• Child Health Nursing Research
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• v.23 no.2
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• pp.199-206
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• 2017

Purpose: The purpose of this study was to explore perception of the clinical learning environment, resilience and perfectionism in relation to practice burnout and to identify factors influencing practice burnout in student nurses. Methods: A descriptive correlational study was conducted. The participants were 313 student nurses from three universities in B and U city. Data were analyzed using t-test, ANOVA, Pearson correlation coefficient, $Scheff{\acute{e}}s$ test and multiple regression analysis. Results: Mean score for practice burnout in student nurses was 2.92 out of 5 points. Practice burnout explained 44.7% of the variance in perfectionism (${\beta}=.245$, p<.001), satisfaction with college life (${\beta}=.232$, p<.001), resilience (${\beta}=-.228$, p<.001), clinical learning environment (${\beta}=-.193$, p<.001), satisfaction with major (${\beta}=.180$, p=.001), practical relationships with peers (${\beta}=.128$, p=.005), and satisfaction with clinical practice (${\beta}=.124$, p=.039). Conclusion: Research results suggest that the important variable for student nurses' practice burnout is perfectionism. Therefore education is needed to develop strategies to manage perfectionism and reduce practice burnout.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.131-140
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• 2024

The outbreak of Covid-19 has forced teachers of special education in Saudi Arabia to keep to themselves to live in a technology-infused society throughout the virtual teaching and learning process. This study set out to explore the competence, self-efficacy, and autonomy in using information communication technology (ICT) of special education teachers in Saudi Arabia. A total of 244 special education teachers in Saudi Arabia participated in this study. This study adopted the New General Self-Efficacy Scale developed and validated by Chen, Gully, and Eden (2001), as well as the Basic Psychological Needs in Exercise Scale (BPNES) developed and validated by Vlachopoulos and Michailidou (2006). Confirmatory factor analysis (CFA) and multivariate analysis of variance (MANOVA) were used as the main data analysis in this study. The findings showed that special education teachers in Saudi Arabia possessed competence, self-efficacy, and autonomy in using ICT in their teaching and learning process. All the factor loadings in each factor were.75 or higher, indicating good factor loadings. The results of the MANOVA indicated that special education teachers in Saudi Arabia do not report different perceptions of their competence, self-efficacy, and autonomy despite their different gender, age group, academic background, and teaching experiences.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.1-12
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• 2020

As one of the essential resources in the agricultural process, soil moisture has been carefully managed by predicting future changes and deficits. In recent years, statistics and machine learning based approach to predict soil moisture has been preferred in academia for its generalizability and ease of use in the field. However, little is known that machine learning based soil moisture prediction is applicable in the situation of South Korea. In this sense, this paper aims to examine 1) whether publicly available weather data generated in South Korea has sufficient quality to predict soil moisture, 2) which machine learning algorithm would perform best in the situation of South Korea, and 3) whether a single machine learning model could be generally applicable in various regions. We used various machine learning methods such as Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) to predict future soil moisture in Andong, Boseong, Cheolwon, Suncheon region with open source weather data. As a result, GBM model showed the lowest prediction error in every data set we used (R squared: 0.96, RMSE: 1.8). Furthermore, GBM showed the lowest variance of prediction error between regions which indicates it has the highest generalizability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.626-635
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• 2017

This study aimed to identify the factors affecting confidence in performance of fundamental nursing skills in nursing students. Participants were 318 nursing students who haven't had clinical practice experiences to the point of data collection in two universities in B and U cities. Data were analyzed using t-test, ANOVA, Scheff? test, Pearson's correlation coefficients, and stepwise multiple regression. The mean scores of self-directed learning ability, satisfaction with practicum, and confidence in performance of fundamental nursing skills were $3.38{\pm}0.40$, $3.93{\pm}0.59$, and $3.40{\pm}0.61$, respectively. Correlations were found between confidence in performance of fundamental nursing skills and self-directed learning ability (r=.289, p<.001) and satisfaction with practicum (r=.353, p<.001), and between self-directed learning ability and satisfaction with practicum (r=.393, p<.001). Factors influencing the confidence in the performance of fundamental nursing skills were satisfaction with practicum (${\beta}=.24$, p<.001), self-directed learning ability (${\beta}=.15$, p=.010), and attitude to practicum participation (${\beta}=.13$, p=.027). These factors explained 15.6% of the variance in the participants' confidence in performance of fundamental nursing skills. Therefore, effective nursing educational programs need to be developed in order to foster confidence in the performance of fundamental nursing skills of nursing students by enhancing self-directed learning ability, satisfaction with practicum and active attitude to practicum participation.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.445-452
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• 2020

