Solving the Quadrilemma of Junior High Math Experimentation: Digital Intelligence Technology for Authentic π-Estimation Modelling Practices

DOI

10.2991/978-2-38476-497-6_12How to use a DOI?

Keywords

Digital Intelligence; π Estimation; Inquiry-Based Learning

Abstract

The deep integration of digital intelligence technology and education presents significant opportunities, yet junior high mathematics experimentation faces persistent challenges: unrealizable experiments, delayed feedback and neglected thinking process, neglected emotional experiences, and insufficient critical thinking development. This study develops a framework integrating multimodal digital intelligence technologies including AI agent companions, virtual simulation platforms, automated statistical tools, and real-time feedback systems to address these challenges. Using π-Estimation as a case study, implementation outcomes demonstrate measurable improvements: Students achieved 87.2% accuracy in high-level knowledge transfer tasks “Buffon Needle Experiment”, exhibited enhanced self-regulation on the Self-Regulation Scale for Science, showed improved critical thinking in analysis, evaluation, and inference based on CTSAS, and developed positive mathematical attitudes through contextualized historical experiences. The approach resolves traditional limitations through convergence of AI-driven historical immersion, multi-dimensional teacher-student-intelligent system feedback, and personalized cognitive scaffolding. Results indicate that such technology integration contributes to effective inquiry-based mathematics learning by supporting authentic experimentation, timely process-oriented feedback, emotional engagement, and critical thinking development.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xirun Zhu
AU  - Yang Li
AU  - Shixiang Deng
AU  - Tianqi Luo
PY  - 2025
DA  - 2025/12/15
TI  - Solving the Quadrilemma of Junior High Math Experimentation: Digital Intelligence Technology for Authentic π-Estimation Modelling Practices
BT  - Proceedings of the 2025 International Conference on Educational Innovation and Information Technology (EIIT 2025)
PB  - Atlantis Press
SP  - 120
EP  - 128
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-497-6_12
DO  - 10.2991/978-2-38476-497-6_12
ID  - Zhu2025
ER  -