• Title/Summary/Keyword: 발견학습

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Bio-marker Detector and Parkinson's disease diagnosis Approach based on Samples Balanced Genetic Algorithm and Extreme Learning Machine (균형 표본 유전 알고리즘과 극한 기계학습에 기반한 바이오표지자 검출기와 파킨슨 병 진단 접근법)

  • Sachnev, Vasily;Suresh, Sundaram;Choi, YongSoo
    • Journal of Digital Contents Society
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    • v.17 no.6
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    • pp.509-521
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    • 2016
  • A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

Designing the Instructional Framework and Cognitive Learning Environment for Artificial Intelligence Education through Computational Thinking (Computational Thinking 기반의 인공지능교육 프레임워크 및 인지적학습환경 설계)

  • Shin, Seungki
    • Journal of The Korean Association of Information Education
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    • v.23 no.6
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    • pp.639-653
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    • 2019
  • The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.

Effects of Primary ELLs' Affective Factors and Satisfaction through AI-based Speaking Activity (인공지능 기반 말하기 학습이 초등영어학습자들의 정의적 특성과 학습 만족도에 미치는 영향)

  • Yoon, Tecnam;Lee, Seungbok
    • The Journal of the Korea Contents Association
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    • v.21 no.9
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    • pp.34-41
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    • 2021
  • The purpose of this study is to explore any effects of primary English language learners' affective factors and satisfaction through AI-based speaking activity. In order to answer these questions, a total number of 46 ELLs from a public elementary school participated in this research. Survey questionnaire on affective factors and learning satisfaction were distributed and the results were analyzed quantitatively. The findings are as follows. First, participants could expand their knowledge on AI-based activity towards its educational advantages and capability. Second, overall affective factors of the participants on AI-based activity changed positively, with the improvement of the mean score. The paired samples t-test showed that there was a significant difference among interest, value and attitude. Third, the satisfaction degree on AI-based learning escalated, particularly in the sense of efficacy, academic achievement and involvement. Lastly, it was revealed that the satisfaction degree was correlated with learners' self-confidence, interest and attitude.

Case studies on the flipped classroom with a MOOC in college contexts (대학에서의 MOOC기반 플립러닝 사례분석)

  • Lim, Keol;Kim, Mi Hwa
    • Journal of Digital Convergence
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    • v.17 no.9
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    • pp.173-184
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    • 2019
  • This study investigated the effects of applying the flipped classroom approach with MOOC to the college educational system. A total of six undergraduate students participated in the 10-week innovative learning setting. The participants performed online activities using the learning content from a MOOC website; this was followed by a participatory learning process in the offline classroom. The semi-structured face-to-face interviews for the six participants after the classes were completed and analyzed. The results showed that the instructional method enabled students to be highly motivated and to perform learning activities. However, there were some limitations: (1) learning was impeded due to English language issues and (2) the Korean education culture was still unfamiliar with this pedagogical method. Finally, suggestions for future research are discussed.

The Developement of Liver cancer Vital Sign Information Prediction System using Aptamer Protein Biochip (압타머 단백질 바이오칩을 이용한 간암 진단 생체 정보 예측 시스템 개발)

  • Kim, Gwang-Jun;Lee, Hyoung-Keun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.6 no.6
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    • pp.965-971
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    • 2011
  • As the liver cancer in our country cancerous occurrence frequency to be the gastric cancer in the common cancer, If the case which will be discovered in early rising the treatment record was considered seriously about under the early detection. The system which it sees with the system for the early detection of the liver cancer reacts the blood of the control group other than the patient who is confirmed as the liver cancer and the liver cancer to the biochip and aptamer protein biochip profiles mechanical studying leads and it is a system which it classifies. 1149 each other it reacted blood samples of the control group other than the liver cancer patient who is composed of the total 85 samples and the liver cancer which is composed of 310 samples to the biochip which is composed with different oligo from the present paper and it was a data which it makes acquire worker the neural network it led and it analyzes the classification efficiency of the result 95.38 ~ 97.95% which it was visible.

SSI Education and Scientific Literacy from a Lifelong Learning Perspective (평생학습적 시각을 통해 바라본 SSI 교육과 과학적 소양)

