• (The)Korea Educational Review
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• v.23 no.1
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• pp.113-138
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• 2017

Questions of why, what, and how represent the new perspective on goal construct. This paper proposed a novel approach toward the goal construct as a dynamic decision-making process. A number of researchers have agreed that goals initiate and sustain human motivation. In spite of the consistency in emphasis on goals, there are apparent inconsistencies in definitions of goal construct across theories and research. These inconsistences hinder interdisciplinary communication about goal construct, which in turn leads to jingle-jangle fallacy. Therefore, on the basis of systematic literature review, I defined the goal construct as a multifaceted and hierarchical decision-making process to structure desired end-states. The first process is generating goals, which can be also called "why" process. During this phase, individuals generate cognitive schema about general direction of desired end-states based on the conscious and nonconscious interpretation of subjective experience. The second process is goal setting, which can be called "what" process. Here, individuals clarify contents of multiple goals and structure hierarchy and priority of them. The last process is implementing goals, "how" process. This process contains decision making about whether he/she decides to implement the goal or not and how to execute goal-directed behaviors. In the last section of this paper, I tried to suggest several practical applications of this new perspective for adolescents, who struggle with why-what-how to have goals in learning context.

• Journal of vocational education research
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• v.29 no.3
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• pp.23-40
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• 2010

Career guidance refers to services intended to assist students to make educational and occupational choices and to manage their careers. Young students, specially enrolled in vocational high schools, need programs to help them make transitions to the working world and to re-engage with further learning, and career guidance needs to be part of such programs. Teachers assume the critical roles in planning and organizing the career guidance programs in vocational high schools. The program includes career information provision, assessment and self-assessment tools, career counseling, work search, etc. In this study, we developed a research model based upon TRA(theory of reasoned action) developed by Ajzen and Fishbein to investigate the factors influencing the intention to provide career guidance services to students in vocational high schools. Based on 155 survey responses from vocational high school teachers, we show that attitude and subjective norm motivate teachers to provide career guidance services, and that attitude toward career guidance is directly influenced by self-efficacy for career guidance and burden from extra work. It was also confirmed that facilitating condition is the antecedent of self-efficacy. But contrary to our expectation, self-efficacy for career guidance has no significant effect on the intention for providing career guidance services at 5% significance level. In light of these findings, implications for theory and practice are discussed.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.402-411
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• 2019

The purpose of this study is to determine critical assessments and core competencies, and to determine the competence and discipline of self-assessment. We surveyed 511 students who graduated from 12 universities. Self-efficacy 24 items were measured on a 5-point scale, 8 core competencies and 52 detailed competencies were self - assessed from 0 to a maximum of 10 points. The higher the score, the higher the self - evaluation competency level. Statistical analysis was performed using SPSS 20.0 Ver., And a statistical significance level of 0.05 was considered. The self - evaluation competency level was the highest at 6.7 points in the clinical dentistry area, and the lowest at the evidence - based decision area of 5.7 points. Self-regulation was found to be positively related to the self-evaluation core competence level among self-efficacy sub-factors. As the students' self-efficacy affects subjective academic achievement and self-evaluation, it is necessary to develop and apply relevant programs to enhance critical thinking in curriculum, apply problem-based learning method, improve self-efficacy and leadership, It should be possible to cultivate.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.629-635
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• 2019

In term of the factors affecting psychosocial adjustment of breast cancer patients, their quality of life after surgical operation, radiation, and chemotherapy were systematically meta-analyzed. As a result, their qualities of life of the patients that had radiation therapy was the lowest right after the therapy, and gradually increased after the end of the therapy. However, after six months, their quality of life failed to reach the same level before the therapy. They had depression and side effects the most right after the therapy, and somewhat reduced them after the end of the therapy. In case of surgical operation, the more they were educated, the more they had psychosocial adjustment, and the more they had a medical examination and took out an insurance policy, the more they had psychosocial adjustment. In case of chemotherapy, their cognitive function is influenced so that they have impairments in memory, learning, and thinking stages. Since subjective cognitive impairment has a relationship with depression, it is necessary to monitor depression of chemotherapy patients. Given the results of this systematic meta-analysis, when three types of therapies (surgical operation, radiation therapy, and chemotherapy) are applied to patients with breast cancer, it is necessary to recognize their psychosocial adjustment, depression, anxiety, and quality of life in the nursing and radiation therapy fields and thereby to introduce an intervention program for a holistic approach.

• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.665-676
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• 2021

As the number of deteriorated buildings increases, the importance of safety diagnosis and maintenance of buildings has been rising. Existing visual investigations and building safety diagnosis objectivity and reliability are poor due to their reliance on the subjective judgment of the examiner. Therefore, this study presented the limitations of the previously conducted appearance investigation and proposed 3D Point Cloud data to increase the accuracy of existing detailed inspection data. In addition, this study conducted a calculation of an objective building safety grade using a Deep-Neural Network(DNN) structure. The DNN structure is generated using the existing detailed inspection data and precise safety diagnosis data, and the safety grade is calculated after applying the state evaluation data obtained using a 3D Point Cloud model. This proposed process was applied to 10 deteriorated buildings through the case study, and achieved a time reduction of about 50% compared to a conventional manual safety diagnosis based on the same building area. Subsequently, in this study, the accuracy of the safety grade calculation process was verified by comparing the safety grade result value with the existing value, and a DNN with a high accuracy of about 90% was constructed. This is expected to improve economic feasibility in the future by increasing the reliability of calculated safety ratings of old buildings, saving money and time compared to existing technologies.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.390-399
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• 2022

