• Journal of the Korean earth science society
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• v.26 no.6
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• pp.469-476
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• 2005

The objective of this study is to investigate the effects of a new learning method called, 'e-Learning,' by applying this method on a middle school science curriculum and study the influence it has on the students’ short and long term memory. The study was performed on two classes of sixth grade students at 'K middle school' in Yangsan. By handing out structured study assignment in e-Learning, I was able to observe how it affected the learners’ short and long term retention. The results of the study were as follows: First, classes that underwent studies using e-Learning did not show any influence on short term retention. Second, e-Learning had positive influence on long term retention. Third, learners who experienced e-Learning had positive cognition on e-Learning.

• The Journal of Korean Association of Computer Education
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• v.12 no.5
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• pp.35-47
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• 2009

Just as noted in some studies related to U-learning based on the ubiquitous technology, it is required to reflect both factors of the environments and contexts of learners on the teaching and learning strategy. For this, the current paper suggests an inquiry learning method and a mobile learning support device for the inquiry learning. Since the inquiry learning is operating on the basis of the contents that learners themselves experience in the fields, it naturally leads them to position in the learning environments and contexts. In this study some curricula are adopted and transformed for the inquiry learning, and the developed mobile device for the learning has a guide function, so that learners might follow the inquiry learning process. In addition, it is possible to reuse the acquired learning data by storing them on a remote learning sever, which may support the inquiry learning of students. These system and device are applied in the teaching sites of schools and, consequently, it is found that in regard with the learning interest and academic performance of students there is an advanced result, being statistically significant.

• Korean Medical Education Review
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• v.14 no.2
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• pp.64-68
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• 2012

Learning in medical school is usually regarded as a very specialized type of learning compared to that of other academic disciplines. Medical students might have general beliefs about their own learning. Beliefs about learning have a critical effect on learning behavior. There are several factors that affect medical students' learning behavior: epistemological beliefs, learning styles, learning strategies, and learning beliefs. Several studies have addressed epistemological beliefs, learning styles, and learning strategies in medical education. There are, however, few studies that have reported on medical students' beliefs about learning. The purpose of this study was to determine what learning beliefs medical students have, what the causes of these beliefs are, and how medical educators teach students who have such beliefs. In this study, the five learning beliefs are assumed and we considered how these beliefs can affect students' learning behaviors. They include: 1) medical students are expected to learn a large amount of information in a short time. 2) memorization is more important than understanding to survive in medical schools. 3) learning is a competition and work is independent, rather than collaborative. 4) reading textbooks is a heavy burden in medical education. 5) the most effective teaching and learning method is the lecture. These learning beliefs might be the results of various hidden curricula, shared experiences of the former and the present students as a group, and personal experience. Some learning beliefs may negatively affect students' learning. In conclusion, the implications of medical students' learning beliefs are significant and indicate that students and educators can benefit from opportunities that make students' beliefs about learning more conscious.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.5
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• pp.1478-1491
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• 2016

This study has designed to find out the effects of a project-based flipped learning model at universities on the self-directed learning ability, the self-leadership, and the learning competency. For the study, two procedures were performed. First, a flipped learning model for a project-based learning was developed on the basis of the literature reviews. The flipped learning model has three different steps: the pre-class, the in-class, and the post-class. In the pre-class, instructors provide mini-core courses using various technologies for learners outside the class. The in-class is the step to check whether learners prepare their learning or not. Also, in this step, the in-death learning and the teaching-learning process by interaction between instructors and learners would be performed. In the post-class, learners would be able to sustain the extended learning to develop the learning tasks and activities after flipped learning class. Through this step, the learners could be experienced integrated thinking and application, documentation and management, as well as sharing and spread of their learning. Second, the effectiveness of the developed flipped learning model on the self-direction, the self-leadership, and the learning competency was examined. The quantitative research method and the qualitative research method were used for this study. The results indicated that the flipped learning model showed improvement on the self-direction, the self-leadership, and the learning competency.

