Author(s)

Zheng Gao ^1,2, Li Wan ²

Affiliation(s)

¹ Dongguan City University, Dongguan, Guangdong, 523109, China
² Nanchang Normal College of Applied Technology, Nanchang, Jiangxi, 330100, China

Corresponding Author

Zheng Gao

ABSTRACT

Online classrooms require massive intelligent learning resources and big data support, and micro course resources in universities are also one of the digital resources. As one of the digital resources in universities, the educational resources in online classrooms have the characteristics of numerous subjects, single forms, large quantities, and uneven quality, making it difficult to fully support the needs of intelligent learning. Its characteristics include openness, sharing, intelligence, interactivity, collaboration, and ubiquitous availability, which require rapid and in-depth development and improvement to become intelligent resources. Based on the "Internet plus" model, this paper discusses the core elements of intelligent teaching under the "Internet plus" model, and studies and designs them. This realizes the overall framework of the online teaching "smart classroom" support platform, and divides the functions of each subsystem. This article provides specific solutions from the technical implementation level. This article has certain reference significance for the development and improvement of intelligent teaching. The data analysis results of the questionnaire survey indicate that the average scores of student performance, student participation, student satisfaction, knowledge mastery, learning enthusiasm, and teaching efficiency in the experimental group are 72.17, 73.4, 73.03, 79.23, 78.11, and 78.03, which are 11.99, 7.86, 10.06, 9.57, 17.25, and 8.73 higher than those in the control group.

KEYWORDS

Smart Education, Micro Course Design, Online Education, Artificial Intelligence

CITE THIS PAPER

Zheng Gao, Li Wan, Micro Course Design and Online Education Strategies of Information Fusion Technology in Smart Education Environment. Advances in Educational Technology and Psychology (2024) Vol. 8: 95-103. DOI: http://dx.doi.org/10.23977/aetp.2024.080214.

REFERENCES

[1] Akgun S, Greenhow C. Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2022, 2(3): 431-440.
[2] Chen X, Zou D, Xie H. Two decades of artificial intelligence in education. Educational Technology & Society, 2022, 25(1): 28-47.
[3] Lazarus M D, Truong M, Douglas P. Artificial intelligence and clinical anatomical education: Promises and perils. Anatomical Sciences Education, 2024, 17(2): 249-262.
[4] Ouyang F, Zheng L, Jiao P. Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 2022, 27(6): 7893-7925.
[5] Nemorin S, Vlachidis A, Ayerakwa H M. AI hyped? A horizon scan of discourse on artificial intelligence in education (AIED) and development. Learning, Media and Technology, 2023, 48(1): 38-51.
[6] Schiff D. Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 2022, 32(3): 527-563.
[7] Liang J C, Hwang G J, Chen M R A. Roles and research foci of artificial intelligence in language education: an integrated bibliographic analysis and systematic review approach. Interactive Learning Environments, 2023, 31(7): 4270-4296.
[8] Chaudhry M A, Kazim E. Artificial Intelligence in Education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 2022, 2(1): 157-165.
[9] Vartiainen H, Tedre M. Using artificial intelligence in craft education: crafting with text-to-image generative models. Digital Creativity, 2023, 34(1): 1-21.
[10] Holmes W, Tuomi I. State of the art and practice in AI in education. European Journal of Education, 2022, 57(4): 542-570.
[11] Skavronskaya L, Hadinejad A, Cotterell D. Reversing the threat of artificial intelligence to opportunity: a discussion of ChatGPT in tourism education. Journal of Teaching in Travel & Tourism, 2023, 23(2): 253-258.
[12] Bozkurt A, Junhong X, Lambert S. Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 2023, 18(1): 53-130.
[13] Yau K W, Chai C S, Chiu T K F. A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 2023, 28(1): 1041-1064.
[14] Shamir-Inbal T, Blau I. Micro-learning in designing professional development for ICT teacher leaders: The role of self-regulation and perceived learning. Professional Development in Education, 2022, 48(5): 734-750.
[15] Khong H K, Kabilan M K. A theoretical model of micro-learning for second language instruction. Computer Assisted Language Learning, 2022, 35(7): 1483-1506.
[16] Pham N K T. Vietnamese students’ perspectives on online micro-teaching (OMT) as a technique in English teacher education in the 4.0 era. AsiaCALL Online Journal, 2022, 13(1): 40-72.
[17] Lu S Y, Lo C C, Syu J Y. Project-based learning oriented STEAM: The case of micro–bit paper-cutting lamp. International Journal of Technology and Design Education, 2022, 32(5): 2553-2575.
[18] Tapalova O, Zhiyenbayeva N. Artificial intelligence in education: AIEd for personalised learning pathways. Electronic Journal of e-Learning, 2022, 20(5): 639-653.
[19] Limna P, Jakwatanatham S, Siripipattanakul S. A review of artificial intelligence (AI) in education during the digital era. Advance Knowledge for Executives, 2022, 1(1): 1-9.
[20] Baidoo-Anu D, Ansah L O. Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 2023, 7(1): 52-62.

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