In the last decade, tutoring agencies have increased in the Netherlands. In the current paper we investigate a Bayesian hypothesis testing method tailored to the evaluation of educational interventions. Bayesian methods allow for inference that (1) disentangles no evidence and evidence for no effect and (2) reveals the degree of uncertainty that exists for a hypothesis rather than the binary of rejecting or not rejecting H-null. This presentation proposes a methodology for studying educational interventions using a combination of latent variable models that allow for growth over time and Bayesian methods to test hypotheses about growth between experimental conditions. A simulation study was conducted to test what Bayes factors can be expected given a limitation on data collection using a real-world example. The simulation showed that for no effect and larger effect sizes, one can expect to make the correct inference quite often, while for small effect sizes, the Bayes factor remains undecided.