Scientific opportunities

  1. Measuring effects of school initiation cutoffs as a causal instrument to understand changes in development
  2. Collecting site-level opportunities for other causal inference strategies, e.g., gathering information about local policy changes that might create opportunities for causal analysis
  3. Encouraging research partners to pursue random assignment to condition as part of their proposed research and test for downstream effects of randomization across constructs
  1. Tracking changes in diagnostic status to understand developmental prevalence and consequence of diagnoses in longitudinal data and across contexts
  2. Tracking device access and screen time and screen usage and their concurrent and longitudinal relationships with LEVANTE core constructs
  3. When possible (depending on site-specific cultural, ethical, and legal norms), tracking gender identity and gender transitions when and if they occur to better understand the development of gender identity across contexts
  1. Longitudinal prediction of learning outcomes regarding environmental, contextual, sociodemographic, and cognitive factors, both via fitting predictive models and via the possibility of open challenges for prediction
  2. Prediction of low-probability events, e.g. behavioral and diagnostic outcomes, via a similar strategy
  3. Engagement with cognitive and educational AI development via stimulus- and trial-level modeling of behavior