• Journal of Science Education
• /
• v.46 no.1
• /
• pp.93-108
• /
• 2022

The purpose of this study is to develop a STEAM program that can be used in the high school credit system to be fully implemented in 2025, and to examine its validity and effectiveness. The STEAM program analyzed the 2015 revised curriculum centering on science, technology, and engineering through the 2015 revised curriculum analysis, and then selected the five latest issues: hydrogen fuel, climate crisis, data science, appropriate technology, and barista. In accordance with this self-developed program development format (frame), it was developed for seven months through a process of group deliberation. The draft of the STEAM program for 29 sessions of five types, developed to indirectly experience the career path and occupation of high school students, was verified through consultation with 2 STEAM education experts. It was applied at five different high schools for a pilot implementation. As a result of the pilot application, it was confirmed that the students' STEAM attitude significantly improved in the post-test than the pre-test, and the students' high satisfaction with the program was confirmed. In addition, through an interview with the pilot application teacher, it was positively evaluated that 'the content and level of the program are suitable and through experience solving real-life problems, you can apply the content knowledge of related subjects and have an opportunity to experience careers.' Based on the results of the pilot application, the high school credit system STEAM program for students and teachers was finally completed in 29 lessons of five types. Through this study, the development and operation of the next-generation STEAM program that can be applied in the high school credit system should be actively developed, and a plan to improve teachers' professionalism so that the high school credit system can be established and operated properly for blended classes triggered by COVID-19. The necessity of design was suggested. This study is expected to be used as basic data for the development and operation of STEAM programs in the high school credit system, which will be fully implemented in 2025.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.155-166
• /
• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.