• Educational Technology International
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• v.13 no.2
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• pp.233-255
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• 2012

The purpose of this study is to examine the relationships among the factors that affect technology knowledge, learning strategies with technology, and academic self-efficacy of college students. Technology and its utilizing ability is a critical competency for the learners to acquire to live in the Digital Era of 21st century. However, little is known about how the competency involving technology affects academic self-efficacy. To address the aim of the study, a survey was conducted with 39 questions including technology knowledge, learning strategies with technology, and academic self-efficacy targeting 137 students in A university. The result of the structural equation modeling shows that the technology knowledge of college students indirectly influences the academic self-efficacy. The learning strategies with technology are mediating variable linking technology knowledge with academic self-efficacy. Technology knowledge explains 71% of variance in learning strategies with technology. Therefore, college students need to keep up with knowledge of technology and improve learning strategies with technology to activate academic self-efficacy.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.189-191
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• 2014

This paper provides an overview of the E-learning service education on the last decade, In the early 2000's the emphasis of educational technology was on interactive multimedia- stand alone packages on computer hard disks or portable memory, which integrated a range of media forms in the lately. Customers handle finding the best sources of content.The system then uses social signals such as those coming from Facebook, Twitter, LinkedIn, delicious as well as clicks and views. The SNS and network infrastructure is sufficiently mature that the focus should shift to how to use the technology most appropriately to facilitate learning. As we study environmental conditions of the traditional internet and the mobile internet users in some ways. In this paper, analyze the nature of learning, role of educational and suggest alternative policy, innovation of e-learning service and effective e-learning environment in developing technology.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.739-748
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• 2016

This study quantitatively measured the impact of blended learning with smart devices for learning satisfaction. It is targeted in specialized domestic company with IT Service which build smart learning systems and utilize for employee training. Specifically, it empirically analyzed that learning attitude(Self-efficacy, Self-innovativeness, Perceived usefulness, Perceived ease of use) with smart devices affect acceptance of smart learning and offline face-to-face learning satisfaction. As a result, the learning attitude of the smart learning gave a positive effect on the acceptance of the smart learning and then acceptance of the smart learning gave a positive effect on offline face-to-face learning satisfaction. Additionally learning the attitude of the smart learning even gave a positive impact, as well as the acceptance of smart learning experience in offline training. It imply that this variables of smart-learning attitude affect the self-directed learning and positive learning experience.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.169-180
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• 2021

Since machine learning was invented, there have been many different machine learning-based algorithms, from shallow learning to deep learning models, that provide solutions to the classification tasks. But then it poses a problem in choosing a suitable classification algorithm that can improve the classification/detection efficiency for a certain network context. With that comes whether an algorithm provides good performance, why it works in some problems and not in others. In this paper, we present a data-centric analysis to provide a way for selecting a suitable classification algorithm. This data-centric approach is a new viewpoint in exploring relationships between classification performance and facts and figures of data sets.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.4
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• pp.648-661
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• 2011

The purpose of this study was to examine the school parent and student's perception of Practical Arts and Technology Home Economics and to suggest plan to school parent of multicultural and learning disability families. The subjects of this study were elementary and secondary teachers who teaching Practical Arts or Technology Home Economics. The instrument of this study was questionnaire including five sections: influence on students by Practical Arts and Technology Home Economics, interest in Practical Arts and Technology Home Economics to school parents, school support with learning ability improvement, school parents support with home in Practical Arts and Technology Home Economics, data form of school parents support with home in Practical Arts and Technology Home Economics. The findings of this study were as follows; Sociality development of students is influential by Practical Arts and Technology Home Economics. School parents and students believe important subjects in Practical Arts and Technology Home Economics. Teachers ask for support with learning ability improvement for practical training space and programs in Practical Arts and Technology Home Economics. School parents ask for support with learning ability improvement of programs of teaching learning method for home education on Practical Arts and Technology Home Economics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.610-632
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• 2024

