• The Journal of Korean Association of Computer Education
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• v.20 no.2
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• pp.1-11
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• 2017

The demands of computer science education for non-majors in higher education is increasing but relevant evaluation tools for the students' computational artifacts are lack. This research aims to develop a scoring rubric to assess student's computational artifacts in non-major programming course at Computational Thinking point of view. The rubric was developed based on 'CT Practice Design Pattern' as a framework. The rubric consists of 'domain, skills, evaluation, evaluating resources, and scales'. Domains are 'Design of abstract model', 'Design and application of creative artifacts', and 'Analysis of the artifacts'. Experts reviewed the rubric to ensure contents validity. The rubric is resulted in reliable for consistency. This rubric can be revised and applied to application environment accordingly.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.355-367
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• 2018

The purposes of this study are 1) to identify systems thinking level and definition, 2) to develop a framework for the assessment of systems thinking level, and 3) to develop a rubric for scoring open-ended written responded test. In order to achieve these purposes, a total of 60 articles were analyzed by using the literature analysis framework. The systems thinking level and definition are identified through the results of systems thinking literature analysis. Based on the systems thinking level and definitions, the research derived a framework that includes the core ideas and evaluation content of each level. In addition, rubric for the scoring of open-ended response test items was revised and supplemented. It is concluded that a content validity test on the tools (systems thinking level and definition, framework for item development, rubric) has been developed in the study. The content validity was verified by 7-science education experts. According to the result of CVI, it was found to be more than .95 in all three tools. Based on the results of this study, the research will develop items that can measure students' level of systems thinking. The construct validity and criterion validity of the developed items should be verified systematically. The research could carry out a validation study for the systems thinking measurement related to the core competence emphasized in the 2015 revised curriculum.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.624-626
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• 2023

Credit scoring is a technique used by financial institutions to assess the creditworthiness of potential borrowers. This involves evaluating a borrower's credit history to predict the likelihood of defaulting on a loan. This paper presents an ensemble of two Transformer based models within a framework for discriminating the default risk of loan applications in the field of credit scoring. The first model is FinBERT, a pretrained NLP model to analyze sentiment of financial text. The second model is FT-Transformer, a simple adaptation of the Transformer architecture for the tabular domain. Both models are trained on the same underlying data set, with the only difference being the representation of the data. This multi-modal approach allows us to leverage the unique capabilities of each model and potentially uncover insights that may not be apparent when using a single model alone. We compare our model with two famous ensemble-based models, Random Forest and Extreme Gradient Boosting.

• Journal of Cardiovascular Imaging
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• v.31 no.1
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• pp.1-17
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• 2023

The Coronary Artery Calcium Data and Reporting System (CAC-DRS) is a standardized reporting method for calcium scoring on computed tomography. CAC-DRS is applied on a per-patient basis and represents the total calcium score with the number of vessels involved. There are 4 risk categories ranging from CAC-DRS 0 to CAC-DRS 3. CAC-DRS also provides risk prediction and treatment recommendations for each category. The main strengths of CAC-DRS include a detailed and meaningful representation of CAC, improved communication between physicians, risk stratification, appropriate treatment recommendations, and uniform data collection, which provides a framework for education and research. The major limitations of CAC-DRS include a few missing components, an overly simple visual approach without any standard reference, and treatment recommendations lacking a basis in clinical trials. This consistent yet straightforward method has the potential to systemize CAC scoring in both gated and non-gated scans.

• Journal of Distribution Science
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• v.19 no.2
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• pp.65-75
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• 2021

Purpose: During the pandemic, a large number of orders forced online retailers of fresh produce to quickly change their emergency logistics capabilities to meet the needs of ordinary consumers during the pandemic. Our research aims to help online retailers establish an emergency physical distribution framework for fresh produce during disasters to meet consumer needs. Research design and methodology: 160 effective responses were collected from the online response team in Wuhan, China, and exploratory factor analysis was used to determine the emergency logistics capability framework. Twelve experts were invited online to collect their scoring opinions and use the entropy method to determine the importance of emergency logistics capabilities. Results: Our results have identified a total of 17 emergency logistics factors for online retailers, and we found that Transportation route planning and reconstruction capabilities, Emergency plan planning ability, and Supply chain real-time information sharing capability are the most important in the overall framework. Conclusions: This research completely established the physical distribution framework of fresh agricultural products online retailer in emergency situations. It enriches academic resources in the field of emergency distribution and provides a scientific basis for corporate managers to improve their physical distribution capabilities in emergency situations.

