• Title/Summary/Keyword: 컴퓨터 활용 적응적 평가

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Applying Information and Communication Technology for Advancing Educational Assessment (교육 평가의 혁신을 위한 테크놀러지의 활용)

  • Park, Joo-Yong
    • Proceedings of the Korean Society for Cognitive Science Conference
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    • 2005.05a
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    • pp.112-121
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    • 2005
  • 평가는 교수와 함께 교육 목표를 이루는데 있어 핵심적인 역할을 한다. 그렇지만 평가는 교수법의 발전 속도에 비교하면 상당히 느릴 뿐만 아니라, 교사는 물론 학생들에게 부정적으로 비추어지고 있다. 본 논문에서는 시험이 학생들을 동기화시킬 뿐만 아니라 그 자체로 중요한 학습 경험임을 강조하면서, 학습을 위한 평가를 활성화시키기 위해 테크놀러지를 이용한 평가 방식들을 소개하였다. 개발을 물론 어느 정도 연구가 이루어진 테크놀러지를 활용한 평가 기법을, 수행평가와 선다형의 개선안으로 대별하였다. 수행평가를 위한 기법에서는 논술채점, 지식 지도 제작법, 그리고 학습자 모형을 이용한 평가기법이, 선다형의 개선안으로 적응형 컴퓨터화 검사, 다중평가 및 변형선다형 방식이 각각 상술되었다. 결론에서는 평가를 통한 교육 효과를 극대화하기 위해서는, 교사는 물론 학생들의 평가에 대한 태도 변화 교육과 실제 교육 현장에서 쉽게 활용될 수 있는 컴퓨터를 이용한 평가기법의 개발과 보급의 중요성이 강조되었다.

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Adaptive Context-Sensitive Spelling Error Correction System Based on Self-Attention for Social Network Service Chatting Data (SNS 채팅 데이터에 적응적인 Self-Attention 기반 문맥의존 철자오류 교정 시스템)

  • Choi, Hyewon;Jang, Daesik;Son, Dongcheol;Lee, Seungwook;Ko, Youngjoong
    • Annual Conference on Human and Language Technology
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    • 2019.10a
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    • pp.362-367
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    • 2019
  • 본 논문에서는 Self-Attention을 활용한 딥러닝 기반 문맥의존 철자오류 교정 모델을 제안한다. 문맥의존 철자오류 교정은 최근 철자오류 교정 분야에서 활발히 연구되고 있는 문제 중 하나이다. 기존에는 규칙 기반, 확률 기반, 임베딩을 활용한 철자오류 교정이 연구되었으나, 아직 양질의 교정을 수행해내기에는 많은 문제점이 있다. 따라서 본 논문에서는 기존 교정 모델들의 단점을 보완하기 위해 Self-Attention을 활용한 문맥의존 철자오류 교정 모델을 제안한다. 제안 모델은 Self-Attention을 활용하여 기존의 임베딩 정보에 문맥 의존적 정보가 반영된 더 나은 임베딩을 생성하는 역할을 한다. 전체 문장의 정보가 반영된 새로운 임베딩을 활용하여 동적으로 타겟 단어와의 관련 단어들을 찾아 문맥의존 철자 오류교정을 시행한다. 본 논문에서는 성능평가를 위해 세종 말뭉치를 평가 데이터로 이용하여 제안 모델을 실험하였고, 비정형화된 구어체(Kakao Talk) 말뭉치로도 평가 데이터를 구축해 실험한 결과 비교 모델보다 높은 정확율과 재현율의 성능향상을 보였다.

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A Study on Judgement of Optimal SPRT for Learning Estimation (학습 평가를 위한 최적의 SPRT 판정에 관한 연구)

  • Jeon, Mi-Ran;Oh, Am-Seok
    • Journal of Korea Multimedia Society
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    • v.12 no.8
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    • pp.1182-1189
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    • 2009
  • A potential advantage of computer-based education is individualized instruction. In this regard, issues regarding how to evaluate individual learners fast and accurately in order to implement customized instruction program and to open education are raised. In this study, we suggest through a simulation study a way to reach an optimal decision by complementing the insufficient point of the way of the decision of the existing SPRT(Sequential Probability Ratio Testing) in which the number of questions in a test decreases while decision on pass or fail is relatively exact. For the purpose, the data of the examinees obtained from actual tests were used in this study and we present that simulation to verify the accuracy of decision and Multilevel SPRT decision standard for initial set point for optimal SPRT decision and evaluate the ground of the same through simulation.

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Development of an Adaptive e-Learning System for Engineering Mathematics using Computer Algebra and Bayesian Inference Network (컴퓨터 대수와 베이지언 추론망을 이용한 이공계 수학용 적응적 e-러닝 시스템 개발)

  • Park, Hong-Joon;Jun, Young-Cook
    • The Journal of the Korea Contents Association
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    • v.8 no.5
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    • pp.276-286
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    • 2008
  • In this paper, we introduce an adaptive e-Learning system for engineering mathematics which is based on computer algebra system (Mathematica) and on-line authoring environment. The system provides an assessment tool for individual diagnosis using Bayesian inference network. Using this system, an instructor can easily develop mathematical web contents via web interface. Examples of such content development are illustrated in the area of linear algebra, differential equation and discrete mathematics. The diagnostic module traces a student's knowledge level based on statistical inference using the conditional probability and Bayesian updating algorithm via Netica. As part of formative evaluation, we brought this system into real university settings and analyzed students' feedback using survey.

