Viet Xuan TRINH;Duyen Thi Kim NGUYEN;Dat Ngoc NGUYEN;Loc Xuan TRAN;Huong Thi Lan PHAM
Journal of Distribution Science
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v.22
no.1
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pp.69-78
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2024
Purpose: This study is undertaken from the standpoint of student-centered learning and theoretical paradigms that have developed in the business world and display conceptual affinities: the transfer of knowledge and training. Research design, data and methodology: Utilizing questionnaire surveys and multivariate data analysis are two research methodologies (CFA, SEM). Around 201 undergraduate students who were studying in Vietnam provided the data. Results: The results show importance of the faculty role in students' knowledge acquisition. The findings show that Ability to form a good relationship positively influences the development of competence. Additionally, neither ability to develop a good relationship nor learning drive or knowledge acquisition are significantly correlated with one another. The growth of competencies is positively impacted by the suitability of teaching approaches. Knowledge acquisition is favorably impacted by learning motivation, and knowledge acquisition in turn is positively impacted by competence development. Conclusions: Research has shown the important role of lecturers in students' knowledge acquisition. From this result, some implications related to lecturers are also given to help improve students' ability to acquire knowledge. Building good relationships with students (ready to answer questions, positive relationships) and good expertise will help increase learning motivation, ability to acquire knowledge as well as improve development for students.
Comtemporary firms need capability of acquiring external knowledge and internalizing it to cope with environmental fluctuation. The paper analyzes the impact of absorptive capacity, an ability to recognize and utilize external knowledge, on knowledge acquisition of the firm, and examines the role of trust in the knowledge acquisition process. Data were collected from 84 domestic companies that had adopted ERP packages. The results indicate that prior experiences of knowledge acquisition, communication mechanism, and conflict resolution mechanism affect knowledge acquisition positively. Among those independent variables, communication mechanism and conflict resolution mechanism significantly and positively related with trust. Trust is, in turn, positively associated with knowledge acquisition. Meanwhile, previous knowledge base and prior relationship with the knowledge provider do not affect knowledge acquisition. Further, the results provide evidence that trust plays a mediating role between other absorptive capacity factors and knowledge acquisition.
Background: Case-based learning (CBL) is becoming an important approach for improving interprofessional collaboration education. Previous studies have examined learners' satisfaction with interprofessional education (IPE) in medical institutions. However, there are few studies on the implementation of university-led CBL interventions and their direct effects on learning outcomes. The aim of this study was to evaluate the effectiveness of CBL interventions on changes in the participants' perception and knowledge acquisition ability. Methods: The CBL approach consisted of team-based case-based learning, self-directed learning, and post-feedback. It was conducted as a single course for pharmacy students in their 5th year in a university setting. Changes in the participants' perceptions and self-assessments of competence levels were evaluated using survey responses. The effect of the CBL intervention on knowledge acquisition ability was directly evaluated using the exam score. Results: The majority agreed or strongly agreed that team-based case-based learning, and self-directed learning helped them to improve their knowledge and skills to a higher level and to increase the self-assessment of competency level. The average score of knowledge acquisition ability (average score of 75.0, p=0.0098) was significantly higher in the CBL intervention group than the lecture-based learning intervention group (average score of 52.0). Conclusion: The participants positively perceived that CBL intervention helped them to effectively improve their knowledge and the self-assessment of competency level. It also enhanced knowledge acquisition ability. These data, based on the survey responses, suggest that it is necessary to implement CBL interventions in a university-led single professional education.
Future robots, especially service and personal robots, will need much more intelligence, robustness and user-friendliness. The ability to learn contributes to these characteristics and is, therefore, becoming more and more important. Three of the numerous varieties of learning are discussed together with results of real-world experiments with three autonomous robots: (1) the acquisition of map knowledge by a mobile robot, allowing it to navigate in a network of corridors, (2) the acquisition of motion control knowledge by a calibration-free manipulator, allowing it to gain task-related experience and improve its manipulation skills while it is working, and (3) the ability to learn how to perform service tasks ...
Proceedings of the Korean Institute of Intelligent Systems Conference
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2003.09a
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pp.447-450
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2003
In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.
The study examined the effects of explicit derivational morphology instruction (henceforth DMI) on the incidental vocabulary acquisition and reading comprehension of 132 Korean 1st-year high school students who responded to a battery of tests (two vocabulary tests and a reading comprehension test). Multiple statistical tools were used to analyze the data: Analysis of Covariance (ANCOVA), Analysis of Variance (ANOVA), Simple Regression Analysis, Tests of Simple Main Effects, and effect size computation using Cohen's d. The results indicated that (a) DMI enhanced students' ability to infer word meanings in context, (b) DMI promoted high proficiency students' reading comprehension, whereas it impeded intermediate proficiency students' reading comprehension, (c) vocabulary knowledge has a strong positive predictive value for reading comprehension, and (d) the gaps of vocabulary knowledge across proficiency levels were still substantial, despite the observation that DMI promoted students' vocabulary acquisition. These results have a bearing on English as Foreign Language (EFL) reading pedagogy.
