• Title/Summary/Keyword: 교수진의 조언

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Information Literacy: Identification of Factors Affecting Undergraduate Students (대학생의 정보리터러시에 영향을 미치는 요인 분석)

  • Oh, Eui-Kyung;Chang, Hye-Rhan
    • Journal of the Korean Society for Library and Information Science
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    • v.39 no.4
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    • pp.207-231
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    • 2005
  • The study Is attempted to identify the factors affecting information literacy among undergraduate students. Through literature review, exposure to related education, use experiences in information resources, advice of the faculty, individual background are considered as variables affecting information literacy attitudes and performance. A questionnaire was devised and collected data from 628 students. Then 24 hypotheses were tested statistically. Descriptive analysis shows differences in information literacy, lower exposure to library instruction, and lack of the faculty advice. Results of the hypotheses testing shows computer and internet education, use experience of the various information resources, gender and major areas of study as factors affecting information literacy. Based on the results, recommendations are suggested to improve the information literacy.

A study of DISC Behaviour Patterns on the satisfaction difference of Comic-Animation Department students : Focusing on satisfaction in the major and satisfaction of the university life (DISC 행동유형에 따른 만화애니메이션학과 대학생들의 만족도 차이 연구 - 전공만족도와 대학생활만족도를 중심으로)

  • Kim, Shin
    • Cartoon and Animation Studies
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    • s.47
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    • pp.217-239
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    • 2017
  • The purpose of this research is to maximize the core competencies by objectively measuring the Behaviour Patterns of students in Comic-Animation major to understand the difference between individuals and to maximize one's merits which will improve the efficiency in education. Also through this research we could understand which aspects would be affected in both the satisfaction about the major based on Behaviour Patterns and the satisfaction of university life. According to the DISC Patterns, 41.7% of the students in Comic-Animation department shows that they were in Patterns I (Influence). And Patterns S (Steadiness) were 10% which was the lowest percentage in this survey. In the average of the subject's satisfaction aspect, the satisfaction of the professors' suggestion was 3.68 which was the highest. While the satisfaction of the administration service and welfare facility was 2.56 which was the lowest. The satisfaction rate based on DISC Behaviour Patterns shows a significant difference among the satisfaction of the department, the satisfaction of atmosphere in university and the satisfaction of the admin and welfare. Patterns I (Influence) was the highest the satisfaction in the major and the satisfaction of the university life while Patterns C(Criticalness) was the lowest. In particular, the importance of the I (Influence) is the most important factor, but it is essential that there is a slight decrease in the precision and accuracy of the work, and C(Criticalness) is shy and stressed, so they need to give positive communication and accurate advice. It is required to Comic-Animation department professor to analyse students' character based on Behaviour Patterns and a person's pros and cons for the career exploration and the employment consultation in order to have positive affect on employment rate. Also if the department's Behaviour Patterns construction were well utilized, it can improve the success rate of useful leadership and fellowship. it will improve the atmosphere in the department which will decrease the drop-out rate but increase the cohesion in the department which will lead to providing better result in the work and the project.

Use of ChatGPT in college mathematics education (대학수학교육에서의 챗GPT 활용과 사례)

  • Sang-Gu Lee;Doyoung Park;Jae Yoon Lee;Dong Sun Lim;Jae Hwa Lee
    • The Mathematical Education
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    • v.63 no.2
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    • pp.123-138
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    • 2024
  • This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.