Mechanisms and Limits of Digital Process Visualization in Brush-Calligraphy Copying in Primary and Secondary Schools

Authors

  • Sun Siyuan Quanzhou Normal University, Quanzhou

DOI:

https://doi.org/10.55927/eajmr.v5i9.321

Keywords:

Calligraphy Education, Brush-Calligraphy Copying, Process Visualization, Augmented Feedback, Formative Assessment

Abstract

Digital sensing and video recording preserve trajectory, velocity, pressure, and brush posture, making transient brush movements available for classroom review and comparison. Visibility alone does not establish motor competence. Through a problem-oriented narrative synthesis and conceptual analysis, this study compares six core empirical sources retrieved through August 8, 2026, by participants, writing tasks, process measures, feedback design, and retention or transfer evidence. The literature suggests that process visualization can support joint observation, problem localization, and feedback dialogue. Studies involving adults, other writing systems, or ordinary pen handwriting offer evidence about possible mechanisms but cannot establish overall effectiveness in school-based Chinese brush calligraphy. The proposed framework distinguishes process recording, diagnostic evidence, regulatory evidence, and learning evidence.

References

Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. https://doi.org/10.1080/0969595980050102

Bonneton-Botté, N., Fleury, S., Girard, N., Le Magadou, M., Cherbonnier, A., Renault, M., Anquetil, E., & Jamet, E. (2020). Can tablet apps support the learning of handwriting? An investigation of learning outcomes in kindergarten classroom. Computers & Education, 151, Article 103831. https://doi.org/10.1016/j.compedu.2020.103831

Danna, J., Fontaine, M., Paz-Villagrán, V., Gondre, C., Thoret, E., Aramaki, M., Kronland-Martinet, R., Ystad, S., & Velay, J.-L. (2015). The effect of real-time auditory feedback on learning new characters. Human Movement Science, 43, 216–228. https://doi.org/10.1016/j.humov.2014.12.002

General Office of the Ministry of Education. (2024, September 30). Notice on further strengthening standardized Chinese character writing education in primary and secondary schools.

Gerth, S., Klassert, A., Dolk, T., Fliesser, M., Fischer, M. H., Nottbusch, G., & Festman, J. (2016). Is handwriting performance affected by the writing surface? Comparing preschoolers', second graders', and adults' writing performance on a tablet vs. paper. Frontiers in Psychology, 7, Article 1308. https://doi.org/10.3389/fpsyg.2016.01308

Gong, X., Tao, W., & Ma, Y. (2025). CalliSense: An interactive educational tool for process-based learning in Chinese calligraphy. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (pp. 1–20). Association for Computing Machinery. https://doi.org/10.1145/3706598.3714176

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487

Huang, X., & Qiao, C. (2024). The effects and learners’ perceptions of cluster analysis-based peer assessment for Chinese calligraphy classes. SAGE Open, 14(2), Article 21582440241255846. https://doi.org/10.1177/21582440241255846

Jimenez-Diaz, J., Chaves-Castro, K., & Morera-Castro, M. (2021). Effect of self-controlled and regulated feedback on motor skill performance and learning: A meta-analytic study. Journal of Motor Behavior, 53(3), 385–398. https://doi.org/10.1080/00222895.2020.1782825

Jin, M., & Cai, L. (2023). Why technology has not profoundly influenced education: A response based on a historical investigation of teachers' embodied technology [In Chinese]. E-education Research, 44(4), 117–123. https://doi.org/10.13811/j.cnki.eer.2023.04.016

Limbu, B. H., Jarodzka, H., Klemke, R., & Specht, M. (2019). Can you ink while you blink? Assessing mental effort in a sensor-based calligraphy trainer. Sensors, 19(14), Article 3244. https://doi.org/10.3390/s19143244

Liu, H., & Zhang, L. (2025). Digital transformation of calligraphy teaching in the context of artificial intelligence: Motivation, challenges, and approaches [In Chinese]. Journal of Suzhou Vocational and Technical College, 28(4), 61–67. https://doi.org/10.13985/j.cnki.34-1227/c.2025.04.009

