Intelligent Educational Systems for Teaching Programming

this article, we described three types of systems: intelligent tutoring system, standalone expert critiquing system and computer supported critiquing system. They all can provide helpful feedback to student code, but each has its own pros and cons. Tutoring systems can provide step-by-step support for completing a program, but they usually need to have extensive knowledge about the domain content, student modeling and pedagogical strategy [22]. Users in the system can only work on a predefined set of exercises. Expert critiquing systems do not have this limitation. They can perform critiquing on any code, which enables them to be beneficial for both beginner and intermediate level programmers. As with intelligent tutoring systems, expert critiquing systems require significant development effort before they can be put into use. Computer supported critiquing systems avoid this difficulty by allowing incremental authoring during real use of the system. Systems can be put into use during the early development stages. They require, however, a human in the feedback loop to ensure the quality of the feedback and handle situations the system cannot. While most systems mentioned in this article have proved effective in teaching programming, they are primarily for research purposes. Few systems have been deployed and used in a large scale. Nearly all of Page 4 of 6 Intelligent Educational Systems for Teaching Programming them were started from scratch. Reusable infrastructures with authoring tools are needed to reduce the development effort for these systems. Eventually, integration into commonly used programming development environments can make the educational experience provided by these systems more available to real-life programmer