• The Mathematical Education
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• v.63 no.2
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• pp.187-207
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• 2024

In this study, we explored the feasibility of automatically scoring descriptive assessment items using GPT-4 based ChatGPT by comparing and analyzing the scoring results between teachers and GPT-4 based ChatGPT. For this purpose, three descriptive items from the permutation and combination unit for first-year high school students were selected from the KICE (Korea Institute for Curriculum and Evaluation) website. Items 1 and 2 had only one problem-solving strategy, while Item 3 had more than two strategies. Two teachers, each with over eight years of educational experience, graded answers from 204 students and compared these with the results from GPT-4 based ChatGPT. Various techniques such as Few-Shot-CoT, SC, structured, and Iteratively prompts were utilized to construct prompts for scoring, which were then inputted into GPT-4 based ChatGPT for scoring. The scoring results for Items 1 and 2 showed a strong correlation between the teachers' and GPT-4's scoring. For Item 3, which involved multiple problem-solving strategies, the student answers were first classified according to their strategies using prompts inputted into GPT-4 based ChatGPT. Following this classification, scoring prompts tailored to each type were applied and inputted into GPT-4 based ChatGPT for scoring, and these results also showed a strong correlation with the teachers' scoring. Through this, the potential for GPT-4 models utilizing prompt engineering to assist in teachers' scoring was confirmed, and the limitations of this study and directions for future research were presented.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.349-377
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• 2023

With the recent advancements in artificial intelligence, the emergence of ChatGPT is expected to bring significant changes to various industries. In particular, there are active attempts to introduce ChatGPT in the education sector, and for librarians, utilizing ChatGPT is seen as an essential element for future learning tools. Against this background, this study aimed to examine librarians' perceptions of introducing ChatGPT in the school library through Focus Group Interviews (FGI). As a result, six themes were derived, including differences in perceptions of ChatGPT application in school libraries, teaching and learning activities utilizing ChatGPT, practical operation of ChatGPT, considerations for successful performance, librarians' required competencies and environment (infrastructure), and the development direction of ChatGPT utilization services in school libraries. Based on these findings, implications for the necessity of educational services utilizing ChatGPT were proposed. This study is significant as the first attempt to introduce ChatGPT in the school library field.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.139-151
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• 2023

This study aims to gain insights into ChatGPT, which has recently received significant attention. The study utilized a mixed method involving case studies and news big data analysis. ChatGPT can be described as an optimized language model for dialogue. The question arises whether ChatGPT will replace Google search services, posing a potential threat to Google. It could hurt Google's advertising business, which is the foundation of its profits. With AI-based chatbots like ChatGPT likely to disrupt the web search industry, Google is establishing a new AI strategy. The study used the BIG KINDS service and analyzed 2,136 articles over six months, from August 23, 2022, to February 22, 2023. Thirty of these articles were written in 2022, while 2,106 have been reported recently as of February 22, 2023. Also, the study examined the contents of ChatGPT by utilizing literature research, news big data analysis, and use cases. Despite limitations such as the potential for false information, analyzing news big data and use cases suggests that ChatGPT is worth using.

• Environmental Analysis Health and Toxicology
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• v.17 no.3
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• pp.239-243
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• 2002

Changes of plasma vitellogenin (VTG) and glutamate pyruvate transaminase (GPT) were examined for determining whether hepatocyte was damaged during the process of VTG induction in the juvenile rockfish, Sebastes schlegeli exposed to exogenous estrogen (estradiol-l7$\beta$, E$_2$). Rockfishes were intraperitoneally injected with E$_2$(5 mg/kg B.W.) in 70% ethanol and plasma sampling were extracted at 0, 1, 3, 6, 9, 12, 15 days af-ter E$_2$administration. VTG and GPT were then analyzed by SDS -PAGE and Reitman -Frankel method, respectively. VTG band was detected at a molecular weight position of 175 kDa on Day 3 after E$_2$administration. This band became more distinct at 6 days, but its was gradually thinned with time -course, and not detected at 15 days. GPT was suddenly increased at 1 days after 22 administration and highest GPT was detected at 3 days. However. GPT was gradually decreased with time -course as the change of VTG. These results suggest that the process of VTG induction by exogenous E$_2$damage to hepatocyte, and plasma GPT was temporarily increased in the juvenile rockfish.

