Exploring Ionospheric Disturbances Using GNSS: A STEM-Based Investigation of the 2024 Extreme Geomagnetic Storm - Chollada Pansong; Nitipat Buakao; Thanapon Keokhumcheng; Pharinya Phothila; Patcharin Intamas; Prasert Kenpankho (My University, 2025)
This study investigates the effectiveness of a STEM-based instructional approach integrating GNSS satellite technology and ionospheric TEC (Total Electron Content) analysis during extreme geomagnetic storms. The objective was to enhance students’ conceptual understanding, practical skills, and STEM-related attitudes through interdisciplinary learning activities. The SPACE model (Study, Plan, Analyze, Create, Evaluate) was applied as a pedagogical framework to guide students through real-world TEC anomaly detection using GPS RINEX data and computational tools. The integration of real satellite data and hands-on analysis enabled students to connect theoretical knowledge with real-world phenomena, deepening their engagement and inquiry-based thinking. Pre- and post-test results revealed statistically significant improvements, with scores increasing from a mean of $\mathbf{5 1. 8 (S D = 7. 5 4)}$ to $\mathbf{7 5. 0}(\mathbf{S D}=$ 7.42) ($\mathbf{p}\lt \mathbf{0. 0 0 0 0 0 1}$). Moreover, the STEM Attitude Questionnaire reflected strong positive perceptions, especially in STEM career motivation ($\bar{x}=4.20$) and perceived value of STEM ($\bar{x}=$ 4.13). These findings highlight the model’s potential to foster STEM readiness. Integrating GNSS-based TEC analysis into the STEM framework significantly enhanced students’ academic outcomes, practical skills, and STEM attitudes.
Keywords: Earthquake Detection and Analysis; Ionosphere and magnetosphere dynamics; GNSS positioning and interference