• Journal of vocational education research
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• v.35 no.6
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• pp.65-84
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• 2016

This study aims to explore the duty system of the lifelong learning counseling, and to analyze the needs of counseling practice which are conceived by lifelong education practitioners. Based on the related prior studies, the duty system of lifelong learning counseling was investigated and classified. Also, differences of how to recognize the importance of counseling job and how to practice counseling are assessed by Borich method. After data were collected by practitioners from lifelong education field, the dependent t-test and the Borich needs assessment formula were used for analysis of the collected data. The results are as follows: the 4 subdivided duties of lifelong learning counseling are formation of relationship, learner's analysis, learning promotion, and follow-up management. The 11 tasks are learner's interview, providing learning information, analysis of learner's characteristics and needs, learning level diagnosis, diagnosis of learning inhibiting factors, promotion of learning motivation, advice of learning course and learning method, support of study circle activity, career planning counseling, follow-up counseling, and counseling evaluation. According to the needs assessment, learner's analysis is conceived as the most important duty among the 4 sub-duties, and learner's analysis is regarded as second important duty by the counseling practitioners. Among the 11 tasks, providing learning information is the most important tasks among counseling practitioners, and analysis of learner's characteristics and needs is followed as second task. The duty system of the lifelong learning counseling and needs assessment data can be used as the basic data for lifelong education practitioners to conduct the duty of lifelong learning counseling efficiently and to support the lifelong learning plan according to learner's characteristics.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.39-45
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• 2019

The aim of this research is to find out how convergent operation of the learning coaching and compensation system affects the academic self-efficiency and learning performance of university students. In the second semester, a compensation system was prepared based on learning coaching and learning outcomes, made a notice in advance, and conducted a survey before and after operation to measure the academic self-efficacy. In addition, the MLST-II Learning Strategy Diagnosis Examination was conducted on G university students to diagnose the learning tendency. As a result, although G University students felt a reluctance by coaching the learning community and expected negative results during the course of participation in the learning community due to low motivation and low expectation of results, they showed a significant improvement in academic self-efficiency and learning outcomes. Therefore, even students with negative learning tendency will need to consider how to operate these programs in the educational field, as the expert's learning coaching and compensation systems produce positive results for students' academic self-efficiency and learning outcomes rather than leaving them to autonomy.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.173-178
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• 2020

In the near future, as artificial intelligence and computing network technology develop, collaboration with artificial intelligence (AI) will become important. In an AI society, the ability to communicate and collaborate among people is an important element of talent. To do this, it is necessary to understand how artificial intelligence based on computer science works. An algorithmic education focused on problem solving and learning is efficient for computer science education. In this study, the results of an assessment of computational thinking at the beginning of the semester, a satisfaction survey at the end of the semester, and academic performance were compared and analyzed for 28 students who received algorithmic education focused on problem-solving learning. As a result of diagnosing students' computational thinking and problem-solving learning, teaching methods, lecture satisfaction, and other environmental factors, a correlation was found, and regression analysis confirmed that problem-solving learning had an effect on improving lecture satisfaction and computational thinking ability. For algorithmic education, if you pursue a problem-solving learning technique and a way to improve students' satisfaction, it will help students improve their problem-solving skills.

• 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.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.267-273
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• 2024

Using a cloud-based vertex AI platform that can develop an artificial intelligence learning model without coding, this study easily developed an artificial intelligence learning model by the non-professional general public and confirmed its clinical applicability. Nine dental diseases and 2,999 root disease X-ray images released on the Kaggle site were used for the learning data, and learning, verification, and test data images were randomly classified. Image classification and multi-label learning were performed through hyper-parameter tuning work using a learning pipeline in vertex AI's basic learning model workflow. As a result of performing AutoML(Automated Machine Learning), AUC(Area Under Curve) was found to be 0.967, precision was 95.6%, and reproduction rate was 95.2%. It was confirmed that the learned artificial intelligence model was sufficient for clinical diagnosis.

• Communications of Mathematical Education
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• v.12
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• pp.411-422
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• 2001

대학수학에서 학생들의 글쓰기를 통해 수학전반에 대한 학습진단, 느낌, 대책, 자기경험등 여러가지를 발표토록하여 바람직한 수학관을 갖고 수학학습태도를 기르도록 도움을 줄 기회를 갖게 하며, 수학이 중요하고 필요함을 깨우쳐 수학이 그들 인생의 동반자가 되도록 한다.

• 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.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.285-288
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• 2006

Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to teaming algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generation turbine and power turbine are considered for estimation for performance deterioration of a complex component at design point was conducted. As a result of that, complex defect diagnostics has been conducted. As a result, the accuracy of diagnostics were verified with its relative error with in 10% at each component.

• School Mathematics
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• v.5 no.2
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• pp.209-221
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• 2003

This study focuses on the necessity of developing the material for teachers who are involved in diagnosing and prescribing students' mathematical errors. And it also intends to stimulate the related research of this area. For this, it tries to suggest the fundamental components-(1)types and frequencies of errors, (2) diagnostic test kit, (3)causes of errors, (4)ideas for prevention, (5)ideas for correction, (6)practice for settlement, and (7) performance test kit and frame of the teaching guide book for the teachers according to the general procedure of diagnosis and prescription. Finally it provides the concrete research areas for the future study.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1249-1256
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• 2018

Recently the research on artificial intelligence is actively processing in the fields of diagnosis and prediction. In this paper, we acquire the data of electrical current, revolution per minute (RPM) and vibration that is occurred in the motor and pump where hey are installed in the industrial fields. We train the acquired data by using the k-nearest neighbors. Also, we propose the status diagnosis methods that judges normal and abnormal status of motor and pump by using the trained data. As a proposed result, we confirm that normal status and abnormal status are well judged.