• Journal of Korean Elementary Science Education
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• v.43 no.2
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• pp.322-336
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• 2024

This study explored the educational effects of using ChatGPT in science lessons for elementary school students. The participants included 25 sixth-grade students studying at an elementary school in Metropolitan City D. This study examined the impacts of elementary science lessons on the cognitive development of elementary school students and their perceptions of using ChatGPT in their science classes. We found that science lessons that used ChatGPT aided the cognitive development of the participating elementary students. These students responded positively to the classes using ChatGPT. The results were then divided into those who perceived ChatGPT positively, those who perceived it negatively, and those who recognized both positive and negative aspects. Students who perceived it negatively mainly remained at the memorization level, and those who recognized both positive and negative aspects posed higher-level questions to ChatGPT.

• Journal of fish pathology
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• v.17 no.3
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• pp.191-198
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• 2004

Temporal changes of plasma vitellogenin (VTG), alkaline-labile protein phosphorus (ALPP), calcium (Ca), glutamate pyruvate transaminase (GPT) and hepatosomatic index (HSI) were examined in the $estradiol-17\beta$ ${E_2}$-administered immature rockfish, Sebastes schlegeli. Fish were intraperitoneally injected with ${E_2}$ (5 ㎎/kg B.W.) in 70% ethanol and then plasma were extracted at 0, 1, 3, 6, 9, 12 and 15 days. VTG band was detected at a molecular weight position of about 170 kDa on Day 3 in SDS-PAGE. This band became more distinct at 6 days but its was gradually thinned with time-course, and not detected at 15 days. Plasma ALPP and Ca increased suddenly at 1 day and the highest concentrations were detected at 6 days and then these concentrations decreased gradually with time-course. ALPP and Ca concentrations at 15 days after E2 administration were very similar to that before E2 administration. GPT was increased at 1 day and higher GPT was detected at 3 days. However, GPT was gradually decreased with time-course. GPT and HSI at 15 days after E2 administration were also very similar to that before E2 administration. HSI was also increased at 1 day and the highest value was detected at 3 days and then gradually decreased with time-course. These results suggest that plasma ALPP, Ca, GPT and HSI could be utilized as a biomarker of exogenous E2 exposure in coastal ecosystem, because the changes of ALPP, Ca, GPT and HSI after E2 administration are very similar to that of VTG.

• Education of Primary School Mathematics
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• v.26 no.2
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• pp.99-113
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• 2023

In this study, I explored the possibility of using ChatGPT math education. For this purpose, students' problem-solving outputs and conversation data between pre-service teachers and a student were selected as an analysis case. A case was analyzed using ChatGPT and compared with the results of mathematics education experts. The results that ChatGPT analyzed students' problem-solving strategies and mathematical thinking skills were similar to those of math education experts. ChatGPT was able to analyze teacher questions with evaluation criteria, and the results were similar to those of math education experts. ChatGPT could also respond with mathematical theory as a source of evaluation criteria. These results demonstrate the potential of ChatGPT to analyze students' thinking and teachers' practice in mathematics education. However, there are limitations in properly applying the evaluation criteria or providing inaccurate information, so the further review of the derived information is required.

