Research on Educational Transformation and the Adaptability of Digital Pedagogy from the Perspective of Digital Natives
Kata Kunci:
cognitive adaptation, blended learning, digital natives, digital pedagogy, educational transformationAbstrak
Against the backdrop of digital technologies profoundly reshaping society, the unique cognitive characteristics of digital natives pose challenges to traditional educational models. This study, grounded in constructivist learning theory and the Technology Enhanced Learning (TEL) framework, systematically analyzes the cognitive traits of digital natives in areas such as fragmented information acquisition, visual learning preferences, and collaborative knowledge construction. Through case studies and empirical analysis, it proposes that digital pedagogy must adapt through four dimensions: integrating fragmented instructional content, designing multimodal interactions, implementing AI-adaptive learning pathways, and creating blended virtual-physical teaching environments. Findings confirm that adapted digital pedagogy enhances digital natives' learning engagement and knowledge internalization efficiency, providing theoretical foundations and practical pathways for educational digital transformation.
Referensi
Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6.
Brown, J. S. (2000). Growing up digital: How the web changes work, education, and the ways people learn. The Magazine of Higher Learning, 32(2), 10–20.
Ke, Z., & Huang, Y. (2009). Images better than text? N generations of students and cognitive development. Journal of Education Research, 193, 15–23.
Bennett, S., Maton, K., & Kervin, L. (2008). The ‘digital natives’ debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786.
Zhao, Y. (2014). Digital insight: A preliminary exploration based on the concepts of digital natives and digital immigrants. Chinese Journal of Library Science, 40(6), 43–54.
Hui, L., Wang, J., & Li, D. (2024). Research dynamics and trends on digital natives domestically and internationally based on CiteSpace. Journal of Hangzhou Dianzi University, 20(4), 71–78.
Huang, R., Liu, D., Liu, X., et al. (2023). Digital pedagogy: Conceptual framework and implementation pathways. Research on Modern Distance Education, 35(1), 1–14.
Bonk, C. J., Graham, C. R., Cross, J., et al. (2009). The handbook of blended learning: Global perspectives, local designs. Turkish Online Journal of Distance Education, 10(4), 181–181.
Allen, I. E., & Seaman, J. (2003). Sizing the opportunity: The quality and extent of online education in the United States, 2002 and 2003. Sloan Consortium Report, 659–673.
Wang, Y., & Zheng, Y. (2023). Real-world challenges, implication reconstruction, and model construction of personalized learning in the intelligent era. Research on Educational Technology, 44(3), 28–35.
Hu, H., & Dong, Y. (2017). Technology facilitating deep learning: Theoretical construction and empirical research on “personalized-collaborative” learning. Journal of Distance Education, 35(3), 48–61.
He, K. (1997). Constructivist teaching models, methods, and instructional design. Journal of Beijing Normal University (Social Sciences Edition), (5), 74–81.
Liu, S. (2000). A new model for human information acquisition and processing in the network era: The two-level three-cycle processing approach. Chinese Journal of Educational Technology, (4), 11–13.
Kennedy, G., Judd, T. S., Churchward, A., Gray, K., & Krause, K. (2008). First-year students’ experiences with technology: Are they really digital natives? Australasian Journal of Educational Technology, 24(1), 108–122.
Kennedy, G., Judd, T., Dalgarno, B., et al. (2010). Beyond natives and immigrants: Exploring types of net generation students. Journal of Computer Assisted Learning, 26(5), 332–343.
Helsper, E. J., & Eynon, R. (2010). Digital natives: Where is the evidence? British Educational Research Journal, 36(3), 503–520.
Liu, S. N. Y., & Hao, X. H. (2024). Challenges and approaches for generative AI in educational innovation. Tsinghua University Journal of Education, 45(3), 1–12.
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2026 International Conference on Fundamental and Applied Research (I-CFAR)
Artikel ini berlisensiCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
