Plenary: SOC Plenary Virtual 2 (Virtual) on Thursday, July 16, 2026, 7:00 PM
Room: Virtual Room Main
Thread: Learning and Teaching
Duration: 60 minutes
Chairs: Jack Mercer, Ellen O'Neill
Support: Mariana Otero Becerril
Beyond Adoption Rates: Sustainable AI-Integration in K-12 Education
Presenters: Luis Luna-Reyes, Somya Luthra
Keywords: Public Policy, Equity and Justice, AI Adoption, Professional Development, AI Policy, TAM, AI Competency
Teacher AI adoption is growing but remains fragile. Once adopted, AI tools may be abandoned, leading to competency loss through forgetting and requiring a second round of professional development before re-adoption is viable. This dynamic is invisible to cross-sectional survey methods and unaddressed by existing technology adoption frameworks. To the best of the authors’ knowledge, this paper develops the first system dynamics model of teacher AI adoption calibrated against TALIS 2024 data and other secondary sources. The model uses a co-flow structure to track teacher competency across three adoption states over a 100-month simulation horizon. Eight policy experiments are tested. Policies that accelerate adoption, including peer network amplification and institutional mandates, reliably generate a competency trap in which peak disengaged teachers reach nearly double the baseline level. Training without embedded classroom practice produces worse outcomes than the status quo across every indicator. Re-engagement support for previously disengaged teachers is the most efficient single-lever intervention available. Disengaged teachers carry substantially higher workloads than their adopting colleagues, creating a growing within-school workload inequality. Sensitivity analysis confirms that these findings are robust across the plausible parameter space. The findings have direct implications for how AI adoption strategies are designed, sequenced, and evaluated in national education systems.
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Labour Market, Gender Norms and Population Mental Health in Scotland
Presenter: Shreya Sonthalia
Keywords: Health
The prevalence of poor mental health among working-age adults in Scotland has risen since the mid 2000s, with women consistently report higher rates than men despite decades of measurable progress in gender equality. This paper investigates the structural mechanisms sustaining this "Scottish Gender Paradox" by examining the dynamic interaction between the labour market, gender norms, and population mental health. A simulation model, grounded in complex realism, and based in a feedback-driven literature synthesis was developed. Disconfirmatory interviews were conducted with 10 experts. The gender gap in poor mental health persists primarily because structural gender inequality channels women into poor mental health at a higher rate. The historical rise in poor mental health for both genders was not primarily driven by the 2008 recession. Within the model, the recession functioned as an activating event for pre-existing structural vulnerabilities rather than as an independent cause of the mental health trend. The recession's mental-health cost is carried almost entirely by the rise in insecure work it accelerated, not by the demand shock itself.
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