Most researchers receive formal training in frequentist statistics during their undergraduate studies. In particular, hypothesis testing is usually rooted on the null hypothesis significance testing paradigm and its p-value. Null hypothesis Bayesian testing and its so-called Bayes factor are now becoming increasingly popular. Although the Bayes factor is often introduced as being the Bayesian counterpart to the p-value, its computation, use, and interpretation are quite distinct from the p-value. There is now evidence confirming that the application of the Bayes factor in applied research is ill-devised. To improve the current status quo, we have created a Shiny/R app called "the Bayes factor," which offers a dynamic tutorial for learning all the basics about the Bayes factor. In this paper, we explain how the app works and we offer suggestions on how to use it in class or self-study settings. The app is freely available at https://statsedge.org/shiny/LearnBF/.