A Study on the Efficiency Enhancement of Self-Directed Learning and Online Lecture Using Emotional Factor Control
Keywords:
Emotion control, Self-directed learning, Education, Online education
Abstract
The 4th industrial revolution, AI, and ChatGPT have been advancing up as key topics in industrial areas and educational systems. This paper deals with the effective teaching method for the effective nurturing of manpower including the ChatGPT. ChatGPT and AI are highly impacting on educational systems as well as many industrial areas because ChatGPT can be easily used by everyone to ask questions and get responses about any field. However, online teaching cannot catch up their teaching results because they cannot see directly. Therefore, they have to develop on how they can see the results of their lecture.
This paper considers methods to see the results using emotional factors. During online lecture, when students have a satisfaction with lecturer’s lecture results, students will express happiness, enjoyment, sadness, fear, anger, disgust, surprise, and embarrassment depending on their satisfaction level. Basically, whenever they have emotional feeling, they can show their faces status such as happiness, enjoyment, sadness, fear, anger, disgust, surprise, and embarrassment.
This paper suggests the method that lecture can adjust or control lecture style through emotional factor measurement and expression.
References
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K-12 schools can use it to improve student engagement online. https://www.thetechedvocate.org/basic-insurance-online-training-courses/
K-12 Standards (2017). Computer Science Teachers Association, http://www.csteachers.org/standards.
Kalla, D. et al. (2023). Study and Analysis of Chat GPT and its Impact on Different Fields of Study. International Journal of Innovative Science and Research Technology, 8(3).
Karandish, D. (2021). 7 benefits of AI in education. The journal. https://thejournal.com/Articles/2021/06/23/7-Benefits-of-AI-in-Education.aspx?p=1
Kaur, B., Singh, D., & Roy, P. P. (2018). EEG based emotion classification mechanism in BCI. Procedia Computer Science, 132, 752-758.
Kim, D. H. & Shakya, R. (2023). A Study on the Curriculum Design for K-12 AI Education Using Knowledge Graph, submitted, Sept, 2023.
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Kim, D. H. (2022). How to teach and Learn AI. OutskirtPress.
Kim, D. H. (2023). A Study on the Job Replacement Impact of ChatGPT and Education Method. European Journal of Science, Innovation and Technology, 3(4), 105-122.
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Roose, K. (2923). Donʼt Ban ChatGPT in Schools. Teach With It. https://www.nytimes.com/2023/01/12/technology/chatgpt-schools-teachers.html
Shafait, Z., Khan, M. A., Bilan, Y., & Oláh, J. (2021). Modeling the mediating roles of self-directed learning and knowledge management processes between emotional intelligence and learning outcomes in higher education. PloS one, 16(7), e0255177. https://doi.org/10.1371/journal.pone.0255177
Shafait, Z., Yuming, Z., Meyer, N., & Sroka, W. (2021). Emotional intelligence, knowledge management processes and creative performance: modelling the mediating role of self-directed learning in higher education. Sustainability, 13(5), 2933. https://doi.org/10.3390/su13052933
Sommer, T., Gläscher, J., Moritz, S., & Büchel, C. (2008). Emotional enhancement effect of memory: Removing the influence of cognitive factors. Learning & Memory, 15(8), 569-573.
Steinbauer, G., Kandlhofer, M., Chklovski, T., Heintz, F., & Koenig, S. (2021). A differentiated discussion about AI education K-12. KI-Künstliche Intelligenz, 35(2), 131-137. https://doi.org/10.1007/s13218-021-00724-8
Tate, A. S. (2023). How will AI like ChatGPT change education for our children, https://www.parents.com/how-will-ai-technology-change-education-7100688
Touretzky, D. et al. (2019). A year in K-12 AI education. Association for the advancement of AI (AI magazine, Winter), 88-90.
UNESCO (2021). AI and education. https://creativecommons.org/licenses/by-sa/3.0/igo/
UNICEF (2021). Policy guidance on AI for children. https://www.unicef.org/globalinsight/media/2356/file/UNICEF-Global-Insight-policy-guidance-AI-children-2.0-2021.pdf
University of Toronto (AI). https://www.engineering.utoronto.ca/research-innovation/industry-partnerships-with-u-of-t-engineering/data-analytics-artificial-intelligence/
Van Mechelen, M. (2022). Emerging Technologies in K-12 Education: A Future HCI Research Agenda. ACM Transactions on Computer-Human Interaction, 1-42. https://www.researchgate.net/publication/363044441
Wang, X. W., Nie, D., & Lu, B. L. (2014). Emotional state classification from EEG data using machine learning approach. Neurocomputing, 129, 94-106. http://dx.doi.org/10.1016/j.neucom.2013.06.046
Webb, M. et al. (2017). Computer science in K-12 school curricula of the 2lst century: Why, what and when? Educ Inf Technol, 22, 445-468. https://doi.org/10.1007/s10639-016-9493-x
Why Choose to Include Artificial Intelligence Course in K-12 Curriculum. https://knowledge-hub.com/2020/01/24/the-benefits-of-incorporating-artificial-intelligence-in-k-12-education/
Wu, C. et al. (2021), Web-based Platform for K-12 AI Education in China. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 15687-15694.
Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, 3, 100061.
Zhang, Y. (2018). A Study on the Effects of Emotional Factors on Middle School Students in English Learning. Advances in Social Science, Education and Humanities Research, 89.
Zhou, Y. (2022). Analysis of the Transformation of China's K12 Education Model under the New Trend. Journal of Education, Humanities and Social Sciences, 5, 362-369
Bellas, F. et al. (2022). AI curriculum for European high schools: An Embedded intelligence approach. IJAAI in Education, 8, 1-31. https://doi.org/10.1007/s40593-022-00315-0
Bold (2023). https://bold.expert/technology/?filter-category%5B%5D=education-technology-technology&gclid=Cj0KCQjww4 hBhCtARIsAC9gR3aJCWHu0LzYNBGqGoZ6A1lb6Lb2y-6f—lhdiBSV1UJeaon3ID_bcIaAnj9EALw_wcB
ChatGPT (Partha Pratim Ray, March 2023). A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope, Internet of Things and Cyber-Physical Systems.
Code school. https://www.codeschool.fi
Digital promise (2023). https://digitalpromise.org/initiative/computational-thinking/computational-thinking-for-next-generation-science/what-is-computational-thinking/
How K-12 Data Analytics and AI can support equitable learning. https://www.powerschool.com/blog/how-data-analytics-and-ai-support-equitable-learning/
Jiahong Su et al. (2022). A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100065
K-12 AI curricula (2022). ED-2022/FLI-ICT/K-12
K-12 schools can use it to improve student engagement online. https://www.thetechedvocate.org/basic-insurance-online-training-courses/
K-12 Standards (2017). Computer Science Teachers Association, http://www.csteachers.org/standards.
Kalla, D. et al. (2023). Study and Analysis of Chat GPT and its Impact on Different Fields of Study. International Journal of Innovative Science and Research Technology, 8(3).
Karandish, D. (2021). 7 benefits of AI in education. The journal. https://thejournal.com/Articles/2021/06/23/7-Benefits-of-AI-in-Education.aspx?p=1
Kaur, B., Singh, D., & Roy, P. P. (2018). EEG based emotion classification mechanism in BCI. Procedia Computer Science, 132, 752-758.
Kim, D. H. & Shakya, R. (2023). A Study on the Curriculum Design for K-12 AI Education Using Knowledge Graph, submitted, Sept, 2023.
Kim, D. H. (2019). Visegrad group 4th wave. LAMBERT.
Kim, D. H. (2022). How to teach and Learn AI. OutskirtPress.
Kim, D. H. (2023). A Study on the Job Replacement Impact of ChatGPT and Education Method. European Journal of Science, Innovation and Technology, 3(4), 105-122.
Kim, T. W. (2021). AI comparativeness in Country. ETRI report.
Kotra report (2023). Canada AI policy and Investment. https://dream.kotra.or.kr/kotranews/cms/news/actionKotraBoardDetail.do?SITE_NO=3&MENU_ID=180&CONTENTS_NO=1&bbsGbn=243&bbsSn=243&pNttSn=199778
Levesque, E. M. (2018). The role of AI in education and the changing US workforce. Brookings. https://www.brookings.edu
Lund, B. D. & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? https://doi.org/10.1108/LHTN-01-2023-0009
Lund, B. D. (2023). A Brief Review of ChatGPT: Its Value and the Underlying GPT Technology, University of North Texas. https://doi.org/10.13140/RG.2.2.28474.06087
Ministry of Education (2020). AI education in primary. Newspaper, Yonhap news.
Mitrović Veljković, S., Nešić, A., Dudić, B., Gregus, M., Delić, M., & Meško, M. (2020). Emotional intelligence of engineering students as basis for more successful learning process for industry 4.0. Mathematics, 8(8), 1321. https://doi.org/10.3390/math8081321
New, J. (2016). Building a Data-Driven Education System in the United States. Center for Data Innovation.
New, J. (2018). Why the United States Needs a National Artificial Intelligence Strategy and What It Should Look Like. Center for Data Innovation.
