International Journal of New Developments in Education, 2024, 6(2); doi: 10.25236/IJNDE.2024.060223.
Wen Yang1, Lutong Wang2, Feng Lin3, Xin Wen3, Ya Wang4, Jiamin Li5
1Hechi Senior High School, Chemistry Teaching and Research Section, Hechi, China
2Institute of Education, Guangxi Modern Polytechnic College, Hechi, China
3College of Accounting and Auditing, Guangxi University of Finance and Economics, Nanning, China
4School of Fine Arts and Art Design, Qiqihar University, Qiqihar, China
5School of Education, Guizhou Normal University, Guiyang, China
This study aims to construct an ecological model of high school chemistry online courses through the use of large-scale language models, creating intelligent high school chemistry online courses primarily based on artificial intelligence. It seeks to interpret an intelligent question-and-answer teaching model based on natural language and to reshape the knowledge structure of high school chemistry through a human-machine interaction model. The research employs the scientometric software CiteSpace to visually analyze the co-occurrence of keywords in online courses and gradually explores the research hotspots and development trends in high school chemistry online courses.and research frontiers of high school chemistry online courses. The results show that large-scale language model technology has unique advantages in explaining chemical knowledge, experimental demonstration, and online course creation; organic chemistry, online courses, online teaching, and blended teaching become high school chemistry research trends. It is inferred that the high school chemistry online course based on large-scale language models gradually evolves into a new normal in chemical education research.
Large language model, High school chemistry, Online course, Citespace, Visualization
Wen Yang, Lutong Wang, Feng Lin, Xin Wen, Ya Wang, Jiamin Li. Research on Visualization of High School Chemistry Online Courses Based on Large Language Models. International Journal of New Developments in Education (2024), Vol. 6, Issue 2: 140-145. https://doi.org/10.25236/IJNDE.2024.060223.
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