Generating abstract and real-world coding exercises with adjustable difficulty

• Main Authors: Tiam-Lee, Thomas James Z., Sumi, Kaoru
• Format: text
• Published: Animo Repository 2018
• Subjects: Natural language generation (Computer science); Computer Engineering; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/13074
• Institution: De La Salle University

We developed an approach for automatically generating abstract and real-world coding exercises with adjustable difficulty. Using our approach, we can produce exercises based on abstract computational operations for learning the syntax of a programming language, and exercises based on real-life contexts for learning abstraction and logic formulation. We present an initial evaluation of the exercises by students and teachers of programming. This work can pave the way for the development of intelligent programming tutors with adaptive and personalized feedback that can display content based on the state of the student.