The Journal of Korean Institute for Practical Engineering Education
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v.4
no.1
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pp.30-44
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2012
The purposes of this study were to develop Korean version of the Kolb learning Style Inventory (version 3.1) by systematic translation process and to test learning style of 596 K University-students. First, Korean version of LSI was successfully developed and tested for ensuring internal consistency reliability and internal validity. Second, K University students' average scores of learning modes were as follows: 27.75 of Concrete Experience(CE), 27.93 of Reflective Observation(RO), Abstract 31,95 of Conceptualization (AC), and 32.37 of Active Experimentation(AE). In addition, the study reported KUT students learning style distribution: 32% of accommodating style, 27.2% of Diverging one, 26.5% of Assimilating one, and 14.3% of Converging one.
Purpose: The goals of this study were to identify the relationships among learning agility, grit, positive psychological capital, and nursing performance and to determine the impact of these factors on clinical nursing performance. Methods: Between November and December 2021, a descriptive survey design was conducted with a convenience sample of 260 clinical nurse participants from two regional hospitals. Data were collected using the Learning Agility Scale, Grit Scale, Psychological Capital Questionnaire, and the Nursing Performance Scale. Data from 248 nurses were analyzed using descriptive statistics, independent t-test, one-way analysis of variance, Pearson's correlation, and multiple linear regression analysis using SPSS 27.0. Results: Results revealed significant positive correlations between nursing performance and learning agility, grit, and positive psychological capital. Stepwise multiple regression analysis identified positive psychological capital as the strongest predictor of nursing performance, followed by work experience, learning agility, grit, and educational level. These variables accounted for 51% of the variance in nursing performance. Conclusion: This study underscored the importance of positive psychological capital, learning agility, and grit in improving nursing performance. Healthcare organizations should prioritize the development of these attributes among nurses. Implementing strategies to enhance these factors in nursing practice and education could improve nursing performance, potentially resulting in better patient outcomes and increased job satisfaction. Future research should explore specific interventions to cultivate these qualities and assess their long-term impact on nursing practice.
The purpose of this research is to develope and implement a convergent educational contents based on theoretical background of integrated education using agent based modeling in the ubiquitous learning environment. The structure of this contents consists of three modules that were designed by trans-disciplinary concept and situated learning theory. These three modules are: convergent problem presenting module, resource of knowledge module and learning of agent based modeling and IT tools module. After the satisfaction survey of the implemented content, out of 5 total value, the average value was 3.86 for effectiveness, 4.13 for convenience and 3.86 for design. The result of the survey shows that the users are generally satisfied. By using this u-learning contents, learners can experience and learn how to solve the convergent problem by utilizing IT tools without any limitation of device, time and space. At the same time, the proposal of structural design of contents can be a good guideline to the researchers to develop the convergent educational contents in the future.
