Scientific opportunities

LEVANTE provides a rich array of opportunities for future investigation.
Some examples of LEVANTE’s additional scientific opportunities are as follows:

Investigating mechanisms of developmental change using causal inference techniques.

  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

Understanding the intersection between developmental change and key foci of clinical and applied interest.

  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

Engaging with new advances in machine learning to identify predictors of developmental and learning outcomes.

  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