When should professional-development places be concentrated (1.0.0)
This Python agent-based model simulates the diffusion of instructional practices among primary-school science teachers connected through within-school and cross-school networks. It represents teachers as agents nested in schools and compares five adoption mechanisms: simple contagion, proportion thresholds, count thresholds, adaptive norm conformity, and an individual-only baseline. The model evaluates fixed-budget training allocations, including concentrated and distributed policies, and estimates when school-level dose-response evidence can support targeted allocation. Experiments examine peer interference, cross-school contact intensity, global critical transitions, allocation stability, and the distinction between participant-level and system-level outcomes. Teacher attributes are informed by a de-identified Beijing questionnaire, whereas team sizes and contact networks are explicit model assumptions. The package includes executable Python scripts, ODD documentation, parameter tables, experiment metadata, simulation outputs, and the authorized questionnaire workbook required to reproduce the questionnaire-informed analyses. Results are intended as model-based design evidence for future longitudinal research rather than forecasts of adoption rates.
Release Notes
Version 1.0.0 — Initial reproducible release. This release provides the complete Python implementation of the training-diffusion agent-based model, including the core simulation, fixed-budget allocation experiments, global-critical diagnostics, and critical-region allocation experiments. It includes ODD documentation, parameter tables, experiment metadata, reproducible random-seed information, simulation outputs, and the authorized de-identified questionnaire workbook used to generate questionnaire-informed teacher attributes. The model represents teachers nested in schools and compares simple contagion, proportion thresholds, count thresholds, adaptive norm conformity, and an individual-only baseline. This release also documents cross-school interference, dose-response estimation, allocation stability, and global critical transitions. No known software bugs remain in the released scripts. Public redistribution of the questionnaire workbook remains subject to the data provider’s authorization and applicable ethics/data-use conditions.
Associated Publications
When should professional-development places be concentrated 1.0.0
Submitted by
yuhouchunsun
Published Oct 25, 2026
Last modified Oct 25, 2026
This Python agent-based model simulates the diffusion of instructional practices among primary-school science teachers connected through within-school and cross-school networks. It represents teachers as agents nested in schools and compares five adoption mechanisms: simple contagion, proportion thresholds, count thresholds, adaptive norm conformity, and an individual-only baseline. The model evaluates fixed-budget training allocations, including concentrated and distributed policies, and estimates when school-level dose-response evidence can support targeted allocation. Experiments examine peer interference, cross-school contact intensity, global critical transitions, allocation stability, and the distinction between participant-level and system-level outcomes. Teacher attributes are informed by a de-identified Beijing questionnaire, whereas team sizes and contact networks are explicit model assumptions. The package includes executable Python scripts, ODD documentation, parameter tables, experiment metadata, simulation outputs, and the authorized questionnaire workbook required to reproduce the questionnaire-informed analyses. Results are intended as model-based design evidence for future longitudinal research rather than forecasts of adoption rates.
Release Notes
Version 1.0.0 — Initial reproducible release. This release provides the complete Python implementation of the training-diffusion agent-based model, including the core simulation, fixed-budget allocation experiments, global-critical diagnostics, and critical-region allocation experiments. It includes ODD documentation, parameter tables, experiment metadata, reproducible random-seed information, simulation outputs, and the authorized de-identified questionnaire workbook used to generate questionnaire-informed teacher attributes. The model represents teachers nested in schools and compares simple contagion, proportion thresholds, count thresholds, adaptive norm conformity, and an individual-only baseline. This release also documents cross-school interference, dose-response estimation, allocation stability, and global critical transitions. No known software bugs remain in the released scripts. Public redistribution of the questionnaire workbook remains subject to the data provider’s authorization and applicable ethics/data-use conditions.