The potential use of Bayesian Networks to support committee decisions in programmatic assessment.

Bayesian Networks offer an approach that is theoretically well-supported for programmatic assessment. They can aid committees in managing evidence accumulation, help them make inferences under conditions of uncertainty, and buttress decisions by adding a layer of defensibility to the process. They are a pragmatic tool adding value to the programmatic space by applying a complementary statistical framework. We see four major benefits of BNs in programmatic assessment: BNs allow for visual capturing of evidentiary arguments by committees during decision-making; 'recommendations' from probabilistic pathways can be used by committees to confirm their qualitative judgments; BNs can ensure precedents are maintained and consistency occurs over time; and the imperative to capture data richness is maintained without resorting to questionable methodological strategies such as adding qualitatively different things together. Further research into their feasibility and robustness in practice is warranted.