• Journal of the Korean Chemical Society
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• v.55 no.6
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• pp.1042-1055
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• 2011

The purpose of this study was to compare the conceptual and algorithmic problem solving ability on Boyle's law and Charles's law according to cognitive levels and characteristics of students in middle school 1st grade students. For this study, questionnaire items of conceptual and algorithmic problem solving ability were developed. and the problem solving ability according to cognitive levels and characteristics of students was compared. The long-term memory effect in conceptual and algorithmic problem solving ability according to cognitive levels was investigated, and problem solving process were analyzed by questionnaire items. In the results of this study, conceptual problem solving ability was higher than algorithmic problem solving ability in all cognitive levels. There was statistically significant difference in concrete operational period and transitional period students. In comparison of the long-term memory effect in conceptual and algorithmic problem solving ability, formal operational period students had the long-term memory effect. There was no statistically significant difference in the conceptual and algorithmic problem solving ability according to private education among the characteristics of students. But there was statistically significant difference in the problem solving ability according to experiences of the scientific activities and hopes to related scientific careers. From results of analysis of problem solving process, it is known that the students had a tendency to just remember macroscopic phenomena and to solve the problems without understanding the concepts. Therefore, teaching and learning strategy is necessary to replace unscientific concepts by the scientific concepts through identifying students's unscientific concepts in advance.

• Journal of The Korean Association For Science Education
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• v.20 no.2
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• pp.214-220
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• 2000

The difference (bias) between self-efficacy and chemistry problem-solving ability was investigated for 96 (male: 48, female: 48) high school students. A self-efficacy instrument was administered, which asked the confidence in solving algorithmic and conceptual problems successfully. Their chemistry problem-solving ability was then assessed with 10 algorithmic and 10 conceptual problems as same in the self-efficacy instrument. Although students had higher scores in the algorithmic problems, no significant difference was found in the self-efficacy to solve the two different forms of problems. Therefore, the bias scores in the conceptual problems were higher than those in the algorithmic problems. Two-way ANOVA results for the bias in the algorithmic problems revealed a significant interaction between gender and the previous achievement level. Analysis of simple effects indicated that the bias scores of high-achieving boys were significantly higher than those of high-achieving girls. While most high-achieving boys were in the overconfident category, high-achieving girls were more likely to be in the underconfident category.

• Journal of The Korean Association For Science Education
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• v.24 no.2
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• pp.320-326
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• 2004

This study investigated whether algorithmic problem solving and conceptual problem solving influenced each other or not. Four classes of 12th grade (N= 112) that are equal in prior achievement were randomly assigned to group AC (Algorithmic-Conceptual problem) and group CA (Conceptual-Algorithmic problem). Students of group AC solved the conceptual problems after learning the related algorithmic problems, and those of group CA solved the same problems in reverse order. The results revealed that learning the algorithmic problems improved students' ability to solve the related conceptual problems, but learning the conceptual problems did not help students solve the related algorithmic problems. Regarding the confidence on problem solving, learning the algorithmic problems had little effect on the related conceptual problems. Learning the conceptual problems also had little effect on students' confidence on solving of the related algorithmic problems.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.79-87
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• 2005

We compared algorithmic problem solving and conceptual understanding of chemistry with three types (algorithmic, pictorial- and wordy-formatted conceptual) of problems. The familiarity, confidence, and preference to the three type of problems were also examined. The chemistry problem solving ability test was administered to 228 students from two top high schools in the province of Gyeonggi who were preparing the chemistry examination among the four optional subjects (biology, chemistry, earth science, physics) for enter university. After administrating the chemistry problem solving ability test, the degree of familiarity to some problems and the degree of confidence of their answers in a Likert scale were asked to the students. Besides, the students were asked to place preference to the type of problems in order. The students scored better on the algorithmic problems than on the conceptual problems (pictorial and wordy problems), and were also most familiar with the algorithmic problems. The students were more confident of their answers on both of types pictorial and algorithmic problems, and preferred pictorial problems rather than both of types algorithmic and wordy problems.

• Journal of the Korean Chemical Society
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• v.44 no.1
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• pp.68-73
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• 2000

In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.

• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.1-8
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• 2006

This study investigated the causal relationships between high school student multiple-choice algorithmic chemistry problem solving and 1) the motivational variables of achievement goal (task goal/performance goal/performance-avoidance) and perceived ability, and 2) the cognitive variables of learning strategy (deep learning/surface learning) and self-regulation. Path analysis supported a causal model in which perceived ability and task goal were found to positively influence algorithmic chemistry problem-solving ability via self-regulation. In particular it was found that perceived ability directly influenced algorithmic chemistry problem-solving ability. Moreover, deep learning was found to have been influenced by perceived ability and task goal, while surface learning was influenced by performance-avoidance goal. Lastly, there did not appear to be any causal relationship between learning strategy and algorithmic chemistry problem-solving ability.

