Generating Multi-Part Autogradable Faded Parsons Problems From Code-Writing Exercises

Abstract

Parsons Problems and Faded Parsons Problems have been shown to be effective in helping students in programming courses transition from passive learning, such as lectures or textbooks, to active learning in the form of writing code. We present FPPgen, an authoring system that largely automates the conversion of existing open-ended code-writing exercises to Faded Parsons Problems (FPPs). FPP solutions can be machine-checked using either spec-based autograding, in which student solutions are evaluated against instructor-provided test cases, or mutation-based autograding, in which students produce one or more unit tests that are evaluated using mutation testing. Our system allows creating exercises that rely on complex libraries and helper functions, such as student code intended to be run as part of a complex framework-based application. Our system also gracefully supports cumulative multi-part problems, in which later parts build on earlier parts. Python and Ruby exercises are currently supported, but FPPgen is language-agnostic and adding autograders for other languages is straightforward. In our experience so far, instructors can draft simple questions in less than an hour and mutation-based questions in about two hours as open-ended coding questions, and student helpers can use our tools to convert these to FPPs in less than an hour. FPPgen is in active use in both beginning and advanced large-enrollment programming courses in a CS undergraduate program at a large US university.