Mobile Learning (M-learning) adoption and success in supporting students' learning engagement mainly depend on many factors. Therefore, this study systematically reviews the literature, synthesizes and analyzes the predictors of M-learning adoption, and uses success for students' learning engagement. Literature from 2016 to 2023 in various databases is covered in this study. Based on the review's findings, the factors that influence students' learning engagement when it comes to M-learning usage and adoption, can be divided into technical, pedagogical, and social factors. More specifically, technical factors include mobile devices availability and quality, connectivity to the internet, and user-friendly interfaces, pedagogical factors include effective instructional design, teaching methods, and assessment strategies, and social factors include motivation of students, social interaction and perceived enjoyment - all these factors have a significant impact on the M-learning adoption and use success. The findings of the review also indicated that M-learning has a key role in enhancing the learning engagement of students through different ways, like increasing their motivation, attention, and participation in their process of learning, paving the way for interaction and building relationships opportunities with peers and instructors, which in turn, can lead to strengthening the learning environment. The implications of these findings extend beyond immediate educational contexts, offering vital insights for future educational technology strategies and policy decisions, particularly in addressing global educational challenges and embracing technological advancements in learning.

• Journal of Engineering Education Research
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• v.18 no.2
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• pp.77-88
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• 2015

Recently, there has been an increasing interest in 'Flipped Learning,' an IT-based learner-centered teaching-learning method corresponding to meet the paradigm of the future education. For smooth Flipped Learning, there are three steps in total: a pre-class should precede; then, in the structure of classes in the classroom, in-class learning among peer learners should be done; and lastly, the operation of a post-class should be done. For successful Flipped Learning, class elements in each step should be designed with a time difference, interconnected so as to achieve a single educational objective. However, it was found that there was a limitation in that the teaching-learning model of the preceding Flipped Learning consisted of the order of analysis, design, development, implementation and evaluation as general procedures, so it would not sufficiently consider the situations of Flipped Learning only. On this background, this thesis proposes a differentiated Flipped Learning model for mastery learning in a subject of an institute of technology as a model of systematic instructional design and presents a case of a class applied to an actual subject of computer engineering.

• Educational Technology International
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• v.19 no.2
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• pp.199-228
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• 2018

The main purposes of this study were (a) to analyze the research trend of educational use of tangible technology, (b) to identify tangible learning mechanisms, and potential benefits of learning with tangible technology, and (c) to provide references and future research directions. We conducted a systematic literature review to search for academic papers published in recent five years (from 2013 to 2017) in the major databases. Forty papers were coded and analyzed by the established coding framework in four dimensions: (a) basic publication information, (b) learning context, (c) learning mechanism, and (d) learning benefits. Overall, the results show that tangible technology has been used more for young learners in the kindergarten and primary school contexts mainly for science learning, to achieve both cognitive and affective learning outcomes, by coupling tangible objects with tabletops and desktop computers. From the synthesis of the review findings, this study suggests that the affordances of tangible technology useful for learning include embodied interaction, physical manipulations, and the physical-digital representational mapping. With such technical affordances, tangible technologies have the great potential in three particular areas in education: (a) learning spatial relationships, (b) making the invisible visible, and (c) reinforcing abstract concepts through the correspondence of representations. In conclusion, we suggest some areas for future research endeavors.

• Asia pacific journal of information systems
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• v.31 no.1
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• pp.43-75
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• 2021

Clearly, the smartphone is increasingly playing a greater role in everyday life, thus providing opportunities to evaluate how well the use of the smartphone meets the requirements of undergraduate students in independent learning outside of a classroom setting. This study used the task-technology fit (TTF) model to explore the effectiveness of smartphone usage to interact with learning materials in independent learning outside of classrooms, the need for smartphone support, and the fit of devices to tasks as well as performance. First, the study used interviews, observation, and survey data to identify what are the most important constructs of smartphones that stimulate students to interact with learning materials in independent learning outside of classrooms. Based on the findings from the exploratory study and Task Technology Fit theory, we postulated the Navigation design, Ergonomic design, Content support, and Capacity as the essential dimension of the smartphone construct. Then, we proposed a research model and empirically tested hypotheses with the structural model analysis. The results reveal a significant positive impact of task and technology on TTF for smartphone usage to interact with learning materials in independent learning outside of classrooms; it also confirmed the TTF and performance have a direct effect on actual use.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.262-265
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• 2018

Deep learning, a sub-field of machine learning changing the prospects of artificial intelligence (AI) because of its recent advancements and application in various field. Deep learning deals with algorithms inspired by the structure and function of the brain called artificial neural networks. This works reviews basic architecture and recent advancement of deep structured learning. It also describes contemporary applications of deep structured learning and its advantages over the treditional learning in artificial interlligence. This study is useful for the general readers and students who are in the early stage of deep learning studies.