• Journal of Korean Physical Therapy Science
• /
• v.9 no.3
• /
• pp.179-186
• /
• 2002

This study addresses the need to adopt teaching-learning approaches in physical therapy education that develop links between theory and clinical practice in a meaningful way. Problem-based learning (PBL) is presented as a useful way to educate physical therapy for the future. The essential characteristics of problem-based learning include: curricular organization around problems rather than disciplines; an integrated curriculum rather than one separated into clinical and theoretical components; and an inherent emphasis on cognitive skills as well as on knowledge. PBL as implemented in the health sciences, is an educational method in which the focus of learning is a small-group tutorial in which students work through health care scenarios. The goals of the health care scenarios are to provide a context for learning, to activate prior knowledge, to motivate students, and to stimulate discussion. Learning is student-centered rather than faculty-centered, and self-directed learning is emphasized. Whereas the former focuses on critical thinking and clinical judgement, the latter's emphasis is on clinical competency. The physical therapist (PT) program at Cheju Halla college is a partial integrated problem-based curriculum. The history and process of PBL in general and in the PT program are reviewed. Long-term advocates of PBL stress that it is the only known method for preparing future professionals to be able to adapt to change, learning how to reason critically, enabling a holistic approach to health.

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.263-273
• /
• 2020

The purpose of this study is to check mediating effect of middle school students' peer attachment on relation between self-esteem and intrinsic learning motivation. To this end, this study collected data by measuring the level of self-esteem, peer attachment, and intrinsic learning motivation for 457 male and female middle school students (225 male and 232 female students) located in S city, Jeollanam-do. The results of this study are as follows: The correlation between self-esteem, peer attachment and intrinsic learning motivation of middle school students was all significant. Self-esteem had a significant effect on peer attachment and intrinsic learning motivation, and peer attachment also had a significant effect on intrinsic learning motivation. Meanwhile, Peer attachment showed a partial mediating effect between self-esteem and intrinsic learning motivation. The mediating effect of peer attachment was different according to grade. Through this study, it was confirmed that the self-esteem of middle school students influences peer attachment, and that peer attachment influenced by self-esteem can influence intrinsic learning motivation. The implications and limitations of this study were also discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.6
• /
• pp.25-32
• /
• 2012

In this paper, we proposed a development of M-learning smart-trainer content for improving the learning ability of military education. Learners of time and space constraints beyond quickly and accurately can learn with the goal, each subject by partial learning, and repetition, the whole learning quickly and easily by selecting efficiently to help you learn a m-Bizmaker with applications was designed. Experiment targets the military company of two, first aid courses were conducted for the evaluation. Traditional collective comparison group teaching methods, the proposed content, teaching methods applied in the experimental group were selected. The proposed learning applications using smart instructor for verification of learning, with which to compare, test subjects were compared with each of 49 subjects, the results p<.005 level, there was difference among the two groups. Therefore, the proposed application using a smart trainer after class proved that contribute to improving achievement.

• Journal of Convergence for Information Technology
• /
• v.12 no.4
• /
• pp.31-37
• /
• 2022

The purpose of this study was to identify the effects of family strength as a parameter on the relationship between grit, and learning satisfaction of university students. The grit scale, family strength scale and learning satisfaction scale were applied to data from surveys conducted on 194 students recruited from a university in G gun, C province. This study examined the mediating effects of family strength in relation to grit and learning satisfaction using the hierarchical regression analysis. Results showed that family strength had partial mediating effects in the between grit and learning satisfaction. Therefore, it seems that grit directly and indirectly affect learning satisfaction through family strength. This result indicates that the importance of family strength for learning satisfaction and suggest that family strength should be included in developing learning satisfaction improvement programs.

• Journal of KIISE:Software and Applications
• /
• v.34 no.12
• /
• pp.1045-1055
• /
• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• Journal of Digital Convergence
• /
• v.10 no.5
• /
• pp.89-103
• /
• 2012

This paper analyzed the effect of learning motivation and conation(endurance, effort) on the consultant' entrepreneurship(innovativeness, proactiveness, risk- taking) and competencies(ability, knowledge, attitude), and the mediating effect of the entrepreneurship on the consultant's competencies. The result shows that the learning motivation and conation have a positive impact on the partial factors of the consultant's entrepreneurship(innovativeness, proactiveness) and competencies(ability, knowledge), but not impact on the risk- taking and the attitude. Innovativeness and proactiveness have an positive impact on the consultant's competencies, but not the risk-taking. Innovation and proactiveness fully mediated the effect of learning motivation on the ability, and partially mediated on the knowledge. The effect of learning conation on the ability and knowledge was partially mediated by the innovation, not by the proactiveness. This study shows that the management of the learning motivation and conation, the education of entrepreneurship(innovativeness, proactiveness) are very important for the cultivating the consultant' competencies.

• Journal of the Korea Convergence Society
• /
• v.9 no.2
• /
• pp.349-357
• /
• 2018

The purpose of this study was to identify the self-determination motivation on learning flow by college nursing students and the mediation effects of metacognition. A sample of 145 subjects were recruited from two university in G city. And data were collected from Nov 21 to Nov 30, 2016. Data were analyzed using with SPSS 22.0. The factors affecting the learning flow were self-determination motivation, planing and monitoring of metacognition, sex and explanatory power was 66.3%. All of the metacognition factors had a partial mediating effect in the relationship between self-determination motivation and learning flow. This study is to provide basic data to develop the nursing education method to improve learning flow in the field where self regulated learning is increasing.

• Journal of Digital Convergence
• /
• v.12 no.3
• /
• pp.105-115
• /
• 2014

This paper aims to examine the mediating effects of psychological capital on the relationships between learning organization and innovative behavior. 310 sheets of questionnaires were gathered from the organizational members of the companies in 5 cities, including Seoul and Pohang and analysed using structural equation modelling technique. The results show followings: First, the human factor of learning organization has a significant influence to the innovative behavior and the psychological capital. Second, structural factor of learning organization has a significant influence to the psychological capital but does not have a significant influence to the innovative behavior. Third, the mediating effect of psychological capital has a significant partial effect between human factor of learning organization and innovative behavior, and full effect between structural factor of learning organization and innovative behavior. The results of this study implies that some guideline could be used in promoting learning organization and making implementing strategy.

• Journal of KIISE
• /
• v.42 no.11
• /
• pp.1452-1458
• /
• 2015

Korean Morphological Analysis is a difficult process. Because Korean is an agglutinative language, one of the most important processes in Morphological Analysis is Morpheme Recovery. There are some methods using Heuristic rules and Pre-Analyzed Partial Words that were examined for this process. These methods have performance limits as a result of not using contextual information. In this study, we built a Korean morpheme recovery system using deep learning, and this system used word embedding for the utilization of contextual information. In '들/VV' and '듣/VV' morpheme recovery, the system showed 97.97% accuracy, a better performance than with SVM(Support Vector Machine) which showed 96.22% accuracy.

• Journal of Korean Association for Spatial Structures
• /
• v.21 no.2
• /
• pp.99-110
• /
• 2021

This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.