• Journal of Korean Elementary Science Education
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• v.30 no.4
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• pp.574-588
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• 2011

교사의 과학 탐구 지도에 대한 인식은 실제 수업에서 탐구 지도를 수행하는데 중요한 역할을 할 수 있다. 따라서 교사들이 과학 탐구를 어떻게 인식하는지 이해할 필요가 있다. 이 연구에서는 한국, 싱가포르, 미국 세 국가의 초등교사를 대상으로 과학 탐구 지도에 대한 인식을 조사하였다. 세 국가는 과학교육과정에서 탐구를 강조해 온 역사와 설명 방식이 다르며 전반적인 교육적 상황 또한 상이하다. 총 100명의 초등교사(한국 34, 싱가포르 35, 미국31)를 대상으로 설문을 실시하였으며 설문은 구체적인 교수 상황을 서술하는 교수 시나리오, 이상적인 탐구 수업에 대한 내러티브 쓰기로 구성되었다. 데이터는 외적 기준과 내적 관점 모두에서 분석되었다. 연구 결과 교사들의 과학 탐구 지도에 대한 인식은 전반적으로 전통적 견해에 머무르고 있는 특징을 보였다. 그러나 각 국가의 교육과정에서 탐구가 서술되고 강조된 방식에 따라 차이가 나타나기도 하였다. 이러한 결과가 교사교육에 주는 시사점을 논의하였다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.275-281
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• 2021

Much of our lives are closely related to artificial intelligence, and society is changing more rapidly. Reflecting this era, the need for artificial intelligence education has emerged and various learning methods have been proposed, but guidance on artificial intelligence teaching and learning activities for lower grades elementary school students is insufficient. Therefore, in this study, the data collection education program for the lower grades of elementary school was developed based on the contents standards of the Korea Foundation for the Advancement of Science & Creativity. Focusing on the principles of artificial intelligence and the detailed data area of the utilization area, the focus was on expressing numbers and letters in various ways, such as colors and pictures, and finding various types of data in life to learn the principles of artificial intelligence. Through this program, it is expected that lower-grade elementary school students will be able to understand the importance of data collection in artificial intelligence through the process of knowing about data and collecting sound, picture, and text data.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.219-234
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• 2018

In this study, we explored the possibility of automating the process of analyzing elements of scientific argument in the context of a Korean classroom. To gather training data, we collected 990 sentences from science education journals that illustrate the results of coding elements of argumentation according to Toulmin's argumentation structure framework. We extracted 483 sentences as a test data set from the transcription of students' discourse in scientific argumentation activities. The words and morphemes of each argument were analyzed using the Python 'KoNLPy' package and the 'Kkma' module for Korean Natural Language Processing. After constructing the 'argument-morpheme:class' matrix for 1,473 sentences, five machine learning techniques were applied to generate predictive models relating each sentences to the element of argument with which it corresponded. The accuracy of the predictive models was investigated by comparing them with the results of pre-coding by researchers and confirming the degree of agreement. The predictive model generated by the k-nearest neighbor algorithm (KNN) demonstrated the highest degree of agreement [54.04% (${\kappa}=0.22$)] when machine learning was performed with the consideration of morpheme of each sentence. The predictive model generated by the KNN exhibited higher agreement [55.07% (${\kappa}=0.24$)] when the coding results of the previous sentence were added to the prediction process. In addition, the results indicated importance of considering context of discourse by reflecting the codes of previous sentences to the analysis. The results have significance in that, it showed the possibility of automating the analysis of students' argumentation activities in Korean language by applying machine learning.

• Journal of The Korean Association For Science Education
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• v.43 no.6
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• pp.583-594
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• 2023

This study aimed to develop an e-PBL program for high school students using COVID-19 related data and to investigate the impact of the developed program on students' science core competencies. For this, the e-PBL program was developed in consideration of the characteristics of learners and e-PBL, and a science core competency analysis framework. The program was applied to 26 general high school life science club students. Test for science department core competency was conducted before and after class by questionnaires and their conversation data during class was collected and analyzed by the framework. As a result of the study, the developed program was effective in improving five science core competencies. In the results of the analysis of the science core competency questionnaire, there were significant effects on scientific thinking ability, scientific inquiry ability and scientific problem solving ability. Unlike in the results of the questionnaires, the five sciences department core competencies appeared evenly in student discourse analysis. Among them, scientific communication ability and scientific participation and lifelong learning ability did not show significant results in the questionnaire, but in the discourse analysis results. Both abilities were the most evenly displayed competencies through the program stages. Through the study, we expect that the program is possibles to be useful instructional material to make high school students increase science core competencies.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.579-590
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• 2022

In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.