Purpose: Nursing students experience a high degree of perceived stress during skills training. The resulting academic sentiment is worthy of research. This study examined the learning motivation as a mediator in the association between perceived stress and positive deactivating academic emotions in nursing students undergoing skills training. Methods: A survey was conducted on 386 third-year undergraduate nursing students at a university in Changchun, China, in 2017. The survey included the items on perceived stress, learning motivation during nursing skill training, and general academic emotion. There were 381 valid responses (response rate=98.7%). Based on the results of partial correlation and stepwise multiple regression equations, the study examined the mediation model between perceived stress, learning motivation and positive-deactivating academic emotions using process 2.16 (a plug-in specifically used to test mediation or moderation effect in SPSS). Results: There was a significant negative correlation between students' perceived stress and learning motivation during nursing skills training and positive-deactivating academic emotions. Nervousness, loss of control, and interest in developing reputation had significant predictive effects on positive-deactivating academic emotions. The mediating model was well supported. Conclusion: Learning motivation during nursing skills training lessened the damage of perceived stress on positive-deactivating academic emotions. Improving students' motivation to learn could reduce their perceived stress and build more positive emotions. Positive emotions during learning played an important role in helping nursing students improve skills and enhance their nursing competence.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.16
no.5
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pp.325-330
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2023
This paper proposes to apply machine learning to the process of predicting the slab thickness based on the structural analysis results or experience and subjectivity of engineers in the design of bridge data construction to enable digital-based decision-making. This study aims to build a reliable design environment by utilizing machine learning techniques to provide guide values to engineers in addition to structural analysis for slab thickness selection. Based on girder bridges, which account for the largest proportion of bridge data, a prediction model process for predicting slab thickness among superstructures was defined. Various machine learning models (Linear Regress, Decision Tree, Random Forest, and Muliti-layer Perceptron) were competed for each process to produce the prediction value for each process, and the optimal model was derived. Through this study, the applicability of machine learning techniques was confirmed in areas where slab thickness was predicted only through existing structural analysis, and an accuracy of 95.4% was also obtained. models can be utilized in a more reliable construction environment if the accuracy of the prediction model is improved by expanding the process
In the recent e-learning environment, avatars are often used to help learners get familiar with the contents, which is ultimately to motivate them to study more. Therefore, it is important to investigate whether avatars have actually the desirable effect on users of e-learning materials. Surprisingly, however, no extensive study has been conducted on this crucial issue Accordingly, main objectives this study are summarized as follows. First, we need to gain better understanding of how much learners' trust towards avatars (termed as "avatar trust") is transferred to learners' trust towards e-learning contents (termed as "contents trust"). Second, we need to investigate how much learners' personal relationships with avatars as well as learning behaviors change depending on avatar types (attractive vs. professional) and contents complexity (easy vs. difficult). As described in the study objectives, in order for us to analyze empirical data more systematically, we classified avatar types into two: "attractive" and "professional;" the contents are categorized as either "easy" or "difficult." Therefore, it is essential for this study to build a prototype e-learning website on which our research purpose can be realized and tested effectively with proper avatar types and e-learning contents. For this purpose, we built a prototype e-learning website, in which avatars are invited from currently working avatar instructors used in real-world e-learning websites, and e-learning contents are adapted from real-world contents about Java programming topic, which have been proved to have shown high quality and reliability. Our research method includes questionnaire survey by inviting a number of valid respondents comprised of office workers who are believed to have high demands for the e-learning contents as well as those who have previous experience with avatar instructors. Respondents were given one of the four e-learning experiment conditions (2 avatar types x 2 contents types) on a random basis. Each experimental e-learning condition is framed to have the same quality but different avatar type and content complexity. Then the respondents are asked to fill out the survey form which has questions about avatar trust, contents trust, personal relationships with avatar, and learning behavior, among others. Regarding the constructs used in research model, we based them rigorously on previous studies. For example, we used six constructs such as behavior to give information (BGI), behavior to obtain information (BOI), need for inclusion wanted, need for control wanted, contents trust, and avatar trust. To measure them, 7-Likert scales were used in the questionnaire. E-learning performance was measured indirectly through two constructs such as BGI and BOI. Six constructs used in the research model were adopted and revised from the FIRO-B model suggested by Schutz. Empirical results are as follows: First, professional avatars are more effective for difficult contents, while attractive avatars were not as effective for easy contents. Second, our study results ascertained that avatar trust transfers to contents trust regardless of avatar types and contents complexity.
