Notice of RetractionA Graded Task-driven Methodology for Computer Science Education

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

In traditional task-driven methodology the tasks devised by the teachers are the same for every student. However, because of different ability of professional competencies of the students, some students with strong professional qualities will achieve the tasks perfectly, while others with poor professional abilities are at a loss what to do. In this paper, a graded task-driven methodology is proposed. Recognizing the different of the students´ abilities, we devise several kinds of tasks for the students to choose. The tasks are graded by its difficulty level, so every student can find the task that fit for him/her. Several years´ practice in the courses of ??Artificial Neural Network?? and ??Data Mining?? shows that this innovation is successful.