A Programming, Robotics and Automatic Control Intervention for Secondary Education Students in Sweden and Italy
eess.SY, cs.SY
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: This paper has 40 pages and 10 figures. Partial results have been presented at NPCW26 in Denmark and are available at https://npcw2026.compute.dtu.dk/Yamashita_npcw2026.pdf
Code: https://github.com/ANcybernetics/AutoSTEM-VirtualToolkit4https:
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
The gist: This study evaluates the AutoSTEM workshop, an intervention for secondary education that combines a serious game with PID-controlled hardware.
Abstract
This study evaluates the AutoSTEM workshop, an intervention for secondary education that combines a serious game with PID-controlled hardware. Seven workshops were conducted across Sweden and Italy. The six Swedish workshops adopted an explicitly SDT-informed facilitation framework, while the Italian workshop followed the existing educational robotics format without a formally defined SDT facilitation protocol. Self-reports, an objective knowledge quiz, and qualitative responses were analysed using multiple site-adjusted statistical approaches. Technical-specific self-efficacy increased substantially in both conditions, with large effect sizes, while objective knowledge showed only modest, non-significant gains. No significant site-adjusted differences were found between SDT and control conditions for the primary outcomes. Perceived engagement was higher in the control condition, although this finding should be interpreted cautiously. The objective knowledge composite remained positive but non-significant across sensitivity analyses. Female participants reported smaller PID self-efficacy gains than males. Qualitative findings supported evidence of PID learning while identifying technical and pacing barriers. Overall, the results suggest that the technology-rich intervention supports competence development, regardless of SDT-informed facilitation.
Related papers
- One Request, Multiple Experts: LLM Orchestrates Domain Specific Models via Adaptive Task Routing
- A Geometric Decision Procedure for STL Feasibility and Repair
- Scaling up statistical model checking of cyber-physical systems via algorithm ensemble and parallel simulations over HPC infrastructures
- From Asymptotic to Designer-Assigned-Time Control: A Review of Stability Notions, Design Mechanisms, and Controller Architectures
- Battery Second Life: A Review of Experimental Studies
- Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems