Effect of Smart Classroom Learning Modes and Strategies on Student’s Academic Capability at Primary Education

Jinjin Bian; Qiudi Wu; Huayang Zhang

doi:10.62177/jetp.v2i4.768

Authors

Jinjin Bian Shenzhen Polytechnic University
Qiudi Wu Shenzhen Polytechnic University
Huayang Zhang Shenzhen Polytechnic University

DOI:

https://doi.org/10.62177/jetp.v2i4.768

Keywords:

Informationization, Smart Classroom, Learning Modes, Learning Strategies

Abstract

The rapid advancement of technology promotes the development of modern education technology while catalyzing transformation and innovation in teaching. A smart classroom with effective learning modes and strategies enables students’ academic growth, whereas the physical environment of a smart classroom alone can only have limited effect on students’ academic growth. Conducting research on smart classroom learning modes and strategies holds both theoretical significance and practical value for promoting students’ academic achievement. The objective of this study is to determine the effect of smart classrooms learning modes and strategies among primary school students. The study involved 36 students, and the data were analyzed using test. The results show a significant difference in the students’ academic performance between the conventional learning modes and strategies and smart classroom learning modes and strategies. In addition, the use of smart classroom learning modes and strategies has greatly improved students’ performance in several areas: personalized learning capacity, autonomous inquiry, knowledge construction, collaborative interaction, innovative utilization of information resources, and self-assessment capabilities.

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References

Kwet, M., & Prinsloo, P. (2020). The ‘smart’ classroom: A new frontier in the age of the smart university. Teaching in Higher Education, 25(4), 510–526.

Saini, M. K., & Goel, N. (2019). How smart are smart classrooms? A review of smart classroom technologies. ACM Computing Surveys (CSUR), 52(6), 1–28.

Lu, K., Yang, H. H., Shi, Y., & Wang, X. (2021). Examining the key influencing factors on college students’ higher-order thinking skills in the smart classroom environment. International Journal of Educational Technology in Higher Education, 18, 1–13.

Mircea, M., Stoica, M., & Ghilic-Micu, B. (2021). Investigating the impact of the internet of things in higher education environment. IEEE Access, 9, 33396–33409.

Zhang, Q. (2022). Construction of Personalized Learning Platform Based on Collaborative Filtering Algorithm. Wireless Communications and Mobile Computing, 2022, 1–9.

Alam, A. (2022). Employing Adaptive Learning and Intelligent Tutoring Robots for Virtual Classrooms and Smart Campuses: Reforming Education in the Age of Artificial Intelligence. In Advanced Computing and Intelligent Technologies (pp. 395–406). Springer Nature Singapore.

Aguilar, J., Sánchez, M., Cordero, J., Valdiviezo-Díaz, P., et al. (2018). Learning analytics tasks as services in smart classrooms. Universal Access in the Information Society, 17(4), 693–709.

Liu, Q. X., & Yang, Z. G. (2021). The construction of English smart classrooms and the innovation of teaching mode under the background of Internet of Things multimedia communication. Mobile Information Systems, 2021, 6398067.

Hu, X. Y. (2023). The role of deep learning in the innovation of smart classroom teaching mode under the background of internet of things and fuzzy control. Heliyon, 9(8), e18594.

Albalawi, R. (2013). Evaluating Tangible User Interface-based Mobile learning [Thesis]. University of Ottawa.

Slotta, J. D. (2007). Supporting collaborative inquiry: New architectures, new opportunities. Paper presented at the annual Computer Supported Collaborative Learning (CSCL) conference, Rutgers, NJ.

Benkiran, M. A., & Ajhoun, R. (2002). An adaptive and cooperative telelearning system: SMART-learning. International Journal on E-Learning, 1(2), 66.

Christensen, C. M., Johnson, C. W., & Horn, M. B. (2008). Disrupting class: How disruptive innovation will change the way the world learns. McGraw-Hill.

Maine Government. (2024). About MLTI. http://www.maine.gov/doe/Learning/LTT/MLTI/About

Zhu, Z., & He, B. (2012). A New Realm of Educational Informationization. Research on Audiovisual Education, 12(12), 5–13.

Lee, M. S., & Son, Y. E. (2012). A study on the adoption of SNS for smart learning in the “creative activity”. International Journal of Education and Learning, 2(3), 1–18.

Yang, K. (2010). Learning-Centered Educational Design Theory. Electronic Industry Press.

Weinstein, C. E. (1990). Learning and Study Strategies Inventory - High School Version. Clearwater, FL: H & H Publishing Company, Inc.

Pokay, P., & Blumendfeldt, P. C. (1990). Predicting achievement early and late in the semester: The role of motivation and learning strategies. Journal of Educational Psychology, 82(1), 41–50.

McKeachie, W. J., et al. (1990). Teaching and Learning in the College Classroom: A Review of the Research Literature. University of Michigan.

Ngendahayo, E., Habarurema, J. B., Limone, P., & Zhang, W. (2023). Modelling STEM learners’ academic performance in advanced level secondary schools with smart classrooms in Rwanda. Education and Information Technologies, 1–23.

Shen, H., & Chen, X. (2022). Virtual reality-based internet+ smart classroom. Journal of Internet Technology, 23(2), 335–344.

Yu, H., Shi, G., Li, J., & Yang, J. (2022). Analyzing the differences of interaction and engagement in a smart classroom and a traditional classroom. Sustainability, 14(13), 8184.

Li, L., Chen, C. P., Wang, L., Liang, K., & Bao, W. (2023). Exploring Artificial Intelligence in Smart Education: Real-Time Classroom Behavior Analysis with Embedded Devices. Sustainability, 15(10), 7940.

Lei, G. (2022). An Index System for Learning Assessment in Higher Education: Case Study of the Sichuan University of Arts and Sciences. Mobile Information Systems, 2022, 1–8.

Cheng, C. C., & Yang, Y. T. C. (2023). Impact of smart classrooms combined with student-centered pedagogies on rural students’ learning outcomes: Pedagogy and duration as moderator variables. Computers & Education, 207, 104911.

Yang, J., Yu, H., Gong, C., & Chen, N. S. (2016). Students’ perceptions and behaviour in technology-rich classroom and multi-media classroom. Eurasia Journal of Mathematics, Science and Technology Education, 13(3), 621–647.

Nguyen, L. T., Kanjug, I., Lowatcharin, G., Manakul, T., Poonpon, K., Sarakorn, W., et al. (2022). How teachers manage their classroom in the digital learning environment–experiences from the University Smart Learning Project. Heliyon, 8(10), e12067.

Zhang, X., Sun, J., & Deng, Y. (2023). Design and Application of Intelligent Classroom for English Language and Literature Based on Artificial Intelligence Technology. Applied Artificial Intelligence, 37(1), 2216051.