• Journal of The Korean Association For Science Education
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• v.27 no.6
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• pp.529-545
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• 2007

Questioning forms an integral part of most strategies for effective teaching when the class consists of difficult content. Science including chemistry is usually content-rich, but difficult to understand without supporting lab experiments, subsidiary visual materials and model kits. Engaging the attention and interest of students in such a subject, therefore, is the key to the success of a daily lesson in the classroom. However, generating meaningful questions requires a certain level of information and metacognitive skills on the part of the teacher. The purpose of this study was to find out the framework of effective teachers' questioning with a large group in chemistry class: how teachers used questioning to engage their students in such a big class, to identify a variety of forms of feedback provided by students and to develop a model of question-inducing strategies. We investigated the teachers' recognition of their questioning and the students' recognition of teachers' questioning by surveying over 82 teachers and 434 students in Korea. The survey findings show that the questionnaire can be categorized into four elements: the theme of the teachers' questions (T), students' inquiries (I), methods of teachers' questioning (M) and encouragement of students (E). These elements can be analyzed and sub-categorized to find out which elements are effective in good questioning, even though the elements are interwoven tetrahedrally.

• Journal of Information Science Theory and Practice
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• v.8 no.2
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• pp.18-31
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• 2020

Cognitive biases can influence human information behaviour and decisions made in information behaviour and use. This study aims to identify the biases involved in some aspects of information behaviour and the role they play in information behaviour and use. Twenty-five semi-structured face-to-face interviews were conducted in an exploratory qualitative study with graduate (MA and PhD) students who were at the stage of their dissertation/thesis research. Eisenberg & Berkowitz Big6^TM Skills for Information Literacy was adopted as a framework for interviews and the analysis was done using grounded theory coding method. The findings revealed the presence of twenty-eight biases in different stages of information behaviour, including availability bias (affects the preference for information seeking strategies), attentional bias (leads to biased attention to some information), anchoring effect (persuades users to anchor in special parts of information), confirmation bias (increases the tendency to use information that supports one's beliefs), and choice-supportive bias (results in confidence in information seeking processes). All stages of information seeking were influenced by some biases. Biases might result in a lack of clarity in defining the information needs, failure in looking for the right information, misinterpretation of information, and might also influence the way information is presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.855-860
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• 2018

The IT technologies applying to IoT(Internet of Things), Big Data, and AI(Artificial Intelligence) are needed in the era of 4th industrial revolution. So, the IT convergence courses of computer science major which will be required in the companies in order to prepare the crises of 4th industry revolution are necessary. And, one approach to cope with this problem is the training of IT convergence man power based on NCS(National Competency Standard) education. In this paper, we propose and analyze the NCS education courses for computer science major in order to teach the students who are needed in the Korean domestic companies preparing the 4th industrial revolution. The skills and applications of Chatbot, Blockchain, and CPS(Cyber Physical System) for the post mobile and post Internet technologies are included in the proposed courses.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.853-863
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• 2022

In order to revitalize start-ups in the beauty field, this study attempted to derive characteristic patterns of changes in demand and differences in emotions and meaning for 'beauty start-ups' by dividing the period by year from 2019 to 2021 based on exploratory data analysis (EDA). Most of the search terms related to the keyword "beauty start-up" showed more interest in institutions or certificates that can learn beauty skills than professional start-up education, which still does not recognize the importance of start-up education, and as an alternative, it is necessary to develop customized start-up education programs for each major. We establish hypotheses through exploratory data analysis and verify hypotheses by combining traditional corroborative data analysis (CDA). There has never been an exploratory data analysis method for beauty startups, and rather than mentioning the need for formal start-up education, analyzing changes in interest in beauty startups and the requirements of prospective start-ups with exploratory data will help develop customized start-up programs.

• The Journal of Korean Association of Computer Education
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• v.16 no.6
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• pp.21-32
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• 2013

Since creativity has been emphasized and creative problem solving has also been a big topic recently, various kinds of research works have proceeded. Among them, this paper focuses on abstract thinking and growth mindset, which affect on problem solving. Also, this paper analyzes what kinds of relationships time perspectives and smart-phone addiction have with the two factors and how they influence on them. In order to do so, we survey on 441 primary, middle, high school, and college students. Our analysis results cover the relationships among the two factors, smart-phone addiction level, present-hedonic perspective, and future time perspective. In addition, we analyze the relationship among the factors with a structural equation model. By doing these, we propose educational alternatives in terms of time and plan to improve our adolescent's abstract thinking level, which helps their problem solving skills and their academic achievement.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.6-20
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• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.305-318
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• 2022

We focused on the care effectiveness of the interactive AI robots. developed an AI toy robot called 'Agaya' to contribute to personalization with more human-centered care. First, by applying P-TTS technology, you can maximize intimacy by autonomously selecting the voice of the person you want to hear. Second, it is possible to heal in your own way with good memory storage and bring back memory function. Third, by having five senses of the role of eyes, nose, mouth, ears, and hands, seeking better personalised services. Fourth, it attempted to develop technologies such as warm temperature maintenance, aroma, sterilization and fine dust removal, convenient charging method. These skills will expand the effective use of interactive robots by elderly people and contribute to building a positive image of the elderly who can plan the remaining old age productively and independently

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.801-806
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• 2022

In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.