• Asia Pacific Journal of Corpus Research
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• v.2 no.1
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• pp.1-11
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• 2021

Recently, corpus assisted vocabulary instruction has been attracting a lot of interest. Most studies have focused on understanding language learners' receptive vocabulary knowledge. Limited attention has been paid to learners' productive competence. To fill this gap, this study attended to learners' productive lexical development in terms of form, meaning and use respectively. This study introduced EFL learners to the corpus-based language pedagogy to learn COVID-19 theme-based vocabulary. To investigate the gains and views of 33 EFL first-year college students, a sentence completion task and a questionnaire were developed. Learners' productive performances in the three lexical knowledge aspects (i.e., form, meaning and use) were particularly targeted. The results revealed that the students achieved significant gains in all aspects regardless of their proficiency level. In particular, the less proficient students achieved greater knowledge retention compared with their highly proficient counterparts. Meanwhile, students showed positive attitudes towards the corpus-based approach to vocabulary learning.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.163-168
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• 2024

Technologies that are considered to be a part of the fourth industrial revolution include holograms, augmented reality, and virtual reality. As technology advances, the industry's scale is growing quickly as well. While the development of technology for direct use is moving slowly, awareness of floating holograms-which are considered realistic content-is growing as the industry's scale and rate of technological advancement continue to accelerate. Specifically, holograms that have been incorporated into museums and exhibition spaces are static forms of content that viewers gaze at inertly. Additionally, their use in educational fields is very passive and has a low rate of utilization. Therefore, in order to improve usability from the viewpoint of viewers of realistic content, such as exhibition halls or museums, we introduce realistic content control technology in this study using a machine learning framework to recognize hands. It is anticipated that using the study's findings, manipulating realistic content independently will enhance comprehension of objects presented as realistic content and boost its applicability in the industrial and educational domains.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.368-391
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• 2018

Face recognition (FR) with a single sample per person (SSPP) is common in real-world face recognition applications. In this scenario, it is hard to predict intra-class variations of query samples by gallery samples due to the lack of sufficient training samples. Inspired by the fact that similar faces have similar intra-class variations, we propose a virtual sample generating algorithm called k nearest neighbors based virtual sample generating (kNNVSG) to enrich intra-class variation information for training samples. Furthermore, in order to use the intra-class variation information of the virtual samples generated by kNNVSG algorithm, we propose image set based multimanifold discriminant learning (ISMMDL) algorithm. For ISMMDL algorithm, it learns a projection matrix for each manifold modeled by the local patches of the images of each class, which aims to minimize the margins of intra-manifold and maximize the margins of inter-manifold simultaneously in low-dimensional feature space. Finally, by comprehensively using kNNVSG and ISMMDL algorithms, we propose k nearest neighbor virtual image set based multimanifold discriminant learning (kNNMMDL) approach for single sample face recognition (SSFR) tasks. Experimental results on AR, Multi-PIE and LFW face datasets demonstrate that our approach has promising abilities for SSFR with expression, illumination and disguise variations.

• International Journal of Knowledge Content Development & Technology
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• v.13 no.3
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• pp.7-30
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• 2023

Nigeria is a country with multiple ethnic groups; as a result, English language is used as a lingua franca to enhance information flow. Despite this, the Indigenous languages of communities are mostly used for interactions, even in university environments thereby affecting smooth interaction for those who do not understand them. This study therefore investigated the impact of being a linguistic outsider on information access, learning and social wellbeing of students. Descriptive research of a case study was used for this study. The population for this study consisted of non-Yoruba indigenous students. Judgmental sampling technique was used to select 50 non-indigenous students; structured interview was used. Results showed that Yoruba indigenous language was used lightly in the classroom and heavily outside the classroom, with mixtures of pidgin and English languages. It was found that being a linguistic outsider had a negative influence on information access. However it was not a total dependent factor to social wellbeing of students who desire for their various languages to be predominantly used and for them to enjoy equal benefits with Yoruba indigenes. This study also revealed that being a linguistic outsider does not have negative influence on academic learning. It was recommended that the stakeholders in university management promote the complete use of English language in the classroom while students should be encouraged to interpret Yoruba language when spoken in the midst of non-indigenes.

