• Journal of The Korean Association For Science Education
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• v.21 no.2
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• pp.255-263
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• 2001

The purpose of this study is to analyse the eighth grade students' performance of open investigations for two kinds of tasks: the qualitative one which involves the descriptive approach through observation, and the quantitative one which involves the quantitative data processing through control of variables. Researcher's observation, interview data as well as students' investigation reports, self-evaluations were analysed. The difficulties of qualitative open investigation lie in detecting and dealing with unexpected observations, of which the acceptance and interpretation were influenced by preconceptions. On the other hand, managing several variables, making reliable and valid measures, and quantitative data processing constituted main difficulties of quantitative open investigation. Some students could recognize the deficiencies of their methods and findings in qualitative one, but few in quantitative one. These results suggest the teaching point for each task of open investigations.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.115-125
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• 2018

In order to examine the ways to improve the efficiency of R&D investment, this paper presents analysis on both quantitative and qualitative efficiency of R&D projects. As Korea's R&D investment has significantly increased in recent years, the efficiency of R&D investment has attracted attention. In this paper, a Data Envelopment Analysis(DEA) method is used to construct models for quantitative efficiency and qualitative efficiency analysis. Based on a cases of agricultural R&D projects of Korea, the efficiency of national R&D projects were analyzed and their quantitative and qualitative efficiencies are compared. As a result, statistically significant difference between quantitative and qualitative efficiency was found. Also, characteristics of Decision Making Units(DMUs) which can influence both quantitative and qualitative efficiency were identified. In particular, the stage of a R&D project has significant impact on R&D efficiency. This study suggests that in order to enhance R&D efficiency both quantitative and qualitative nature of outputs should be considered when measuring R&D efficiency.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.268-273
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• 2000

Velocity-dependent increase in tonic stretch reflexes is one of the prominent characteristics of spasticity. It is very important to evaluate spasticity objectively and quantitatively before and after treatment for physicians. An accurate quantitative biomechanical evaluation for the spasticity which is caused by the disorder of central nervous system is made in this study. A sudden leg dropper which is designed to generate objective testing environment at every trial gives very effective environment for the test. Kinematic data are archived by the 3-dimensional motion analysis system($Elite^{(R)}$, B.T.S., Italy). Kinematic data are angle and angular velocity of lower limb joints, and length and lengthening velocity of lower limb muscle. A program is also developed to analyze the kinematic data of lower limb, contraction and relaxation length of muscles, and dynamic EMG data at the same tim. To evaluate spasticity quantitatively, total 31 parameters extracted from goniogram, EMG and muscle model are analyzed. Statistical analysis are made for bilateral correlations for all parameters. The described instrumentation and parameters to make quantitative and objective evaluation of spasticity shows good results.

• Economic and Environmental Geology
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• v.21 no.1
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• pp.85-96
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• 1988

Geophysical well logging at various coal fields were carried out to study the characteristic response of domestic coal seams. Also a computer program is developed for quantitative analysis of coal logging data. Most coal seams penetrated by the drill holes, where the well logging were carried out, showed poor thickness and quality, and were severely altered. Therefore, majority of log data are inadequate for detailed quantitative analysis. The logs show, however, typical characteristics with related to coal seams, but interpretation should be made with caution because certain log response of demestic coals, mostly anthracite, are quite different to those of foreign coals, mostly bituminous. The developed comuter program has been proved as an effective one for identification of coal seams and lithology anslysis, and is expected to be succesfully used for coal quality analysis in cases of more diversified log data of good quality being obtained.

• Korean Journal of Applied Biomechanics
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• v.31 no.2
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• pp.87-94
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• 2021

Objective: Identification of meaningful patterns and trends in large volumes of unstructured data is an important task in various research areas. In the present study, we gathered golf swing image data and did quantitative analysis of swing image. Method: We collected golf swing images of 30 novice players and 30 professional players in this study. Results: We selected important features of swing posture and employed data mining algorithm to classify whether a player is an expert or a novice. Moreover, our proposed method could offer quantitative advices for golf beginners for correcting their swing. Conclusion: Finally, we found a possibility that our proposed method can be expanded to golf swing correction system

• Journal of Families and Better Life
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• v.13 no.4
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• pp.139-150
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• 1995

This research is planned to compare a quantitative methodology and a qualitative methodology in the study of the household work. For these research tasks this study is centered on husbands' participation in the household work. First it is reviewed study precedent using a quantitative method and a qualitative method to compare a research methodology of the household work. It is selected a survey method of quantitative methodology and a depth interview of qualitative methodology, Second the data are collected through the questionnaire and the depth interview with three couples,. Third to compare a quantitative methodology and a qualitative methodology it is looked about problems in the concept the grouping the collection of data and the interpretation of household work.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.206-207
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• 2022

Currently, safety accidents in construction area are managed regardless of the size. Therefore, the objective of this study is to conduct for developing the quantitative risk assessment according to large and small and medium-sized construction sites. The scope of this study is limited to the fall accidents which is the biggest accidents in the construction sites. the regression analysis was conducted based on the collected data. As a result, it was confirmed that there was a statistically significant difference between larce and small and medium-sized construction sites. This study is expected to be used as basic data for research on the development of a risk quantitative model for small and medium-sized construction sites in the future.

• Journal of Engineering Education Research
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• v.22 no.4
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• pp.61-70
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• 2019

As product development process becomes complex, it becomes more important for engineering students to experience collaborative product development. Especially the collaboration experience based on Product Data Management (PDM) systems is useful, since participants are likely to use the same environment for their professional product development. However, instructors have difficulties to evaluate contribution of each participant to their projects during the practices, since it is hard to trace personal activities for collaborative design processes. To solve this problem, this study suggests a data-driven objective method that analyses product data accumulated in PDM databases to evaluate numerically calculated contributions of participants to their class projects. As a result, the quantitative measures provided by the data-driven analysis with qualitative measures for project results can improve the fairness and quality of evaluation of contributions of participants to collaborative projects. This study implemented the proposed evaluation method with an information system and discussed the result of the application of the system to product development practices.

• Convergence Security Journal
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• v.18 no.1
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• pp.103-110
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• 2018

Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.