• Journal of Korean Elementary Science Education
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• v.37 no.4
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• pp.402-415
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• 2018

This study aims to inquire into the U. S. elementary school teachers' storylines for science teaching methods, scientific knowledge and interactions with students. As research subjects, two American elementary school teachers, named Christina and Melissa, were selected. As test tools, this study adopted Storyline Test and semi-structured interviews. Firstly, in regard to the science teaching method, Christina evaluated that she gradually improved her science teaching skills up to positive 6 points, starting from 2 points in the first year of teaching career, while Melissa sustained a stable state with 5 points in the 9th year of teaching career, starting from 1 point in the first year of teaching career. It was found that both the teachers had more confidence in their science teaching methods by participating in various training programs. Secondly, Christina evaluated her scientific knowledge in the first year of teaching career as 4 points, but evaluated her present scientific knowledge as stable as 6 points since she started studying teaching materials actively, discussing with other teachers and having more ability of application through science class integrated with other school subjects, in the 7th year of her teaching career. On the other hand, Melissa evaluated her scientific knowledge in the first year of teaching career as 1 point since she did not exactly know what to teach elementary school students, but in the 6th year of teaching career, she sustained a stable state with points through joint-activities with other teachers. It was found that chances to research with other teachers had important effect on both the teachers' confidence in scientific knowledge. Thirdly, in regard to interactions with students in science class, Christina said that she did not have any interaction with students when instructing inquiry activities in the first year of teaching career, but since the 10th year of her teaching career, she had sustained a stable state with 6 points through active interaction with students, by leading learning projects and science competitive exhibitions, etc. On the other hand, Melissa evaluated her interaction with students in the first year of teaching career as 1 point because her class was reading-oriented, but since the 9th year of teaching career, she had sustained a stable state with 6 points so far, by developing inquiry activity strategies to improve interaction with students. Overall, it was found that inquiry activities played a central role in improving both the teachers' interaction with students.

• Journal of Korean Library and Information Science Society
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• v.52 no.4
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• pp.229-253
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• 2021

The service strategy of the public library needs to be established based on the users who are the actual beneficiaries of the services, including the perspective of changes in the social environment. This study investigated and analyzed the users' perceptions of the library functions and services currently provided and the demand for future services, targeting public library users in the Busan area. The data were collected through a questionnaire, and the respondents were 733 public library users in Busan. The main result is that first, the role and function of the public library that Busan users consider most important was still in material collection and provision. Second, in the information service type, the demand for cultural/lifelong learning program service was the highest, and in the service program, the demand for new IT technology experience and education was the highest. Third, as a result of ISA analysis of information service type, material provision service and information literacy education service were types to be maintained, and reading related service was type to be managed intensively. Fourth, in the analysis of service demand by age, those aged 41 to 50 years old were the generation with the highest demand in all types except for the information literacy education service type, and the demand for information literacy education was the highest among the elderly generation over 61 years old. And the user group in the western part of Busan was higher than the user group in other regions in demand for almost all service types. The results of this study can be used as basic data when establishing strategies to optimize community public library services for users.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.3
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• pp.295-324
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• 2022

This study analyzed the operation status of the military library and e-book service in order to improve the soldiers' access to the reading environment and to suggest a plan to revitalize the military library. As a result of the survey, it was found that it is necessary to improve the environment such as the IT environment, devices, and time allowed for access to activate the use of e-books. According to the interview results, problems such as low usage rate and awareness of the digital library, the use of different e-book viewers and management systems for each distributor when distributing e-books, and the dissemination of e-books for the management and accessibility of the Armed Services Editions in library were raised. In order to activate the e-book service of the library in the military, diversify e-book service promotion and education programs, activations such as establish standards for the e-book operating system for each county, use platforms and devices to promote e-book operation and use, and construction of e-book service using Armed Services Editions were derived.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.