• Title/Summary/Keyword: e-learning

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Reviewing connectionism as a theory of artificial intelligence: how connectionism causally explains systematicity (인공지능의 이론으로서 연결주의에 대한 재평가: 체계성 문제에 대한 연결주의의 인과적 설명의 가능성)

  • Kim, Joonsung
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.8
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    • pp.783-790
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    • 2019
  • Cognitive science attempts to explain human intelligence on the basis of success of artificial neural network, which is called connectionism. The neural network, e.g., deep learning, seemingly promises connectionism to go beyond what it is. But those(Fodor & Pylyshyn, Fodor, & McLaughlin) who advocate classical computationalism, or symbolism claim that connectionism must fail since it cannot represent the relation between human thoughts and human language. The neural network lacks systematicity, so any output of neural network is at best association or accidental combination of data plugged in input units. In this paper, I first introduce structure of artificial neural network and what connectionism amounts to. Second, I shed light on the problem of systematicity the classical computationalists pose for the connectionists. Third, I briefly introduce how those who advocate connectionism respond to the criticism while noticing Smolensky's theory of vector product. Finally, I examine the debate of computationalism and connectionism on systematicity, and show how the problem of systematicity contributes to the development of connectionism and computationalism both.

A Longitudinal Study on the Effect of Teacher Characteristics Perceived by Students on Mathematics Academic Achievement: Targeting Middle and High School Students (학생들이 인식한 교사의 특성이 수학 학업성취도에 미치는 영향에 대한 종단연구: 중·고등학교 학생을 대상으로)

  • Kim, YongSeok
    • Communications of Mathematical Education
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    • v.35 no.1
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    • pp.97-118
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    • 2021
  • Since the characteristics of teachers that affect mathematics academic achievement are constantly changing and affecting mathematics achievement, longitudinal studies that can predict and analyze growth are needed. This study used data from middle and high school students from 2013(first year of middle school) to 2017(second year of high school) of the Seoul Education Longitudibal Study(SELS). By classifying the longitudinal changes in mathematics academic achievement into similar subgroups, the direct influence of teachers' characteristics(professionalism, expectations, academic feedback) perceived by students on the longitudinal changes in mathematics academic achievement was examined. As a result of the study, it was found that the characteristics of mathematics teachers(professional performance, expectation, and academic feedback) in group 1(343 students), which included the top 14.5% of students, did not directly affect longitudinal changes in mathematics academic achievement. Students in the middle 2nd group(745, 32.2%) had academic feedback from the mathematics teacher, and the 2nd group(1225 students) in the lower 53%, which included most of the students, showed that the expectations of the mathematics teacher were the longitudinal mathematics achievement. The change has been shown to have a direct effect. This suggests that support for teaching and learning should also reflect this, as the direct influence of teachers' professionalism, expectations, and academic feedback on longitudinal changes in mathematics academic achievement is different according to the characteristics and dispositions of students.

Changes in mathematics pedagogical lexicons: Extension research of the International Classroom Lexicon using a text mining approach (수학 교수학적 어휘의 변화: 텍스트 마이닝 기법을 이용한 교실수업 어휘 연구의 확장)

  • Lee, Gima;Kim, Hee-jeong
    • The Mathematical Education
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    • v.61 no.4
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    • pp.559-579
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    • 2022
  • Research on lexicon and language provides insights into the interests, values and practices of a community where individuals use the language. The International Classroom Lexicon Project, in which ten countries participated, identified own country's mathematics teaching and learning lexicons by investigating mathematics classroom instruction from teachers' perspectives in a speaking-oriented community. This study, as an extension of the International Classroom Lexicon Project research, investigated pedagogical lexicons used in 「Mathematics and Education」 journals specialized for Korean professional mathematics teachers published by the Korean Society of Teachers of Mathematics. Using the text mining approach, we also traced how these pedegogical lexicons have changed quantitatively over the past 10 years with a diachronic perspective. As a results, several novel terms were found in the writing-oriented community, which were not identified in the speaking-oriented community. In addition, we could discover some pedagogical lexicons have increased statistically significantly and some lexicons appeared(increased) rapidly across years. This implies the teacher community's values and zeitgeist by reflecting these changes in the sociocultural, incidental and social changing (i.e., periodical change) contexts. This study has value as a first step in understanding zeitgeist for mathematics education in Korean mathematics teacher community according to changes of times over the past 10 years. Also, this study contributes to the methodological insights: the text mining technique provides a methodological contribution to researching changes in interests, values and zeitgeist according to these changes in the times.

