title: Can you hear me now? Effectiveness of formative feedback
keywords: programming education, online tool, data analytics, static analysis
topics: Case studies and Applications , Creative , Software Technology
committee: Ansgar Fehnker
started: April 2020
end: June 2020

Abstract

Novice programmers learn among others by getting formative feedback from student assistants on their programs. Increasingly, online platforms have been developed that also provide automated feedback to students. Previous research is inconclusive whether this feedback is actually efficient, i.e. whether it helps students to change their programming behaviour and skills. The aim of this project is to develop a method that automatically assesses whether feedback, either automated or by humans, is effective in improving the students' code. This information should be made available in the form of a dashboard to the teaching staff, such that they can determine the effectiveness of particular types of feedback, and to adjust interventions to make easier for the student to learn to program.

This project would be contributing to the SURF project ATELIER. This SURF project works on a platform that assists teaching assistant to provide better feedback in programming classes to students. One of the tools included is a static analysis for Processing, a language for new media and visual arts that is based on Java. This tool detects programming smells that arise from the common structure that all Processing programs share. It is built on PMD and can be used to batch process student programs.