Nurismail, E. N., Kareri, D. G. R., Manafe, D. R. T., & Artawan, I. M. (2021). The relationship between emotional intelligence and self-directed learning readiness among students in the faculty of medicine. Jurnal Kajian Psikologi Pendidikan Dan Bimbingan Konseling, 7(1), 28-33.
Ogren, M., & Johnson, S. P. (2021). Factors facilitating early emotion understanding development: Contributions to individual differences. Human Development, 64(3), 108-118.
Okwuduba, E. N., Nwosu, K. C., Okigbo, E. C., Samuel, N. N., & Achugbu, C. (2021). Impact of intrapersonal and interpersonal emotional intelligence and self-directed learning on academic performance among pre-university science students. Heliyon, 7(3). https://doi.org/10.1016/j.heliyon.2021.e06611
Poth, R. D. (2022). Teaching AI to all students. https://www.gettingsmart.com/2022/05/30/teaching-ai-to-all-students/
Roose, K. (2923). Donʼt Ban ChatGPT in Schools. Teach With It. https://www.nytimes.com/2023/01/12/technology/chatgpt-schools-teachers.html
Shafait, Z., Khan, M. A., Bilan, Y., & Oláh, J. (2021). Modeling the mediating roles of self-directed learning and knowledge management processes between emotional intelligence and learning outcomes in higher education. PloS one, 16(7), e0255177. https://doi.org/10.1371/journal.pone.0255177
Shafait, Z., Yuming, Z., Meyer, N., & Sroka, W. (2021). Emotional intelligence, knowledge management processes and creative performance: modelling the mediating role of self-directed learning in higher education. Sustainability, 13(5), 2933. https://doi.org/10.3390/su13052933
Sommer, T., Gläscher, J., Moritz, S., & Büchel, C. (2008). Emotional enhancement effect of memory: Removing the influence of cognitive factors. Learning & Memory, 15(8), 569-573.
Steinbauer, G., Kandlhofer, M., Chklovski, T., Heintz, F., & Koenig, S. (2021). A differentiated discussion about AI education K-12. KI-Künstliche Intelligenz, 35(2), 131-137. https://doi.org/10.1007/s13218-021-00724-8
Tate, A. S. (2023). How will AI like ChatGPT change education for our children, https://www.parents.com/how-will-ai-technology-change-education-7100688
Touretzky, D. et al. (2019). A year in K-12 AI education. Association for the advancement of AI (AI magazine, Winter), 88-90.
UNESCO (2021). AI and education. https://creativecommons.org/licenses/by-sa/3.0/igo/
UNICEF (2021). Policy guidance on AI for children. https://www.unicef.org/globalinsight/media/2356/file/UNICEF-Global-Insight-policy-guidance-AI-children-2.0-2021.pdf
University of Toronto (AI). https://www.engineering.utoronto.ca/research-innovation/industry-partnerships-with-u-of-t-engineering/data-analytics-artificial-intelligence/
Van Mechelen, M. (2022). Emerging Technologies in K-12 Education: A Future HCI Research Agenda. ACM Transactions on Computer-Human Interaction, 1-42. https://www.researchgate.net/publication/363044441
Wang, X. W., Nie, D., & Lu, B. L. (2014). Emotional state classification from EEG data using machine learning approach. Neurocomputing, 129, 94-106. http://dx.doi.org/10.1016/j.neucom.2013.06.046
Webb, M. et al. (2017). Computer science in K-12 school curricula of the 2lst century: Why, what and when? Educ Inf Technol, 22, 445-468. https://doi.org/10.1007/s10639-016-9493-x
Why Choose to Include Artificial Intelligence Course in K-12 Curriculum. https://knowledge-hub.com/2020/01/24/the-benefits-of-incorporating-artificial-intelligence-in-k-12-education/
Wu, C. et al. (2021), Web-based Platform for K-12 AI Education in China. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 15687-15694.
Yang, W. (2022). Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation. Computers and Education: Artificial Intelligence, 3, 100061.
Zhang, Y. (2018). A Study on the Effects of Emotional Factors on Middle School Students in English Learning. Advances in Social Science, Education and Humanities Research, 89.
Zhou, Y. (2022). Analysis of the Transformation of China's K12 Education Model under the New Trend. Journal of Education, Humanities and Social Sciences, 5, 362-369
Published
2023-12-25
How to Cite
Kim, D. H. (2023). A Study on the Efficiency Enhancement of Self-Directed Learning and Online Lecture Using Emotional Factor Control. European Journal of Science, Innovation and Technology, 3(6), 294-304. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/338
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Copyright (c) 2023 Dong Hwa Kim
This work is licensed under a Creative Commons Attribution 4.0 International License.
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