• Journal of The Korean Association For Science Education
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• v.42 no.2
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• pp.239-252
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• 2022

This study aims to develop performance criteria based on characteristics observed in science inquiry tasks for elementary school students. First, the performance characteristics by observing 70 fifth-grade elementary school students' science inquiry activity report are listed. Second, the checklist-type scoring criteria in connection with the theoretical framework of scientific inquiry process and relevant competencies are developed. Third, with the developed scoring criteria, 11 raters participate in scoring 350 students' reports. The main findings are as follow: first, the scoring data are well-fitted for the many-faceted Rasch model, and 22 scoring criteria are reasonably-well differentiated for various levels of proficiency. Second, at low performance level, observable characteristics are to answer questions explicitly required by the task or to observe objects or phenomena using pre-learned scientific concepts, while at high performance level, to explore additional data other than given data or to reflect on one's experimental process. Based on the results, the usefulness of analyzing students' performance characteristics for developing the scoring criteria, and further research directions are discussed.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.3-8
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• 1998

The present work proposes the potential fuzzy framework, based on fuzzy set theory, for supporting decision-making problems, especially, selection problems of a best design in the area of nuclear energy system. The framework proposed is composed of the hierarchical structure module, the assignment module, the fuzzification module, and the defuzzification module. In the structure module, the relationship among decision objectives, decision criteria, decision sub-criteria, and decision alternatives is hierarchically structured. In the assignment module, linguistic or rank scoring approach can be used to assign subjective and/or vague values to the decision analyst's judgment on decision variables. In the fuzzification module, fuzzy numbers are assigned to these values of decision variables. Using fuzzy arithmetic operations, for each alternative, fuzzy preference index as a fuzzy synthesis measure is obtained. In the defuzzification module, using one of methods ranking fuzzy numbers, these indices are defuzzified to overall utility values as a cardinality measure determining final scores. According these values, alternatives of interest are ranked and an optimal alternative is chosen. To illustrate the applicability of the framework proposed to selection problem, as a case example, the best option choice of four design options under five decision criteria for primary containment wall thickening around large penetrations in an advanced nuclear energy system is studied.

• Management & Information Systems Review
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• v.19
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• pp.1-15
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• 2006

The concept of portfolio is rarely understood and used in R&D management field. The conventional management technique in selecting R&D projects is scoring each projects and choosing projects based on the scores which are determined during evaluation. As a collection of good stocks is not necessarily a good stock portfolio, a collection of good R&D projects is not always a good R&D project portfolio. In this paper, framework and practical technique for constructing a R&D project portfolio are introduced. This technique can be easily applied in private and plublic R&D institutes.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.871-880
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• 2011

The purpose of this research is to explore preservice earth science teachers' understanding of volcanic systems using a modified version of InVEST Volcanic Concept Survey (InVEST VCS, Parham et al., 2010). Results showed that participants' understanding of volcanic concepts was rather limited. Questions requiring only basic content knowledge (e.g., terminology associated with volcano) received high scoring responses, while questions requiring higher order thinking and deeper conceptual connections as the mechanics of volcanic eruption received low scoring responses. Specifically, the prediction of hazards and impacts on the environment appeared to be poorly understood. VCS results can be applied to improve the subject content knowledge as well as the pedagogical knowledge that instructors may use when they assess students' understanding of volcanism within a solid conceptual framework.

• Korean Journal of Comparative Education
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• v.28 no.2
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• pp.77-95
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• 2018

This study introduces the Classroom Assessment Scoring System (CLASS) and explores the characteristics of CLASS for observing classroom. The CLASS is a standardized observation instrument that was largely developed for use in the USA. The CLASS attempts to provide a conceptual framework for categorizing classroom interactions and consists of three broad domains of quality (emotional supports, classroom organization, instructional supports). We simulated this method to the elementary school classes. The professional-teacher makes the best use of student's initiation behaviors, and the novice teacher focused on the leading the contents of subject. The novice teacher tyr to make more positive climate and to present more frequent feedback to students than professional teacher's classroom. The professional teacher would like to reveal the student's opinions, questions and subtle emotional state. The CLASS can be used to collect data on a wide range of specific aspects of the teaching and learning process at any given time.