Improving Programming Education Quality with Automatic Grading System

Yun Zhan Cai, Meng Hsun Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


As the rapid growth of information technology, the demand for proficiency in software programming skyrockets. Compared to teaching with slides traditionally, hands-on programming training is more beneficial and practical. However, it is exhausting and time-consuming for educators to grade all assignments in person. Besides, students may not get feedback immediately to correct their wrong conceptions. Therefore, an automatic grading system is required to grade and send feedback to students. Based on an existing continuous integration system, which checks whether new programs behave as expected, we develop a set of course management tools and deploy an automatic grading system in this paper. Our system requires a server to run and test the programs. However, the server is susceptible to being compromised by hackers. Therefore, how we protect sensitive data and prevent malicious network traffic are demonstrated in this paper as well. The tools were applied in an Android application development course with 140 students enrolled. Around 72% of the students indicate the automatic grading system is beneficial to their learning.

Original languageEnglish
Title of host publicationInnovative Technologies and Learning - 2nd International Conference, ICITL 2019, Proceedings
EditorsLisbet Rønningsbakk, Ting-Ting Wu, Frode Eika Sandnes, Yueh-Min Huang
Number of pages9
ISBN (Print)9783030353421
Publication statusPublished - 2019
Event2nd International Conference on Innovative Technologies and Learning, ICITL 2019 - Tromsø, Norway
Duration: 2019 Dec 22019 Dec 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11937 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Conference on Innovative Technologies and Learning, ICITL 2019

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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