Domain-Adaptive Pre-training for Korean Document Summarization (도메인 적응 사전 훈련 (Domain-Adaptive Pre-training, DAPT) 한국어 문서 요약)

  • Hyungkuk Jang;Hyuncheol, Jang
    • Annual Conference of KIPS
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    • 2024.05a
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    • pp.843-845
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    • 2024
  • 도메인 적응 사전 훈련(Domain-Adaptive Pre-training, DAPT)을 활용한 한국어 문서 요약 연구에서는 특정 도메인의 문서에 대한 이해도와 요약 성능을 향상시키기 위해 DAPT 기법을 적용했다. 이 연구는 사전 훈련된 언어 모델이 일반적인 언어 이해 능력을 넘어 특정 도메인에 최적화된 성능을 발휘할 수 있도록 도메인 특화 데이터셋을 사용하여 추가적인 사전 훈련을 진행한다. 구체적으로, 의료, 법률, 기술 등 다양한 도메인에서 수집한 한국어 텍스트 데이터를 이용하여 모델을 미세 조정하며, 이를 통해 얻은 모델은 도메인에 특화된 용어와 문맥을 효과적으로 처리할 수 있음을 보여준다. 성능 평가에서는 기존 사전 훈련 모델과 DAPT를 적용한 모델을 비교하여 DAPT의 효과를 검증했다. 연구 결과, DAPT를 적용한 모델은 도메인 특화 문서 요약 작업에서 성능 향상을 보였으며, 이는 실제 도메인별 활용에서도 유용할 것으로 기대된다.

Qualitative Evaluation by using Intelligent Fuzzy Logical Inference for the Public Education (지능형 퍼지 추론 기법을 적용한 공교육의 정성 평가방법)

  • Kim, Youngtaek
    • The Journal of Korean Association of Computer Education
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    • v.17 no.1
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    • pp.97-105
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    • 2014
  • To enhance the practical usage of solely quantitative evaluation method for each students on the current public education fields which might cause some social problems, an intelligent and adaptive fuzzy logical inference methodology for the additional qualitative evaluation technique is proposed to utilize each students personal characteristic properties to be evaluated. Proposed method uses some verbal descriptions for the linguistic qualifier in addition to the grade points. An imaginary virtual experimentation only has been implemented due to some difficulties with the critical national educational policy problems in the case of some possibly real and practical experimental environments to be utilized for the simulation.

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Audio Generative AI Usage Pattern Analysis by the Exploratory Study on the Participatory Assessment Process

  • Hanjin Lee;Yeeun Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.4
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    • pp.47-54
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    • 2024
  • The importance of cultural arts education utilizing digital tools is increasing in terms of enhancing tech literacy, self-expression, and developing convergent capabilities. The creation process and evaluation of innovative multi-modal AI, provides expanded creative audio-visual experiences in users. In particular, the process of creating music with AI provides innovative experiences in all areas, from musical ideas to improving lyrics, editing and variations. In this study, we attempted to empirically analyze the process of performing tasks using an Audio and Music Generative AI platform and discussing with fellow learners. As a result, 12 services and 10 types of evaluation criteria were collected through voluntary participation, and divided into usage patterns and purposes. The academic, technological, and policy implications were presented for AI-powered liberal arts education with learners' perspectives.

The Development of e-Learning System for Science and Engineering Mathematics using Computer Algebra System (컴퓨터 대수 시스템을 이용한 이공계 수학용이러닝 시스템 개발)

  • Park, Hong-Joon;Jun, Young-Cook;Jang, Moon-Suk
    • The KIPS Transactions:PartA
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    • v.14A no.6
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    • pp.383-390
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    • 2007
  • This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

Data modeling and algorithms design for implementing Competency-based Learning Outcomes Assessment System (역량기반 학습성과 평가 시스템 구현을 위한 데이터 모델링 및 알고리즘 설계)

  • Chung, Hyun-Sook;Kim, Jung-Min
    • Journal of Convergence for Information Technology
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    • v.11 no.11
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    • pp.335-344
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    • 2021
  • The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

Development of a CAS-Based Virtual Learning System for Personalized Discrete Mathematics Learning (개인 적응형 이산 수학 학습을 위한 CAS 기반의 가상 학습 시스템 개발)

  • Jun, Young-Cook;Kang, Yun-Soo;Kim, Sun-Hong;Jung, In-Chul
    • Journal of the Korean School Mathematics Society
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    • v.13 no.1
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    • pp.125-141
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    • 2010
  • The aim of this paper is to develop a web-based Virtual Learning System for discrete mathematics learning using CAS (Computer Algebra System), The system contains a series of contents that are common between secondary und university curriculum in discrete mathematics such as sets, relations, matrices, graphs etc. We designed and developed web-based virtual learning contents contained in the proposed system based on Mathematia, webMathematica and phpMath taking advantages of rapid computation and visualization. The virtual learning system for discrete math provides movie lectures and 'practice mode' authored with phpMath in order to enhance conceptual understanding of each movie lesson. In particular, matrix learning is facilitated with conceptual diagram that provides interactive quizzes. Once the quiz results are submitted, Bayesian inference network diagnoses strong and weak parts of learning nodes for generating diagnostic reports to facilitate personalized learning. As part of formative evaluation, the overall responses were collected for future revision of the system with 10 university students.

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