C. Evans, “The Effectiveness of m-Learning in the Form of Podcast Revision Lectures in Higher Education,” International Journal of Computers & Education, Vol. 50, No. 2, 2008, pp. 491-498.

has been cited by the following article:

• TITLE: An Intelligent Assessment Tool for Students’ Java Submissions in Introductory Programming Courses

  AUTHORS: Fatima Al Shamsi, Ashraf Elnagar

  KEYWORDS: Java; Programming; Computer Aided Education; Computer Aided Assessment; Control Dependence Graphs

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.4 No.1, February 28, 2012

  ABSTRACT: This paper presents a graph-based grading system for Java introductory programming courses, eGrader. This system grades submission both dynamically and statically to ensure a complete and through grading job. While dynamic analysis is based on JUnit framework, the static analysis is based on the graph representation of the program and its quality which is measured by software metrics. The graph representation is based on the Control Dependence Graphs (CDG) and Method Call Dependencies (MCD). eGrader outperforms existing systems in two ways: the ability of grading submission with semantic-errors, effectively, and generating reports for students, as a feedback on their performance, and instructors on the overall performance of the class. eGrader is well received by instructors not only for saving time and effort but also for its high success rate that is measured by four performance indicators which are sensitivity (97.37%), specificity (98.1%), precision (98.04%) and accuracy (97.07%).