Journal of The Korean Association For Science Education
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v.42
no.3
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pp.357-370
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2022
In this paper, we developed an augmented reality learning tool suitable for chemical bond learning and proposed a process-oriented guided inquiry learning using mobile augmented reality (POGIL-MAR) to find out how it affects science achievement, science learning motivation and learning flow. Participants were 139 10th-grade students from a coeducational high school in Gyeonggi-do, and they were randomly assigned to the control group (TL), the treatment group 1 (POGIL), and the treatment group 2 (POGIL-MAR). They learned the concept of the chemical bond from the Integrated Science subject for four class periods. Results of two-way ANCOVA revealed that the POGIL-MAR group scored significantly higher than the other groups in a science achievement test, science learning motivation test, and learning flow test, regardless of their prior science achievement. In addition, in the case of the low-level group, the POGIL-MAR group showed a statistically significant improvement in achievement compared to the TL and POGIL groups. The MANCOVA analysis for sub-factors of science learning motivation show that the POGIL-MAR group had significantly higher scores in intrinsic motivation, career motivation, self-determination, self-efficacy, and grade motivation. In particular, the interaction effect between the teaching and learning method and the level of prior achievement was significant in the intrinsic motivation. Meanwhile, the MANCOVA analysis for sub-factors of learning flow show that the POGIL-MAR group had significantly higher scores in clear goals, unambiguous feedback, action-awareness merging, sense of control, and autotelic experience. Based on the results, educational implications for effective teaching and learning strategy using mobile augmented reality are discussed.
Researchers in science education have recently focused on service learning as an important educational approach to address environmental challenges including climate change. However, there are a limited number of studies focused on service learning in science education in Korea. In this study, based on existing related literature, the theoretical background of service learning is introduced and a conceptual framework that can be applied in the science education environment in Korea as a new approach to address environmental challenges is proposed. Given this, 112 relevant academic documents collected by searching a global database were analyzed. As a result, the theoretical background of service learning rooted in Dewey's experiential learning is introduced. Specifically, service learning is defined as a form of experiential learning that supports students in helping communities with structured services related to learning content, while at the same time fostering their in-depth understanding of content and engaging in civic and social responsibility as members of their community. In addition, a conceptual framework for service learning to address environmental challenges that can be applied to the science education environment in Korea is proposed. The proposed framework classifies the members of service learning into schools, students, and communities, and presents knowledge, experience, and learning through critical reflection as its core elements. It is important to actively implement service learning in science education to address various environmental challenges including climate change, biodiversity loss, air pollution, and deforestation, as just a few pressing challenges. Therefore, based on the proposed conceptual framework for service learning, studies that apply and verify diverse forms of educational approaches to addressing environmental challenges in local communities at school sites are needed.
With the digital transformation of the entire industry, software competency has become the core competency for the future talent. However, it is difficult to find researches related to the corporate education for improving employee's software capability. Therefore, this study tried to verify the relationship between factors affecting the learning performance of employees in online software education. For this purpose, a survey of 223 employees with online software education experience was analyzed using the SPSS PROCESS macro. As a result of analysis, perceived usefulness and self-regulated learning have been found to have a significant multiple mediating effect on learning performance by digital literacy and satisfaction. This suggests that not only learner factors but also the characteristics of education should be considered. The results of this study are expected to be helpful in designing effective online education programs.
Purpose: This study aims to provide essential data for developing educational methods and content, tailored for the prehospital field situation, by analyzing the effects of education regarding the management of cardiac arrest. Methods: This study is a primitive experimental study of 55 new firefighters in C Fire Service Academy. Data were collected from the training which was imparted using the CPR virtual reality simulation program (CBS 2.0) in accordance with COVID-19 quarantine rules and social distancing. Data were analyzed utilizing SPSS version 25.0. Results: After VR simulation training, knowledge about performing CPR (14.85) and self-efficacy (4.12) were significantly high (p<.001). Learning immersion was also high (3.99±0.59), but learning satisfaction was even higher (4.34±0.62). Depending on the recruitment field, firefighters showed higher learning immersion (4.04±0.58 vs 3.68±0.63) and self-efficacy (4.16±0.55 vs 3.91±0.84) than 119 EMTs' but, there was no significant difference between them. In contrast, The quality of performance of CPR by EMT's was significantly higher than that of firefighters (p=.025). Depending on previous simulation experience, there was no significant difference among dependent variables. Conclusion: Virtual reality simulation shows positive results in learning immersion, learning satisfaction, self-efficacy, and performance of CPR. Therefore, we propose that virtual reality simulation training can be a new educational paradigm.
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