A Virtual Manipulative for Learning Log-Linear Models

We present an open-source virtual manipulative for conditional log-linear models. This web-based interactive visualization lets the user tune the probabilities of various shapes—which grow and shrink accordingly—by dragging sliders that correspond to feature weights. The visualization displays a regularized training objective; it supports gradient ascent by optionally displaying gradients on the sliders and providing “Step” and “Solve” buttons. The user can sample parameters and datasets of different sizes and compare their own parameters to the truth. Our website, http://cs.jhu.edu/ ̃jason/ tutorials/loglin/, guides the user through a series of interactive lessons and provides auxiliary readings, explanations, practice problems and resources.