Work

Syntax error based quantification of the learning progress of the novice programmer

Year: 2018

Type: conference-paper

Abstract: Recent data-driven research has produced metrics for quantifying a novice programmer's error profile, such as Jadud's error quotient. However, these metrics tend to be context dependent and contain free parameters. This paper reviews the caveats of such metrics and proposes a more general approach to developing a metric. The online implementation of the proposed metric is publicly available at http://online-analysis-demo.herokuapp.com/.

Source: ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE)

DOI: 10.1145/3197091.3197121

Authors: Alireza Ahadi, Raymond Lister, Luke Mathieson

Institution: University of Technology Sydney

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W2809399576