Purpose: This study was conducted to identify the factors affecting nursing students' resilience. Methods: The subjects were 192 nursing students from a college in G city. Data were collected from september 23 to 26, 2019 and analyzed using SPSS 22.0 and descriptive statistics, t-test, ANOVA, Sheffé test, Pearson's correlation coefficients, and multiple regression. Results: Resilience showed a statistically significant difference according to gender, grade, personal relation, motive for application, major satisfaction, grade point in general characteristics. Academic engagement and resilience showed apparent positive correlation (r=.37, p<.001), stress and resilience showed weak negative correlation (r=-.23, p=.001). In multiple regression analysis, the most affecting factor was the academic engagement (𝛽=.24), poor of subjective health status (𝛽=-.21), female (𝛽=-.19), junior of grade (𝛽=.13). These variables explained 33.0% of the total variance in resilience. Conclusion: To strengthen resilience in nursing students, learning atmosphere creation through intrinsic motivation in the regular class. Also, a variable academic engagement program should be provided to be able to positive thinking about academic study and achievement.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.85-91
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• 2021

School violence has long been recognized as a social problem, and various efforts have been made to prevent it. In this study, we propose a system that can prevent school violence by analyzing data on the frequency of conversations between students, and identify peer relationships. The frequency of conversations between students in the class was quantified using a rating scale questionnaire, and this data was grouped into the appropriate number of clusters using the K-means algorithm. Additionally, the homeroom teacher observed the frequency and nature of conversations between students, and targeted specific individuals or groups for counseling and intervention, with the aim of reducing school violence. Data analysis revealed that the teachers' qualitative observations were consistent with the quantified data based on student questionnaires, and therefore applicable as quantitative data towards the identification and understanding of student relationships within the classroom. The study has potential limitations. The data used is subjective and based on peer evaluations which can be inconsistent as the students may use different criteria to evaluate one another. It is expected that this study will help homeroom teachers in their efforts to prevent school violence by understanding the relationships between students within the classroom.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.841-849
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• 2023

Construction projects have risks due to various factors such as construction delays and construction accidents. Based on these construction risks, the method of calculating the construction period of the construction project is mainly made by subjective judgment that relies on supervisor experience. In addition, unreasonable shortening construction to meet construction project schedules delayed by construction delays and construction disasters causes negative consequences such as poor construction, and economic losses are caused by the absence of infrastructure due to delayed schedules. Data-based scientific approaches and statistical analysis are needed to solve the risks of such construction projects. Data collected in actual construction projects is stored in unstructured text, so to apply data-based risks, data pre-processing involves a lot of manpower and cost, so basic data through a data classification model using text mining is required. Therefore, in this study, a document-based data generation classification model for risk management was developed through a data classification model based on SVM (Support Vector Machine) by collecting construction project documents and utilizing text mining. Through quantitative analysis through future research results, it is expected that risk management will be possible by being used as efficient and objective basic data for construction project process management.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.187-204
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• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Korean Journal of Health Education and Promotion
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• v.1 no.1
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• pp.21-36
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• 1983

It is assumed that menarche is affected not only by the biological factors such as nutrition and genetic heritage, but also it is affected by other socio-cultural environmental factors including weather, geographic location, education and level of modernization. Also recent trend of menarche in Korea indicates that a lot of discussion are being generated to the need of sex education as a part of formal school education. The purpose of this study is to develop the school health education program by determine the age of menarche, the factors relavant to time of menarche and psycho-mental state of students at the time in menarche and investigate the present state of school health education relate to menarche of adolescents. The total number of 732 girls was drown from first, second and third grades of 4 middle schools in Seoul. For the data collection the survey was conducted during the period from May 1 to May 20, 1982 by using prepared questionair. The major results are summarized as follow; 1. Mean age at menarche and the percent distribution of menarche experienced. It was observed that about 68.7% of sampled students have been experienced menarche at the time interviewed. For the each group, age at menarche is revealed that among the students about 37.8% are experienced menarche for under 12 years old group, 62.1% for 13 year-old group, 80.6％ for 14 year-old group and 95.5% for over 15 years old. In sum it was found that the mean age at menarche was 12.3 years old, ranged from age at 10 as earlist the age at 15 as latest. 2. Variables associated with age at menarche. 1) There was tendency those student who belong to upper class economic status have had menarche earlier than those student who belong to lower class. Therefore, economic status is closely related to age at menarche. 2) In time of mother's education level, it is also found that those students whose mother's education levels from high school and college are experienced menarche earlier than those students whose mother's education levels from primary school and no-education. 3) However, in connection with home discipline, there was no significant relationship between age at menarche and home disciplines which are being treated "Rigid", "Moderated ", "Indifferent". 4) Degree of communication between parents and daughter about sex matters was found to be associated each others in determination of age at menarche. 5) It was found that high association between mother's menarche age and their daughter's menarche age was observed. Mother's age at menarche earlier trend to be shown also as earlier of their daughters. 6) Those students belong to "D & E" of physical substantiality index are trend to be earlier in menarche than those students in the index "A & B". 3. Psycho-mental state at the time of menarche. Out of the total students 68.2% had at least one or more than one of subjective symptoms. Shyness was shown as most higher prevalent symptom and others are fear, emotional instability, unpleasant feeling, depression, radical behavior, inferior complex and satisfaction appeared. Very few cases are appeared be guilty and stealing feeling. 4. The present status of school health education program related to menarche. As to the source of information about menarche, teacher was a main source with average index 5.88 and the other informants were mother & family member, friends, books and magagines, movies, television, and radio. For the problem solving at menarche, mother & family members were subject to discussion with an average index 6.02 as high. The others for discuss and knowledge about menarche were books, magagine, friends, teachers, and self-learning based on own experienced. The time of learning about menarche, it was learned as highest percentage with 43.2% at a 6 grades of primary school, middle school with 34.4%, 5 grade of primary school with 18.2%, and 4 grade of primary school with 4.0% respectively.