• Journal of The Korean Association For Science Education
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• v.42 no.1
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• pp.149-160
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• 2022

Comparative studies using large-scale data such as TIMSS, PIRLS, and PISA inform us of the effectiveness of each educational system. Even though samples in the large-scale studies were representative, admitting potential discrepancy when applying the findings of the large-scale studies to local educational system is still needed. This study examines the structural relationship among students' attitude towards science, learning support from teachers, school life, and science academic achievement with both large-scale data and local comparative study data utilizing same variables. Responses on the TIMSS 2019 of 5,554 Korean seventh-grade students and National Assessment of Educational Achievement (NAEA) 2019 of 6,365 third-grade middle school students were used. The results indicate that: a) school life did not affect the science achievements in both data. However, in NAEA 2019, students' attitude mediated the relationship between school life and science achievement; b) learning support from teachers had a significant impact on TIMSS science achievements, and also had positive effect on achievement through students' attitude in TIMSS. On the other hand, learning support had a positive effect on achievement only when student's attitude mediated the relationship in NAEA; c) students 'attitude toward science had positive effect on science achievement on both data; d) the impact of gender was different on school life, academic achievement, students 'attitude towards science, and learning support from teachers on both data; and e) the impact of the number of books differed as well. There were differences in results between the international and domestic research, which inform us that we need to pay attention when interpreting the domestic environment through the results of international research.

• Journal of Science Education
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• v.45 no.1
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• pp.118-128
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• 2021

In this study, as the viewing characteristics of users of YouTube video content related to science education, 'Inflow and Access' is analyzed to find out the interaction between learners and the system, and 'Reaction and Subscription' to find out the interaction between learners and contents. To this end, the YouTube channel "Elementary Science TV," was selected as the subject of research. The channel is mainly focused on the contents of elementary science textbooks, STEAM, and gifted education. The channel's data of YouTube studio was analyzed. The following results were obtained through data analysis: first, as a result of 'Inflow and Access' analysis, YouTube video content related to science education was most often introduced through external links, and the access device was mainly a computer. Second, as a result of the analysis of 'Reaction and Subscription,' 'like' and commenting performed as a reaction to the video were less than 1% of the number of views. Most users watch without a subscription, and watch for longer when using self-directed. Although this study was analyzed through a limited channel called 'Elementary Science TV,' we were able to discover a little about the users' viewing characteristics of YouTube video contents related to science education. In the future, it is expected that it can be used as a basic material for creating videos related to science education for remote classes, establishing a science education video platform.

• Journal of The Korean Association of Information Education
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• v.26 no.2
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• pp.105-120
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• 2022

In addition to the rapid changes in the times caused by the pandemic, the revision of the new curriculum coincides with the change in the proportion of the three elements of learners, society, and subjects that make up the curriculum. In particular, along with the proportion of 'social' in the curriculum, the scope of the word 'educational community' has increased, and the allowable range of curriculum restructuring centered on it has expanded. In order for the intended direction of education to be properly established in the new curriculum, various educational method studies are needed to cultivate newly emerged competencies and literacy. In this study, after selecting the contents and goals of the convergence curriculum based on various criteria for subject selection, the data science program was designed by reconstructing Living Lab's PDIE methodology. As an evaluation factor for this, we tried to analyze the effectiveness of 'creativity', 'problem-solving ability', 'communication ability', 'collaboration ability' among future competencies emphasized in the curriculum. As a result of the study, it was effective in improving creative and communication skills, and this study focuses on verifying the effectiveness of School Living Lab, suggesting the necessity of post-research that expands the application space of research and diversifies the role of educational community subjects.

• Journal of Korean Elementary Science Education
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• v.41 no.1
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• pp.93-105
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• 2022

This study investigated the aspects of how three preservice elementary school teachers conducted the data-text transforming discourses in their science simulation teaching and how their epistemological conversations worked for learners' construction of scientific knowledge. Three preservice teachers, who had presented simulation teaching on the seasonal change of constellations, participated in the study. The results revealed that one preservice teacher, who had implemented the transforming discourses of data-to-evidence and model-to-explanation, appeared to facilitate learners' knowledge construction. The other two preservice teachers had difficulty helping learners construct science knowledge due to their lack of transforming discourses. What we should consider for improving preservice elementary school teachers' teaching competencies was discussed based on a detailed comparison of three cases of preservice teachers' data-text transforming.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.1
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• pp.33-47
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• 2021

This study developed a big data-based STEAM (Science, Technology, Engineering, Art & Mathematics) program using WWT (World Wide Telescope), focusing on content elements of 'solar system', 'star and universe' in the 2015 revised science curriculum, and in order to find out the effectiveness of the STEAM program, analyzed creative problem solving, STEAM attitude, and STEAM satisfaction by applying it to one middle school 176 students simple random sampled. The results of this study are as follows. First, we developed a program to encourage students to actively and voluntarily participating, utilizing the astronomical data platform WWT. Second, in the paired t-test based on the difference between the pre- and post-scores of the creative problem solving measurement test, significant statistical test results were shown in 'idea adaptation', 'imaging', 'analogy', 'idea production' and 'elaboration' sub-factors except 'attention task' sub-factor (p < .05). Third, in the paired t-test based on the difference between the pre- and post-scores of the STEAM attitude test, significant statistical test results were shown in 'interest', 'communication', 'self-concept', 'self-efficacy' and 'science and engineering career choice' sub-factors except 'consideration' and 'usefulness / value recognition' sub-factors (p < .05). Fourth, in the STEAM satisfaction test conducted after class application, the average values of sub-factors were 3.16~3.90. The results indicated that students' understanding and interest in the science subject improved significantly through the big data-based STEAM program using the WWT.