• Korean Journal of Culture and Social Issue
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• v.16 no.2
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• pp.103-124
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• 2010

The purpose of the present study was to examine the relationships among private tutoring hours, academic motivation, use of learning strategies, and academic achievement test scores using structural equation modeling. The sample consisted of 3,607 7th graders from Korean middle schools who were included in the Korean Education Longitudinal Study. The results suggest that there was no evidence that the private tutoring hours predicted students' motivation and learning strategy use. It was found that the private tutoring hours predicted achievements in English and Math, but it was negligible in magnitude. As for achievement test scores, academic motivation and the use of learning strategies played more critical role rather than the private tutoring hours.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.1-9
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• 2007

The purpose of this study is to develope a criterion for evaluation on game-type learning programs by the application of HCI(Human Computer Interaction) theory. And to analyze game-type learning programs for elementary students on the criterion developed in this study. The HCI theory, which deals with principles or methods for developing systems people can use conveniently and pleasantly, has been applied to overall area of program development. And it also has been widely used to evaluate learning programs. However, there have been few studies on a game-type learning program evaluation on the basis of the HCI theory. This paper shows that evaluation criteria are developed on three viewpoint bases : usefulness, usability, and affect which are as elements in HCI. And analyzes the game-type learning programs from these three points of view. The evaluation criteria developed in this study can be applied to a basis for evaluation on game-type learning programs, and the analysis will be able to be a useful guide to game programers as well as its users.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.483-500
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• 2005

The purpose of the study was to explore the conceptual and theoretical fundamentals of learning object. Learning object, a new paradigm for instructional design in the era of information technology, has attracted much research efforts since it has lots of advantages in terms of production efficiency and use effectiveness. A theory for the systematic design of this new instructional design, however, looks far from mature. Since the birth of the idea of a learning object has been found in the field of computer software design, such as object-oriented software development, learning object does not have enough theoretical underpinnings in terms of learning and instruction. The researcher tried to establish theoretical foundations for this new, alien concept as a learning design theory. Relevant research efforts and discourses have been discussed for this purpose.

• Informatization Policy
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• v.26 no.1
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• pp.46-61
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• 2019

The Fourth Industrial Revolution has been revolutionizing industry and education. This paper proposes an education platform, Smart Space EduPlatform (SSEP), for the real estate industry, aimed at educating the basic real estate technology (RETech) for workers in the real estate industry so they can achieve the highest and best use of the real estate in the smart environment. The habitat of SSEP is driven by the donation system ensuring sustainability, various technical functions such as tools for content production and learning participation, and learning behavior frameworks each in form of a learner, a teacher, and a helper. Services of SSEP consist of 17 important RETech lectures under 6 categories-planning and design, decision-making, management, economics, construction, and equipment-and project-based learning (PBL) curriculums. The lectures are provided along with video contents, additional learning materials and learning management service, while teachers' workshops, learner invitation and registration management, curriculum operation services are offered for the PBL curriculums.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.107-126
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• 2021

In e-commerce, rapid and accurate automatic product classification according to product information is important. Recent developments in deep learning technology have been actively applied to automatic product classification. In order to develop a deep learning model with good performance, the quality of training data and data preprocessing suitable for the model are crucial. In this study, when categories are inferred based on text product data using a deep learning model, both effects of the data preprocessing and of the selection of training data are extensively compared and analyzed. We employ our CNN model as an example of deep learning model. In the experimental analysis, we use a real e-commerce data to ensure the verification of the study results. The empirical analysis and results shown in this study may be meaningful as a reference study for improving performance when developing a deep learning product classification model.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1007-1014
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• 2022

Compact Advanced Satellite 500 (CAS500) can be used for various purposes, including vegetation, forestry, and agriculture fields. It is expected that it will be possible to acquire satellite images of various areas quickly. In order to use satellite images acquired through CAS500 in the agricultural field, it is necessary to develop a satellite image-based extraction technique for crop-cultivated areas.In particular, as research in the field of deep learning has become active in recent years, research on developing a deep learning model for extracting crop cultivation areas and generating training data is necessary. This manuscript classified the onion and garlic cultivation areas in Hapcheon-gun using PlanetScope satellite images and farm maps. In particular, for effective model learning, the model performance was analyzed according to the proportion of crop-cultivated areas. For the deep learning model used in the experiment, Fully Convolutional Densely Connected Convolutional Network (FC-DenseNet) was reconstructed to fit the purpose of crop cultivation area classification and utilized. As a result of the experiment, the ratio of crop cultivation areas in the training data affected the performance of the deep learning model.