A Study on Acceptance and Modification in Yulgok Neo-Confucianism by Myungjae Yoon Jeung (명재 윤증의 율곡성리학의 수용과 변전(變轉))

  • Lee, Young-Ja
    • The Journal of Korean Philosophical History
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    • no.42
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    • pp.39-70
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    • 2014
  • Neo-Confucianism of Myungjae Yoon Jeung either accepted Yulgok Neo-Confucianism as it was or modified it. In this study, his Neo-Confucianism was divided into acceptance and modification in Yulgok Neo-Confucianism and examined. In the acceptance of Yulgok Neo-Confucianism, it was clarified that Neo-Confucianism of Myungjae Yoon Jeung thoroughly inherited characteristics of Yulgok Neo-Confucianism, including 'Yiguijimyo', 'Yitongguiguk' and 'Guibalyiseungildo'. However, Myungjae was not just satisfied with inheriting Yulgok Neo-Confucianism as it was, but modified and inherited the theory of Yulgok by suggesting his own original preaching. There were three original preaching of his in overall; 'emphasis on the control of Li', 'argument method on a theory of gaining knowledge by the study of things', and 'perception on moral mind, human mind and human desire'. Ultimately, it is concluded that Myungjae modified, inherited and developed Yulgok Neo-Confucianism to adjust a theory of Neo-Confucianism in a position of 'Yiguijimyo', based on 'a theory of Guibalyiseungildo' of Yulgok as a Confucian scholar of Giho school. It is consistent with his life philosophy that he avoided speculative arguments on Neo-Confucianism and pursued solid study(實工) with solid mind(實心). It is also consistent with his view of learning that he believed that theories of ancient sages were already rich that we should read them and practice their true knowledge(眞知), and making an effort on writing regardless of them was not a study of Mushil(務實). However, due to his younger students, he was classified as a scholar who emphasized the control of 'Li' the most in Yulgok school, and a new academic tie of Giho Soron was created. It is the most important significance that Neo-Confucianism of Myungjae has in that of Giho.

Abnormal Crowd Behavior Detection via H.264 Compression and SVDD in Video Surveillance System (H.264 압축과 SVDD를 이용한 영상 감시 시스템에서의 비정상 집단행동 탐지)

  • Oh, Seung-Geun;Lee, Jong-Uk;Chung, Yongw-Ha;Park, Dai-Hee
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.6
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    • pp.183-190
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    • 2011
  • In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

Development and Implementation of an Activity-Based AI Convergence Education Program for Elementary School Students (초등학생을 위한 활동중심 인공지능 융합 교육 프로그램 개발 및 적용)

  • Shin, Jinseon;Jo, Miheon
    • Journal of The Korean Association of Information Education
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    • v.25 no.3
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    • pp.437-448
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    • 2021
  • As the core technology of the Fourth Industrial Revolution, AI is applied to various fields of society(e.g. politics, culture, industry, economy, etc.) and causes revolutionary changes. Students who will lead the age of AI need the ability to recognize social changes due to AI, acquire AI related knowledge and utilize AI in various situations. However, it is difficult for elementary school students to understand the concept and principles of AI. Therefore, this study developed an AI education program by selecting educational contents and methods appropriate to the level of elementary school students, and investigated the educational effects of the program by applying it to an actual educational setting. The content selected in this study is 'Social Awareness on AI', 'Understanding AI' and 'Utilizing AI', and eight content elements were selected. To help students learn AI easily and pleasantly at their level, activity-centered education, convergence of subjects and project-based learning were selected as instructional methods, and 20 sessions of education program were developed and implemented. In addition, the effects of the program were analyzed concerning 'perception on AI', 'convergent thinking', 'creative problem-solving' and 'collaboration capability', and positive changes were verified for all four aspects.

A Study on Health Risk Assessment by Exposure to Organic Compounds in University Laboratory (대학 실험실에서의 유기화합물 노출에 의한 건강위험성 평가에 관한 연구)