The purpose of this study was to identify the relationship between Nunchi and learning flow among nursing students and to investigate the factors influencing communication skills. Method: The participants were 260 nursing students in K city, who were surveyed between March 5 and April 17, 2019, using self-report questionnaire. Data were analyzed by frequencies, t-test, ANOVA, Pearson's correlation, multiple regression using SPSS Win 21.0. Result: There were positive correlation between Nunchi of participants and learning flow(r=.502, p<.001). There were positive correlation between Nunchi and communication skills(r=.619, p<.001) and between learning flow and communication skills(r=-.567, p<.001). In the multiple regression, Nunchi(β=.381, p<.001), learning flow(β=.243, p<.001) and satisfaction of clinical practice(β=.107, p=.028) were associated with communication skills. These factors accounted for 47.4% of the total variance in communication skills. Based on these results, it will be necessary to develop educational programs and strategies related with the Nunchi and learning flow disposition to improve communication skills of nursing students.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.267-274
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• 2021

The purpose of this study is to investigate differences in learning flow and teaching presence according to the lecturer's appearance and the lecturer's speech rate. For this experiment, 183 freshman students from Xingtai University in China were selected as subjects of the experiment, and a total of four types of lecture videos were developed to test the lecturer's appearance and their speech rates. Data was analyzed through multivariate analysis of variance. According to the results of the analysis, first, learning flow and teaching presence of groups who experienced the presence of the lecturer appeared were significantly higher than the groups who learned without the appearance of the lecturer. Second, the groups who learned from videos with a fast speech rate showed higher learning flow and teaching presence than the group who learned at a slow speech rate. Third, there were no significant differences in both learning flow and teaching presence according to the lecturer's appearance and speech rate. This result provides a theoretical and practical basis for developing customized videos according to learners' characteristics.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.487-494
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• 2023

The purpose of this study was to examine the relationship between self-directed learning readiness, stress coping, and academic resilience among freshman nursing students, and investigate the impact of self-directed learning readiness and stress coping on academic resilience. Data were collected from March 15 to March 26, 2022, using 205 questionnaires that were analyzed using SPSS/WIN 25.0. The results showed that the average self-directed learning readiness score of the participants was 2.61, the average stress coping score was 2.14, and the average academic resilience score was 2.36. Academic resilience was found to be positively correlated with self-directed learning readiness (r=.573, p<.001), problem-focused coping (r=.305, p<.001), seeks social support coping (r=.321, p<.001), and hopeful thought coping (r=.344, p<.001). The variables that affected academic resilience were self-directed learning readiness (β=.498, p<.001), seeks social support coping (β=.203, p=.001), and major satisfaction (β=.117, p=0.034), and these variables explained 44.8% of the variance in academic resilience. Therefore, to enhance academic resilience among nursing students, it is necessary to develop programs that improve self-directed learning readiness and promote active stress coping strategies.

• Journal of the Korean Chemical Society
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• v.44 no.1
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• pp.68-73
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• 2000

In this study, tlhe relationships of high school students' abilities to solve chemistry problems with cognitive variables (logical thinking ability, mental capacity. and learning strategy) and affective variables(self-efficacy, self-concept of ability, learning goal, and attitude toward science) were investigated. The proportion of variance due to the variables for algorithmic and conceptual problem solving ability was studied by a multiple regression analysis. The results indicated that, among the cognitive variables, the logical thinking ability significantly predicted the algorithmic problem solving ability, and the learning strategy was the best predictor of conceptual problem solving ability although not significant. Among the affective variables studied, the self-concept of alility was the significant predictor of both algorithmic and conceptual problem solving abilities. The seif-efficacy was significantly correlated with conceptual problem solving ability, but it had no predictive power.

• Culinary science and hospitality research
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• v.20 no.1
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• pp.1-17
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• 2014

Under the needs to study the predictors of the frontline employees' service-oriented organizational citizenship behaviors(OCBs) in the hotel industry, this study aimed to the influence of goal orientations on the OCBs. The two factors of performance goal and learning goal orientations were hypothesized to influence each dimension of OCBs(loyalty, service delivery, and participation). The data from 266 five star deluxe hotel employees were analyzed with descriptive statistics, multi-variate analysis of variance, and structural equation modeling conducted using SPSS 19.0 and AMOS 20.0. The results showed learning goal orientation positively influenced all dimensions of the OCBs while performance goal orientation positively influenced all dimensions except loyalty. These results suggest that hotel practitioners need to seek the applicants who are willingly oriented to specific goals at recruiting process. Furthermore, hotel organizations need to utilize the employees' goal approach to motivate their performances.