Loup-Escande, E., Frenoy, R., Poplimont, G., Thouvenin, I., Gapenne, O., & Megalakaki, O. (2017). Contributions of mixed reality in a calligraphy learning task: Effects of supplementary visual feedback and expertise on cognitive load, user experience and gestural performance. Computers in Human Behavior, 75, 42–49. https://doi.org/10.1016/j.chb.2017.05.006

Mann, A.-M., Hinrichs, U., & Quigley, A. (2015). Digital pen technology's suitability to support handwriting learning. In T. Hammond, S. Valentine, A. Adler, & M. Payton (Eds.), The impact of pen and touch technology on education (pp. 7–22). Springer. https://doi.org/10.1007/978-3-319-15594-4_2

Matsumaru, T., & Narita, M. (2017). Calligraphy-stroke learning support system using projector and motion sensor. Journal of Advanced Computational Intelligence and Intelligent Informatics, 21(4), 697–708. https://doi.org/10.20965/jaciii.2017.p0697

Mayer, R. E. (2021). Multimedia learning (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781316941355

McKay, B., Hussien, J., Vinh, M.-A., Mir-Orefice, A., Brooks, H., & Ste-Marie, D. M. (2022). Meta-analysis of the reduced relative feedback frequency effect on motor learning and performance. Psychology of Sport and Exercise, 61, Article 102165. https://doi.org/10.1016/j.psychsport.2022.102165

Ministry of Education. (2013, January 18). Notice on issuing the Guidelines for calligraphy education in primary and secondary schools. https://www.moe.gov.cn/srcsite/A26/s8001/201301

Ministry of Education. (2025, May 8). Notice on the issuance of two educational industry standards: Smart education platform—General requirements for personal information protection and Basic data for primary and secondary school faculty and staff. https://www.moe.gov.cn/srcsite/A16/s3342/202507

Narita, M., & Matsumaru, T. (2015). Calligraphy-stroke learning support system using projection. In 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (pp. 640–645). IEEE. https://doi.org/10.1109/ROMAN.2015.7333576

Nishino, H., Murayama, K., Shuto, K., Kagawa, T., & Utsumiya, K. (2011). A calligraphy training system based on skill acquisition through haptization. Journal of Ambient Intelligence and Humanized Computing, 2(4), 271–284. https://doi.org/10.1007/s12652-010-0042-y

Sigrist, R., Rauter, G., Riener, R., & Wolf, P. (2013). Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychonomic Bulletin & Review, 20(1), 21–53. https://doi.org/10.3758/s13423-012-0333-8

Song, T. (2015). Disciplinary norms and curriculum positioning of calligraphy education in primary and secondary schools [In Chinese]. Journal of Teaching and Management, (2), 37–39.

State Council. (2023, October 16). Regulations on the protection of minors in cyberspace. https://xzfg.moj.gov.cn/front/law/detail?LawID=1694

van der Veer, I. P. A., Verbecque, E., Rameckers, E. A. A., Bastiaenen, C. H. G., & Klingels, K. (2022). How can instructions and feedback with external focus be shaped to enhance motor learning in children? A systematic review. PLoS ONE, 17(8), Article e0264873. https://doi.org/10.1371/journal.pone.0264873

Wang, C. (2018). The practical application of embodied cognition theory: Technology-supported situational interaction [In Chinese]. E-education Research, 39(7), 20–26. https://doi.org/10.13811/j.cnki.eer.2018.07.003

Wong, L.-H., Aw, G. P., Sun, H., Yen, C.-C., Teo, C. G., & Wen, Y. (2023). Effects of a machine learning-empowered Chinese character handwriting learning tool on rectifying legible writing in young children: A pilot study. In Proceedings of the 31st International Conference on Computers in Education (pp. 742–747). Asia-Pacific Society for Computers in Education. https://doi.org/10.58459/icce.2023.1067

Yang, X. (2022). Technological negotiation and bodily presence in the learning field of the digital age [In Chinese]. Open Education Research, 28(4), 50–58. https://doi.org/10.13966/j.cnki.kfjyyj.2022.04.006

Yuan, Q., Yang, G., & Lyu, R. (2025). Aesthetic judgment in calligraphic tracing: The dominant role of dynamic features. Behavioral Sciences, 15(4), Article 525. https://doi.org/10.3390/bs15040525

Published

2026-09-29