Computational Thinking Pattern Analysis (CTPA) is a tool that can be used to measure a student's programming skills automatically, in real-time. It does this by analyzing the semantic information in a student's program. Semantic information is the meaning of the code, as opposed to the syntax, which is the structure of the code. CTPA can track an individual student's learning or skill trajectory by analyzing the semantic information in their programs over time.

While the semantic information from individual games/simulations only represents a piece of student learning development, collective semantic analysis of all of a student's games or simulations could provide a measurement of that student's overall progress. This is because the semantic information in a student's programs can be used to assess their knowledge and skills in a variety of areas, such as problem-solving, algorithm design, and data structures.

Representing semantic meaning in measurable units to visually demonstrate student-learning trends, and to represent the students’ knowledge and skill, can benefit students and teachers directly. This approach could also indicate possible curriculum failings at a fundamental level.

1. Bennett, V., Koh, K. H., Repenning, A., Can Learning Acquisition be Computed?, IEEE International Symposium on Visual Languages and Human-Centric Computing 2011, Pittsburgh, PA, USA, September 18-22, 2011.

2. Koh, K. H., Nickerson, H., Basawapatna, A., Repenning, A., Early Validation of Computational Thinking Pattern Analysis, ITiCSE '14: Annual Conference on Innovation and Technology in Computer Science Education, Uppsala, Sweden, June 23-25, 2014