• Educational Technology International
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• v.16 no.2
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• pp.85-110
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• 2015

This study investigated whether college students' self-efficacy, learning strategy utilization, academic burnout, and school support predict course satisfaction and learning persistence. To this end, self-efficacy, learning strategy utilization, academic burnout, and school support were used as prediction variables; and course satisfaction and learning persistence, as criterion variables. The subjects were 178 students who registered for online and mobile "Culture and Art History" courses at K online university. They participated in an online survey. Multiple regression analysis revealed that self-efficacy and learning strategy utilization positively predicted course satisfaction and learning persistence, academic burnout negatively predicted them, and school support predicted neither. Accordingly, we suggest that raising self-efficacy and learning strategy utilization, and reducing academic burnout in the learning environment will improve the course satisfaction and learning persistence of online learners.

• Journal of the Korea Safety Management & Science
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• v.24 no.1
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• pp.49-60
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• 2022

The purpose of this study is to verify the structural relationship between job crafting and job enthusiasm, informal learning, social support, and positive psychological capital, and to investigate the effect of informal learning, social support, and positive psychological capital on job crafting through job enthusiasm. A survey was conducted on 451 safety workers at large domestic companies, and the collected data were analyzed for model suitability, influence relations between variables, and mediating effects with AMOS 23.0 using SPSS 23.0. Through research, we found five important results. First, the structural model of job crafting, job enthusiasm, informal learning, social support, and positive psychological capital properly explained the empirical data. Second, social support and positive psychological capital had a positive effect on job enthusiasm, but informal learning did not significantly affect job enthusiasm. Third, informal learning and positive psychological capital had a positive effect on job crafting, while social support did not significantly affect job crafting. Fourth, job enthusiasm had a positive effect on job crafting. Finally, job enthusiasm was found to mediate the relationship between social support and positive psychological capital and job crafting. These suggest that continuous environmental efforts and systematic management measures are needed to promote job crafting of safety workers so that informal learning, social support, positive psychological capital, and job enthusiasm can be expressed. Therefore, the necessity of developing various sub-factors of informal learning that can promote job crafting of safety workers was suggested as a follow-up study.

• The Korean Journal of Emergency Medical Services
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• v.27 no.1
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• pp.59-70
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• 2023

Purpose: This study was designed to identify the effects of social support, learning flow, and learning satisfaction on academic achievement in university students. Methods: This study involved university students who agreed to participate the investigation in D City using a structured online questionnaire from December 1, 2022 to December 31, 2022. Results: Social support, learning flow, learning satisfaction, and academic achievement had significant correlations. The influencing factors of academic achievement were age and learning flow, with an explanatory power of 20%. Conclusion: Further active management and attention are imperative for vulnerable students in high-age groups to search for the ways to improve learning flow.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.269-277
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• 2021

The purpose of the study is to explore the effect of university's managing and system support in online classes on learning participation mediated by learning presence and to examine the structural relationship between the factors. In order to achieve the purpose of the study, 135 students who take online "College English 2" classes were analyzed for the fitness of the research model and the path and structural analysis through a confirmative factor of the structural equation model. As a result of the study, first, the university's managing support for online class showed a positive effect to learning presence. Second, the university's managing support for online classes completely mediated learning presence and had a positive effect on learning participation. This study can clarify the structural relationship between environmental factors which are online class support and learners' characteristics in university online class, learning presence, and learning participation and can broaden the understanding of learning participation in online classes. It gives the implications that should be considered in teaching and learning design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.1-15
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• 2023

The aim of this study is to identify intelligent learning support functions in Learning Management System (LMS) to support university student learning activities during the transition from face-to-face classes to online learning. To accomplish this, we investigated the perceptions of students on the levels of importance and urgency toward learning support functions of LMS powered with Artificial Intelligent (AI) technology and analyzed the differences in perception according to student characteristics. As a result of this study, the function that students considered to be the most important and felt an urgent need to adopt was to give automated grading and feedback for their writing assignments. The functions with the next highest score in importance and urgency were related to receiving customized feedback and help on task performance processed as well as results in the learning progress. In addition, students view a function to receive customized feedback according to their own learning plan and progress and to receive suggestions for improvement by diagnosing their strengths and weaknesses to be both vitally important and urgently needed. On the other hand, the learning support function of LMS, which was ranked as low importance and urgency, was a function that analyzed the interaction between professors and students and between fellow students. It is expected that the results of this student needs analysis will be helpful in deriving the contents of learning support functions that should be developed as well as providing basic information for prioritizing when applying AI technology to implement learner-centered LMS in the future.

• International Commerce and Information Review
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• v.12 no.1
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• pp.271-295
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• 2010

In this study, we investigate the relationships among organizational market orientation, learning orientation, information technology(IT) support for firm resource, IT support for strategy, and balanced scorecard(BSC) performance in export firms. The development of the research model is based on the empirical studies of strategy and resource-based view. The data from the survey was analyzed using Partial Least Squares(PLS). The results from the empirical model suggest that IT support for firm resource is effected by market orientation and learning orientation. And, IT support for strategy is enhanced by IT support for firm resource. Finally, BSC performance of export firms is effected by IT support for strategy.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.769-779
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• 2020

Self-efficacy has been extensively evaluated, but no studies have investigated the effect of self-efficacy on the self-reliance of women in poor-households economic productivity. This study analyzes self-efficacy as a personal factor, learning processes, and social support as an environmental factor towards the achievement of self-reliance in women from poor-households in productive economy businesses. Despite the dominant logic of this scheme, there is a need for field-based data regarding whether the variable really supports the sustainable empowerment of poor-households women. This study used the quantitative method through the survey technique. The samples of this study included 250 people collected from five regencies in Indonesia by using a multiple-stage random sampling. The data were analyzed with structural equation modeling. The results show that social support has a significant positive impact on the learning process; social support has a direct negative impact on self-efficacy. The learning process has a direct positive influence on self-efficacy, while social support has a non-significant impact on self-reliance. The learning process has a direct influence on self-reliance. Social support and the learning process both have significant positive impact on self-efficacy. Social support, learning process, and self-efficacy simultaneously have a positive impact on self-reliance in productive economic activities.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.55-61
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• 2021

In this study, a learning environment based on STEAM theory was proposed to support and improve learners' activities and achievements for convergent design education. The learning environment design influence STEAM education with intentional design and schedule coordination, schools can create informal environments that are crucial to STEAM education. The physical surroundings of the learning space should be applied to teaching methods and learning activity, especially for STEAM-based education, physical space conditions should support the learner's design thinking and process. Furthermore, STEAM-based education environment should support a vast array of experiences that allow students to learn the context around ideas and skills. For spaces for learning environment based on STEAM, common design principles should be considered such as technology integration, safety and security, transparency, multipurpose space, and outdoor learning. Therefore, the learning environment based on STEAM needs flexible and mobile, connected, integrated, organized, flipped, and team-focused surroundings to support the learners understand, participate, cooperate, and accomplish the design process.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.2
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• pp.180-202
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• 2012

The purpose of this study was to extract an u-PBL support system core value and design strategy based upon field experience learning. To accomplish this the study, first of all, analyzed the core values, design strategy which was selected after needs analysis and literature review of theories and cases regarding the PBL, e-PBL, blended-PBL, Field experience learning based on ubiquitous environment, and learning model based on ubiquitous technology. This study identified the three core values as; systemic support for instructional activity, just in time support for instructional activity and support for interaction facilitation. As further research areas, it might be useful to develop u-PBL instructional support system based upon the model designed from this study. Also, research concerning the verification of the model based upon implementation of the program case might be necessary.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.196-201
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• 2008

Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.