  • Sim, Sanghyo;Won, Jung-II;Jeon, Hasub;Kim, Dowon
    • The Journal of Korean Society for School & Community Health Education
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    • v.22 no.4
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    • pp.49-60
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    • 2021
  • Objectives: Laboratories have various latent physical, chemical, biological, and ergonomical factors according to the diversification and fusion of research and development activities. This study aims to investigate the chemical exposure concentrations of college laboratories and evaluate their health risks, and use them as basic data to promote the health of college students. Methods: The sampling and analysis of harmful chemicals in the air in laboratories were performed using Method 1500 of the U.S. National Institute for Occupational Safety and Health (NIOSH)의 Method 1500. The harmful chemicals in the laboratories were divided into carcinogenic and non-carcinogenic chemicals. Risk assessment was performed using the cancer risk (CR) for carcinogenic chemicals and using the hazard index (HI) for non-carcinogenic chemicals. Results: The harmful chemicals in college laboratories consisted of acetone, diethyl ether, methylene chloride, n-hexane, ethyl acetate, chloroform, tetrahydrofuran, toluene, and xylenes. They showed the highest concentrations in laboratories A (acetone 0.001~2.34ppm), B (chloroform 0.95~6.35ppm), C (diethyl ether 0.08~8.68ppm), and D (acetone 0.07~14.96ppm). The risk assessment result for non-carcinogenic chemicals showed that the HI of methylene chloride was 2.052 for men and 2.333 for women, the HI of N-hexane was 4.442 for men and 5.05 for women. Thus, the HI values were higher than 1. The risk of carcinogenic chemicals is determined by an excess cancer risk (ECR) value of 1.0×10-5, which means that one in 100,000 people has a cancer risk. The ECRs of chloroform exceeded 1.0×10-5 for both men and women, indicating the possibility of cancer risk. Conclusion: College laboratories showed the possibility of non-carcinogenic health risks for methylene chloride, n-hexane, tetrahydrofuran (THF), toluene, and xylenes, and carcinogenic health risks for chloroform, methylene chloride. However, this study used the maximum values of measurements to determine the worst case, and assumed that the subjects were exposed to the corresponding concentrations continuously for 8 hours per day for 300 days per year. In consideration of the nature of laboratory environment in which people are intermittently exposed, rather than continuously, to the chemicals, the results of this study has an element of overestimation.

Domain Knowledge Incorporated Counterfactual Example-Based Explanation for Bankruptcy Prediction Model (부도예측모형에서 도메인 지식을 통합한 반사실적 예시 기반 설명력 증진 방법)

  • Cho, Soo Hyun;Shin, Kyung-shik
    • Journal of Intelligence and Information Systems
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    • v.28 no.2
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    • pp.307-332
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    • 2022
  • One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

Development and Validation of Digital Twin for Analysis of Plant Factory Airflow (식물공장 기류해석을 위한 디지털트윈 개발 및 실증)

  • Jeong, Jin-Lip;Won, Bo-Young;Yoo, Ho-Dong;Kim, Tag Gon;Kang, Dae-Hyun;Hong, Kyung-Jin
    • Journal of the Korea Society for Simulation
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    • v.31 no.1
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    • pp.29-41
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    • 2022
  • As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.

The Usage of Modern Information Technologies for Conducting Effective Monitoring of Quality in Higher Education

  • Oseredchuk, Olga;Nikolenko, Lyudmyla;Dolynnyi, Serhii;Ordatii, Nataliia;Sytnik, Tetiana;Stratan-Artyshkova, Tatiana
    • International Journal of Computer Science & Network Security
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    • v.22 no.1
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    • pp.113-120
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    • 2022
  • Information technologies in higher education are the basis for solving the tasks set by monitoring the quality of higher education. The directions of aplying information technologies which are used the most nowadays have been listed. The issues that should be addressed by monitoring the quality of higher education with the use of information technology have been listed. The functional basis for building a monitoring system is the cyclical stages: Observation; Orientation; Decision; Action. The monitoring system's considered cyclicity ensures that the concept of independent functioning of the monitoring system's subsystems is implemented.. It also ensures real-time task execution and information availability for all levels of the system's hierarchy of vertical and horizontal links, with the ability to restrict access. The educational branch uses information and computer technologies to monitor research results, which are realized in: scientific, reference, and educational output; electronic resources; state standards of education; analytical materials; materials for state reports; expert inferences on current issues of education and science; normative legal documents; state and sectoral programs; conference recommendations; informational, bibliographic, abstract, review publications; digests. The quality of Ukrainian scientists' scientific work is measured using a variety of bibliographic markers. The most common is the citation index. In order to carry out high-quality systematization of information and computer monitoring technologies, the classification has been carried out on the basis of certain features: (processual support for implementation by publishing, distributing and using the results of research work). The advantages and disadvantages of using web-based resources and services as information technology tools have been discussed. A set of indicators disclosed in the article evaluates the effectiveness of any means or method of observation and control over the object of monitoring. The use of information technology for monitoring and evaluating higher education is feasible and widespread in Ukrainian education, and it encourages the adoption of e-learning. The functional elements that stand out in the information-analytical monitoring system have been disclosed.