Automatic construction of a bug library for object-oriented novice Java programmer errors
Machine learning techniques have been applied to the task of student modeling, more so in building tutors for acquiring programming skill. These were developed for various languages (Pascal, Prolog, Lisp, C++) and programming paradigms (procedural and declarative) but never for object-oriented progr...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2008
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2060 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | Machine learning techniques have been applied to the task of student modeling, more so in building tutors for acquiring programming skill. These were developed for various languages (Pascal, Prolog, Lisp, C++) and programming paradigms (procedural and declarative) but never for object-oriented programming in Java. JavaBugs builds a bug library automatically using discrepancies between a student and correct program. While other works analyze code snippets or UML diagrams to infer student knowledge of object-oriented design and programming, JavaBugs examines a complete Java program and identifies the most similar correct program to the student's solution among a collection of correct solutions and builds trees of misconceptions using similarity measures and background knowledge. Experiments show that JavaBugs can detect the most similar correct program 97% of the time, and discover and detect 61.4% of student misconceptions identified by the expert. © 2008 Springer-Verlag Berlin Heidelberg. |
|---|