University Of Tasmania

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Mining autograding data in computer science education

conference contribution
posted on 2023-05-23, 10:56 authored by Gramoli, V, Michael CharlestonMichael Charleston, Jeffries, B, Koprinska, I, McGrane, M, Radu, A, Viglas, A, Yacef, K

In this paper we present an analysis of the impact of instant feedback and autograding in computer science education, beyond the classic Introduction to Programming subject.

We analysed the behaviour of 1st year to 4th year students when submitting programming assignments at the University of Sydney over a period of 3 years. These assignments were written in different programming languages, such as C, C++, Java and Python, for diverse computer science courses, from fundamental ones - algorithms, complexity, formal languages, data structures and artificial intelligence to more "practical" ones - programming, distributed systems, databases and networks.

We observed that instant feedback and autograding can help students and instructors in subjects not necessarily focused on programming. We also discuss the relationship between the student performance in these subjects and the choice of programming languages or the times at which a student starts and stops working on an assignment.


Publication title

Proceedings of the Australasian Computer Science Week Multiconference






School of Natural Sciences


Association for Computing Machinery

Place of publication

United States of America

Event title

18th Australasian Computer Science Week

Event Venue

Canberra, Australia

Date of Event (Start Date)


Date of Event (End Date)


Rights statement

Copyright 2016 ACM

Repository Status

  • Restricted

Socio-economic Objectives

Teaching and instruction technologies

Usage metrics

    University Of Tasmania