• Journal of the Korean Chemical Society
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• v.51 no.2
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• pp.186-192
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• 2007

In this study, the effects of concept mapping on the preservice elementary teachers' achievement, conceptual understanding, anxiety toward science, and science teaching efficacy belief were investigated in the undergraduate general chemistry course. The aptitude-treatment interaction (ATI) between preservice teachers' learning approach and concept mapping strategy was also investigated. Sixty-nine freshmen from a university of education were assigned to a control group and a treatment group. Tests regarding students' learning approach, anxiety toward science, and science teaching efficacy belief were administered as pretests. Treatment lasted for 9 weeks. In every class, students in the treatment group constructed concept maps, while those in the control group solved the problems of the textbook after the lecture. After the instructions, tests of achievement, conceptual understanding, anxiety toward science, and science teaching efficacy beliefs were administered. The results indicated that students in the treatment group significantly outperformed those of the control group in the achievement test. In the conceptual understanding and the science teaching efficacy beliefs, however, no statistically significant differences were found between two groups. Students of the treatment group showed significantly higher anxiety than their counterpart in the test of anxiety toward science. No aptitudetreatment interaction between students' learning approach and the concept mapping strategy was found.

• Journal of Science Education
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• v.37 no.1
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• pp.221-232
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• 2013

The purpose of this study was to examine the effect of the CoRe-based density unit class on conceptual formation and on learner satisfaction with the class. For this study, two hundred and forty 8th grade students were chosen from six classes. The students were divided into two groups: an experimental group, which received a CoRe-based density unit lesson, and a control group, which was taught based on traditional teaching method. The CoRe-based density unit classes consisted of 4 periods based on the analysis of the previous studies on CoRe about density. The results showed the meaningful significant difference between the CoRe-based classes and the classes based on traditional teaching method both in the posttest on the extent of the conceptual formation on the density and in the retention test. The difference suggests that the lesson with CoRe is based on the consideration of the difficulties and limitations students face in various fields such as the students themselves, teachers, learning environment, evaluation, etc. during their learning process and even in the types of preconception they have, and the CoRe-based lesson is centered around the best teaching strategies to solve such difficulties. As a result of the analysis on the experimental group's class satisfaction, it is revealed that the students with a high level of attitudes related science or with a high level of science achievement showed especially high satisfaction in their learning. Analysis of questionnaire survey showed that the students in the experimental group got the opportunity through CoRe-based lesson to stretch their thoughts and ideas in a free way and preferred a teaching method which didn't just show the concept, but allowed them to find it for themselves or which let them predict the solution and then confirm the result on their own and a lesson which encouraged their active participation.

• Journal of the Korean Chemical Society
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• v.54 no.2
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• pp.248-256
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• 2010

This study investigated the effects of the level of enrichment for analogies upon students' mapping, conceptual understanding, and the types of mapping errors in concept learning about Boyle's Law. Analogical reasoning ability test was administered and the score was used as a blocking variable. Three types (simple, enriched, and extended analogies) of learning materials according to the level of enrichment for analogies were studied by randomly assigned middle school students, and a conceptions test and a mapping test were administered immediately. The retention tests of both were administered four weeks later. Analyses of the results revealed that there was no main effect in the level of enrichment for analogies, but there was interaction effect with analogical reasoning ability in the post test on mapping. And the score of enriched analogy group was significantly higher than those of simple analogy group, but the score differences among three groups were not significant in the retention test on conceptual understanding. The frequency of the total mapping errors in the simple analogy group was the highest, and the frequencies of most types of mapping errors in the enriched and the extended analogy groups were less than those in the simple analogy group. There were also some differences in the frequencies of mapping errors with respect to the level of analogical reasoning ability. Therefore, these results will help science teachers plan and practice instructions using analogy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• The Korean Journal of Emergency Medical Services
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• v.9 no.2
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• pp.207-221
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• 2005

Purpose: The purpose of this study was to develop and apply a simulation-problem based learning(S-PBL) package in basic life support(BLS). Methods: This study was used to developed BLS' S-PBL package throughout 12 steps of PBL package development model. Then, BLS' S-PBL methodology was implemented in second year student in the undergraduate emergency medical technology, and survey was done. Results: 1. S-PBL package model was presented based on conceptual model II of PBL ; PEL for professional action. 2. Quantitative analysis of survey was to the effectiveness of learning, 3.59 points ; 4.15 of BLS and 3.84 of integration and practical use of knowledge. 3. As to the satisfaction of student, S-PBL package management, tutor and self-satisfaction' score was 3.59, 3.82, 3.39 respectively. Conclusion: This study was suggested that S-PBL education would be necessary with improved tutor skill and achieved advantage of simulation and PBL.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.

• Research in Mathematical Education
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• v.22 no.2
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• pp.135-152
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• 2019

This conceptual paper proposes a conceptualization regarding teacher candidates' experiences as learners during instructional activities implemented by teacher educators in practice-based teacher education programs. We argue that the current learning cycle framework for teacher candidates to engage in core teaching practices does not fully address teacher candidates' own learning experiences as learners. To provide a rationale for our proposal, we examine the current conceptualization of learning to enact core practices and suggest the need for integrating teacher candidates' experiences into the current conceptualization. We also draw on research on figured worlds as an effort to conceptualize teacher candidates' experiences coming from multiple figured world. We present some examples from our own mathematics methods courses to illustrate how this newly proposed framework can be used in practice and share remaining questions for future research.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.312-316
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• 2022

The article provides a theoretical substantiation of the pedagogical interaction of the subjects of the educational process in the context of distance learning; taking into account the identified features of the implementation of pedagogical interaction defined teaching methods in distance learning; a course has been developed that reveals the features of the pedagogical interaction of participants in the educational process in conditions of distance learning. To solve the tasks and check starting points, a set of methods was used: theoretical: analysis of philosophical, psychological and pedagogical literature, dissertation research, curricula, analysis of the conceptual and terminological system; empirical: questioning, conversation, self-diagnosis.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• Journal of The Korean Association For Science Education
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• v.40 no.4
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• pp.385-398
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• 2020

This study aims to examine genetics problem-solving processes of high school students with different learning approaches. Two second graders in high school participated in a task that required solving the complicated pedigree problem. The participants had similar academic achievements in life science but one had a deep learning approach while the other had a surface learning approach. In order to analyze in depth the students' problem-solving processes, each student's problem-solving process was video-recorded, and each student conducted a think-aloud interview after solving the problem. Although students showed similar errors at the first trial in solving the problem, they showed different problem-solving process at the last trial. Student A who had a deep learning approach voluntarily solved the problem three times and demonstrated correct conceptual framing to the three constraints using rule-based reasoning in the last trial. Student A monitored the consistency between the data and her own pedigree, and reflected the problem-solving process in the check phase of the last trial in solving the problem. Student A's problem-solving process in the third trial resembled a successful problem-solving algorithm. However, student B who had a surface learning approach, involuntarily repeated solving the problem twice, and focused and used only part of the data due to her goal-oriented attitude to solve the problem in seeking for answers. Student B showed incorrect conceptual framing by memory-bank or arbitrary reasoning, and maintained her incorrect conceptual framing to the constraints in two problem-solving processes. These findings can help in understanding the problem-solving processes of students who have different learning approaches, allowing teachers to better support students with difficulties in accessing genetics problems.