Journal of the Korea Academia-Industrial cooperation Society
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v.19
no.4
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pp.154-160
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2018
This thesis aims to develop PBL (Problem-Based-Learning) problems. Its goal is for some groups of students to creative their own problems and to confirm the effectiveness of PBL as they apply it to AI (Artificial Intelligence) in engineering schools. Modern industrial society needs competent people who have abilities in cooperative learning, self-controlled learning, united knowledge application, and creative problem-solving. Universities need to offer their students the opportunity to improve their problem-solving and cooperative learning abilities in order to train the competent people that society demands. PBL activity is an appropriate learning method for the accomplishment of these goals. The study subjects are 37 sophomore students in H University who are studying 'AI'. Five PBL problems were submitted to the class over a period of 15 weeks. The students wrote and submitted a reflective journal after they finished each PBL activity. In addition, they filled out a class evaluation form to assess the performances of each member when the $5^{th}$ PBL problem activity was accomplished. The study shows that the students experienced the effectiveness of PBL in many fields, such as the comprehension of the studied contents (86.48%), comprehension of cooperative learning (94.59%), authentic experience (75.67%), problem-solving skills (89.18%), presentation skills (97.29%), creativity improvement (81.08%), knowledge acquisition ability (86.48%), communication ability (97.29%), united knowledge application (78.37%), self-directed study ability (86.48%) and confidence (97.29%). Through these methods, the students were able to realize that PBL learning activities play an important role in their learning. These methods prepare and enhance their ability to think creatively, work systematically and speak confidently as they learn to become competitive engineers equipped with the knowledge and skills that modern industrial society demands.
The Journal of Asian Finance, Economics and Business
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v.5
no.2
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pp.81-94
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2018
The purpose of this study is to substantiate the affecting factors of informal learning outcomes for professions in various dimensions of an individual and organization. In specific, the study analyzed the effects of learning motivation, job characteristics, and a supportive learning environment which have on task-related knowledge acquisition, adapting to organization and understanding contexts, relationship formation, and improving self-development-ability. The participants of the study were 261 professionals working at four major accounting firms in South Korea. Multiple regression models were applied step by step for analysis. In this study, the informal learning of professionals working at four major accounting firms is influenced by various factors of learning motivation, job characteristics, and a supportive learning environment. The detailed analysis results were as follows. Firstly, peer-support showed the most positive effect on task-related knowledge acquisition. Secondly, for adapting to organization and understanding contexts, task autonomy showed the greatest effect. Thirdly, peer-support was found to be the most important factor for relationship formation. Fourthly, for improving self-development ability, learning goal orientation showed to be the most important factor. The various factors facilitated the professional learning by empirical identification. The study presented practical implications for creating an effective informal learning support environment.
Background: Deficiencies in the ability to maintain balance are common in elderly. Augmented feedback such as knowledge of results (KR) can accelerate learning and mastering a motor skill in older people. Objects: We designed this study to examine whether one session of Wii-Fit game with self-regulated KR is effective for elderly people, and to compare the effect of two different timings of self-regulated KR conditions. Methods: Thirty-nine community-dwelling elders, not living in hospice care or a nursing home, participated in this study. During acquisition, two groups of volunteers were trained in 10 blocks of a dynamic balancing task under the following 2 conditions, respectively: (a) a pre-trial self-regulated KR ($n_1=18$), or (b) a post-trial self-regulated KR ($n_2=21$). Immediate retention tests and delayed retention tests of balancing performance were administered in 15 minutes and 24 hours following acquisition period, respectively. Results: In both groups, significant improvements of balancing performances scores were observed during the acquisition period. Regardless of the group, mean of balancing performance scores on retention tests were well-maintained from the final session. There were no significant differences between groups in balancing performance scores during the acquisition period (p>.05); however, the post-trial self-regulated KR group exhibited significantly higher balancing performance scores in both the immediate retention test and delayed retention test than that of the pre-trial self-regulated KR group (p<.05). Conclusion: Therefore, subjects who regulated their feedback after a dynamic balancing task, during the acquisition period, experienced more efficient motor learning during the retention period than did subjects who regulated their feedback before a dynamic balancing task. Accordingly, in case of presenting the KR of motor learning in clinical settings to elders who reduced dynamic balance abilities, the requesting time of KR is imperative according to self-estimation processes as well as types of KR and practice.
International journal of advanced smart convergence
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v.12
no.2
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pp.34-46
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2023
A growing number of large scale knowledge graphs raises several issues how knowledge graph data can be organized, discovered, and integrated efficiently. We present a novel semantic-based mashup platform for contents convergence which consists of acquisition, RDF storage, ontology learning, and mashup subsystems. This platform servers a basis for developing other more sophisticated applications required in the area of knowledge big data. Moreover, this paper proposes an entity matching method using graph convolutional network techniques as a preliminary work for automatic classification and discovery on knowledge big data. Using real DBP15K and SRPRS datasets, the performance of our method is compared with some existing entity matching methods. The experimental results show that the proposed method outperforms existing methods due to its ability to increase accuracy and reduce training time.
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