  • Park, Shin-Hee;Kim, Chan-Jong
    • Journal of The Korean Association For Science Education
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    • v.42 no.1
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    • pp.61-75
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    • 2022
  • Recently, lifelong learning ability was newly proposed as scientific literacy, the goal of the science curriculum. To solve various science-related problems students encounter in life, lifelong learning abilities related to science beyond school science education are required, but empirical evidence shows that students can solve problems they actually face through scientific literacy. It is not easy to find in the existing science education research. In addition, there is a lack of discussion on how to cultivate lifelong learning ability suggested in the curriculum through school science education. In this study, attention was paid to SSI education as a method for students to cultivate lifelong learning ability through school science education and to develop their ability to solve science-related problems encountered in life. In this context, statements in the existing SSI education studies were reviewed to discover discourses related to lifelong learning, and their types and characteristics were distinguished. It was possible to confirm lifelong learning and its applicability with focus on science education research through this. For the study, 18 literature materials on the subject of SSI education were selected, and the discourses related to lifelong learning in the SSI education research were discovered by examining the statements revealed in the data. As a result of the study, there are four categories of discourses related to lifelong learning: 'awareness of science,' 'connection between science and everyday life', 'promotion of participatory citizenship', and 'construction of identity'. Various SSI education studies have already had lifelong learning perception in various contexts, and the four types of discourses related to lifelong learning could be linked to the four types of learning presented in the UNESCO Lifelong Learning Report. SSI education tends to view students' life experiences as part of their learning and aims to help students develop the character and capacity to make responsible decisions on social issues related to science and put them into practice. This competency can be continuously connected to the real-life of students outside of school as a lifelong learning ability. This study requires expanding the discourse related to lifelong learning in science education and operating and managing the overall educational system to foster students' lifelong learning ability.

Comparative Comprehension of Men Learning by the Principles of Complex System and the Book of Changes (복잡계의 원리와 주역의 사유방식이 주는 교육에의 시사점)

  • Park, Hye jeong;Do, Yeong ae
    • Korean Educational Research Journal
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    • v.41 no.1
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    • pp.59-79
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    • 2020
  • Men learning has no fixed route. In other words, any route can be taken, which can also be seen in the structure of other "complex systems" discussed in modern society. It can also be examined through Yang's long-standing classic, The Book of Changes Men learning itself started from informal learning to become today's formal learning. As we look at the stages of human civilization's progress, we can quickly discover these stages of development. The issue of human beings has always been a topic of discussion, and these discussions are ongoing. Men learn through language and tools, technology and culture, and through philosophy, art, and religion to deal with their complex and diverse mental world. Through these various activities, learning is accomplished. This is not limited to the physical processes of one generation learning through inheriting knowledge; men's learning, a kind of mental process, has extended our life. This is why there is no other reason that men's minds and learning are always developing. This study is about how to learn in a complex and diversified modern society and to find out how to coexist with the principles of the "complex system" and The Book of Changes.

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Learning with information in an infomration-rich environment (풍부한 정보 환경에서 정보와 함께 하는 학습: 인지기술 활용을 중심으로)

  • Chung, Jin-Soo
    • Journal of the Korean Society for information Management
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    • v.20 no.4 s.50
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    • pp.135-158
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    • 2003
  • The Purpose of this study is to investigate how information use contributes to learning. Conducted as part of a larger study, this study focuses on learning by analyzing students' use of cognitive skills during the Process of using information. Within the broad methodological framework of qualitative research in constructivist paradigm (Guba and Lincoln, 1998), the study applied the revised Bloom's taxonomy (Anderson and Krathwohl, 2000) as a particular framework to understand the Phenomenon. Participants included 21 high school juniors in an honors' class of persuasive speech. The study's combinational use of two techniques -concept mapping and individual interview - in a naturalistic setting Proved to be the unique methods for researching the reflection of information use in learning Products. The results revealed that changes in students' understanding occured in four types - simple, analytic, organizational, and holistic changes. The analysis using the revised Bloom's taxonomy showed that a variety of cognitive skills were used during the whole process of information use and that the use of higher levels of cognitive skills is particularly crucial.

A Study of the Thematically Integrated Information Literacy Curriculum for Strengthening its Relationship with Curricula (교과 연계성 강화를 위한 학습주제 중심의 통합 정보활용교육과정에 관한 연구)

  • Song, Gi-Ho;Kim, Tae-Soo
    • Journal of the Korean Society for information Management
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    • v.25 no.3
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    • pp.41-64
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    • 2008
  • This study sought to develop an integrated information literacy curriculum that would have a strong relationship with curricula through the standard themes abstracted from theme network structures, scan and cluster analyses of the information literacy curricula. In addition, this study also attempted to develop a teaching-learning model for the developed integrated information literacy curriculum. This study utilized the themes of information literacy instruction that have interdisciplinary characteristics as analysis criteria in analyzing the commonality of information literacy instruction and the subject curricula. The following characteristics were found from the analyzing the areas of commonality. Foremost, the first themes(the fields of basic learning skills and nature) which belongs to the fields of information society, library, information technology, collaborative skills were found to have many relationships with the subject curricula. Next, the second themes(the field of information problem solving capabilities) which is the core field of information literacy instruction showed a weak relationship with the subject curricula.

A Study on Conversational AI Agent based on Continual Learning

  • Chae-Lim, Park;So-Yeop, Yoo;Ok-Ran, Jeong
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.1
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    • pp.27-38
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    • 2023
  • In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.