• Journal of Digital Convergence
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• v.6 no.2
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• pp.135-143
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• 2008

The remarkable growth of the Internet since mid-l990s has expanded the e-learning market and brought the transformation of educational environments and methodology. It can be said that the e-learning has changed the educational paradigm. Korean government is firmly determined to support the diffusion of e-learning because of the benefits of e-learning. People seem to accept the e-learning when its contents have high quality. A lot of research have been conducted on e-learning, however, it was mostly about user's usage intention, satisfaction and educational effect. It can't seem that sufficient research efforts have been put into figuring out the role of e-learning contents quality in the expansion of e-learning. In this paper, we present the empirical study on the influence of e-learning contents quality on user's satisfaction and educational effect. We conducted an questionnaire survey on college students to collect data and found that the quality of e-learning contents has significant influence on the users' satisfaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1738-1764
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• 2019

With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and online advertising and so on. This paper introduces deep learning techniques from various aspects, including common models of deep learning and their optimization methods, commonly used open source frameworks, existing problems and future research directions. Firstly, we introduce the applications of deep learning; Secondly, we introduce several common models of deep learning and optimization methods; Thirdly, we describe several common frameworks and platforms of deep learning; Finally, we introduce the latest acceleration technology of deep learning and highlight the future work of deep learning.

• Educational Technology International
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• v.22 no.2
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• pp.255-283
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• 2021

In the early 2020, COVID-19 changed the traditional way of teaching and learning. This paper aimed to explore the impact of college students' perception of course quality on their online learning satisfaction. A total of 4,812 valid samples were extracted, and the difference analysis and hierarchical regression analysis were used to make an empirical analysis of college students' online learning satisfaction. The research results were as follows. Firstly, there was no difference in online learning satisfaction among students by gender and grade. Secondly, learning assessment, course materials, course activities and learner interaction, and course production had a significant positive impact on online learning satisfaction. Course overview and course objectives had an insignificant correlation with online learning satisfaction. Thirdly, the total effect of online learning satisfaction was as follows. Course production had the greatest effect, followed by course activities and student-student interactions, followed by course materials. It was the learning evaluation that showed the least effect. This study can provide empirical reference for college teachers on how to continuously improve online teaching and increase students' satisfaction with online learning.

• Educational Technology International
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• v.23 no.1
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• pp.41-66
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• 2022

Vocabulary learning plays an important role in language learning. This study explored a new paradigm based on social networking site (SNS) supported collaborative learning for vocabulary learning. SNS supported collaborative learning (SSCL) can effectively promote learners' engagement, interest and motivation by providing a more communicative and interactive environment. However, vocabulary learning studies on SSCL mainly focused on the effectiveness and influencing factors, lacking specific instructional strategies. Therefore, this study aims to develop instructional strategies that guide instructors to create an SSCL environment for facilitating vocabulary learning. The final instructional strategies are composed of three stages according to the course process, consisting of 8 general strategies and 21 specific guidelines. The content validity was ensured by four experts in the field of educational technology. The instructional strategies were then applied in an actual classroom with 16 students. The positive responses from the instructor and learners indicated that SSCL can be reasonably incorporated into the current curriculum to provide effective learning opportunities and to promote learners' vocabulary learning.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.215-226
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• 2023

Deep learning has made great strides in the field of unstructured data such as text, images, and audio. However, in the case of tabular data analysis, machine learning algorithms such as ensemble methods are still better than deep learning. To keep up with the performance of machine learning algorithms with good predictive power, several deep learning methods for tabular data have been proposed recently. In this paper, we review the latest deep learning models for tabular data and compare the performances of these models using several datasets. In addition, we also compare the latest boosting methods to these deep learning methods and suggest the guidelines to the users, who analyze tabular datasets. In regression, machine learning methods are better than deep learning methods. But for the classification problems, deep learning methods perform better than the machine learning methods in some cases.

• Educational Technology International
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• v.18 no.2
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• pp.73-99
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• 2017

The learning analytics dashboard (LAD) is a supporting tool for teaching and learning in its personalized, automatic, and visual aspects. While several studies have focused on the effect of using dashboard on learning achievement, there is a research gap concerning the impacts of learners' characteristics on it. Accordingly, this study attempted to verify the differences in learning achievement depending on learning motivation level (high vs. low) and dashboard intervention (use vs. non-use). The final participants were 231 university students enrolled in a basic statistics course. As a research design, a 2 × 2 factorial design was employed. The results showed that learning achievement varied with dashboard intervention and the interaction effect was significant between learning motivation and dashboard intervention. The results imply that the impact of LAD may vary depending on learner characteristics. Consequently, this study suggests that the dashboard interventions should be offered after careful consideration of individual students' differences, particularly their learning motivation.