• School Mathematics
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• v.18 no.3
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• pp.503-526
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• 2016

The study aimed at determining the identity of mathematics essay test in the university entrance examination. For this purpose, a document research was conducted for higher order thinking and mathematics essay ability and it analyzed the goal of assessment and the tendency of problem settings and looked into mathematics essay problems of twenty-five universities. As a result, the study found out that evaluation factors of mathematics essay test requires higher order thinking ability including mathematical knowledge and essay ability such as mathematical knowledge, understanding, problem solving, logical and critical thinking, creative ability, power of expression, argument skills. Also, problems from previous mathematics essay tests were set mainly to assess mathematical knowledge, understanding and problem solving. Based on the findings, the past mathematics essay tests in university entrance examination in Korea that require logical and critical thinking, creative ability, power of expression, argument skills were a rather small percentage of questions.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1555-1559
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• 2008

소수력은 국내의 풍부한 부존량을 바탕으로 과거부터 관심을 받아왔으나 대수력에 비해 상대적으로 낮은 경제성이나 하천에 미치는 환경 생태적 영향 등의 이유로 개발이 활성화되지는 못하였다. 최근에는 기후변화협약(1992)이나 교토의정서(1997) 채택 등으로 온실가스 감축문제가 국제적인 이슈가 되면서 신재생에너지 중에서도 탄소배출량이 가장 적은 소수력발전에 대한 관심이 점차 증대되고 있는 상황이다. 그러나 점차 높아지는 환경수요는 대수력에 비해 상대적으로 환경영향이 작은 소수력발전소 건설에도 문제제기를 하기 시작하였으며, 정부의 자금지원에 의존한 '비싼' 전력생산을 회의적 시각으로 바라보는 측면도 존재하고 있다. 본 연구의 목적은 소수력 개발의 장애요인들을 극복하고 우리나라의 풍부한 소수력 부존량을 적극 활용하기 위한 향후 소수력 개발 활성화 방향을 제시하는 것이다. 이를 위해서 소수력발전소의 레크리에이션 기능 활성화, 주변지역의 지원 활성화, 수리권 문제의 해결, 환경친화적인 개발, 신규편익의 발굴 및 계량화, 등을 주요 방향 및 과제로 제시하였다.

• The Mathematical Education
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• v.48 no.2
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• pp.149-167
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• 2009

This study was aimed to examine problem-solving ability of fifth graders on two types of mathematical essay problems, and to analyze the process of mathematical justification in solving the essay problems. For this purpose, a total of 14 mathematical essay problems were developed, in which half of the items were single tasks and the other half were data-provided tasks. Sixteen students with higher academic achievements in mathematics and the Korean language were chosen, and were given to solve the mathematical essay problems individually. They then were asked to justify their solution methods in groups of 4 and to reach a consensus through negotiation among group members. Students were good at understanding the given single tasks but they often revealed lack of logical thinking and representation. They also tended to use everyday language rather than mathematical language in explaining their solution processes. Some students experienced difficulty in understanding the meaning of data in the essay problems. With regard to mathematical justification, students employed more internal justification by experience or mathematical logic than external justification by authority. Given this, this paper includes implications for teachers on how they need to teach mathematics in order to foster students' logical thinking and communication.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.98-98
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• 2023

ChatGPT(Chat과 Generative Pre-trained Transformer의 합성어)는 사용자와 주고받는 대화의 과정을 통해 질문에 답하도록 설계된 대형언어모델로, 지도학습과 강화학습을 모두 사용하여 세밀하게 조정된 인공지능 챗봇이다. ChatGPT는 주고받은 대화와 대화의 문맥을 기억할 수 있으며, 보고서나 실제로 작동하는 파이썬 코드를 비롯한 인간과 유사하게 상세하고 논리적인 글을 만들어 낼 수 있다고 알려져있다. 본 연구에서는 수자원시스템분야의 문제해결에 있어 ChatGPT의 적용가능성을 사례기반으로 확인하고, ChatGPT의 올바른 활용을 위해 필요한 사항에 대해 고찰하였다. 수자원시스템분야의 대표적인 연구주제인 상수관망시스템의 누수인지와 수리해석을 통한 문제해결에 ChatGPT를 활용하였다. 즉, 딥러닝 기반의 데이터분석을 활용한 누수인지와 오픈소스기반의 수리해석 모델을 활용한 관망시스템 적정 분석을 목표로 ChatGPT와 대화를 진행하고, ChatGPT에 의해 제안된 코드를 구동하여 결과를 분석하였다. ChatGPT가 제시한 코드의 구동결과를 사전에 연구자가 직접 구현한 코드구동 결과와 비교분석하였다. 분석결과 ChatGPT가 제시한 코드가 보다 더 간결할 수 있으며, 상대적으로 경쟁력 있는 결과를 도출하는 것을 확인하였다. 다만, 상대적으로 간결한 코드와 우수한 구동결과를 획득하기 위해서는 해당 도메인의 전문적 지식을 바탕으로 적절한 다수의 질문을 해야 하며, ChatGPT에 의해 작성된 코드의 의미를 명확히 해석하거나 비판적 분석을 하기 위해서는 전문가지식이 반드시 필요함을 알 수 있었다.