assessment tools such as written examination and project-based assessment, set up of assessment criteria, implementation of course-embedded assessment, and analysis of results. The proposed method is expected to be a good example to construct the whole strategy for course-embedded assessment in Computer Science & Information Engineering.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.141-152
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• 2013

This research aims at suggesting a case of designing theme-based integrated learning for usage smart media. New approach and direction for developing a gaming instructional design was suggested which can encourage learners to participate in. Quest-based learning, the learning environment design where learners conduct various learner-centered activities, plays an important role of reinforcing the motivation, promoting experiential and cooperative learning based on social interaction. The design using QR codes has been proved to be able to offer the learner-centered learning environment which includes social interaction strategy required for learners expanding their cognitive structure, motivation enhancing strategy encouraging their consistent participation in learning, complex problematic situation and scaffolding strategy emphasized by constructivism. And it is expected to contribute to promoting the design of theme-based integrated learning which is being demanded in the educational environment recently by combining systematic design process and strategies.