• The Mathematical Education
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• v.63 no.2
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• pp.139-163
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• 2024

The purpose of this study is to examine the capabilities of ChatGPT as a tool for supporting students in generating mathematical arguments that can be considered proofs. To examine this, we engaged students enrolled in a mathematics pathways course in evaluating and revising their original arguments using ChatGPT feedback. Students attempted to find and prove a method for the area of a triangle given its side lengths. Instead of directly asking students to prove a formula, we asked them to explore a method to find the area of a triangle given the lengths of its sides and justify why their methods work. Students completed these ChatGPT-embedded proving activities as class homework. To investigate the capabilities of ChatGPT as a proof tutor, we used these student homework responses as data for this study. We analyzed and compared original and revised arguments students constructed with and without ChatGPT assistance. We also analyzed student-written responses about their perspectives on mathematical proof and proving and their thoughts on using ChatGPT as a proof assistant. Our analysis shows that our participants' approaches to constructing, evaluating, and revising their arguments aligned with their perspectives on proof and proving. They saw ChatGPT's evaluations of their arguments as similar to how they usually evaluate arguments of themselves and others. Mostly, they agreed with ChatGPT's suggestions to make their original arguments more proof-like. They, therefore, revised their original arguments following ChatGPT's suggestions, focusing on improving clarity, providing additional justifications, and showing the generality of their arguments. Further investigation is needed to explore how ChatGPT can be effectively used as a tool in teaching and learning mathematical proof and proof-writing.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.233-256
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• 2023

This study conducted foundational research to derive ways to use ChatGPT in mathematics education by analyzing ChatGPT's responses to questions from the National Assessment of Educational Achievement (NAEA) and the College Scholastic Ability Test (CSAT). ChatGPT, a generative artificial intelligence model, has gained attention in various fields, and there is a growing demand for its use in education as the number of users rapidly increases. To the best of our knowledge, there are very few reported cases of educational studies utilizing ChatGPT. In this study, we analyzed ChatGPT 3.5 responses to questions from the three-year National Assessment of Educational Achievement and the College Scholastic Ability Test, categorizing them based on the percentage of correct answers, the accuracy of the solution process, and types of errors. The correct answer rates for ChatGPT in the National Assessment of Educational Achievement and the College Scholastic Ability Test questions were 37.1% and 15.97%, respectively. The accuracy of ChatGPT's solution process was calculated as 3.44 for the National Assessment of Educational Achievement and 2.49 for the College Scholastic Ability Test. Errors in solving math problems with ChatGPT were classified into procedural and functional errors. Procedural errors referred to mistakes in connecting expressions to the next step or in calculations, while functional errors were related to how ChatGPT recognized, judged, and outputted text. This analysis suggests that relying solely on the percentage of correct answers should not be the criterion for assessing ChatGPT's mathematical performance, but rather a combination of the accuracy of the solution process and types of errors should be considered.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.79-92
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• 2024

ChatGPT, as a representative chatbot leveraging generative artificial intelligence technology, is used valuable not only in scientific and technological domains but also across diverse sectors such as society, economy, industry, and culture. This study conducts an explorative analysis of user sentiments and needs for ChatGPT by examining global social media discourse on Reddit. We collected 10,796 comments on Reddit from December 2022 to August 2023 and then employed keyword analysis, sentiment analysis, and need-mining-based topic modeling to derive insights. The analysis reveals several key findings. The most frequently mentioned term in ChatGPT-related comments is "time," indicative of users' emphasis on prompt responses, time efficiency, and enhanced productivity. Users express sentiments of trust and anticipation in ChatGPT, yet simultaneously articulate concerns and frustrations regarding its societal impact, including fears and anger. In addition, the topic modeling analysis identifies 14 topics, shedding light on potential user needs. Notably, users exhibit a keen interest in the educational applications of ChatGPT and its societal implications. Moreover, our investigation uncovers various user-driven topics related to ChatGPT, encompassing language models, jobs, information retrieval, healthcare applications, services, gaming, regulations, energy, and ethical concerns. In conclusion, this analysis provides insights into user perspectives, emphasizing the significance of understanding and addressing user needs. The identified application directions offer valuable guidance for enhancing existing products and services or planning the development of new service platforms.