Computational Thinking Pattern Analysis (CTPA) is a technique for measuring student learning skills in computational thinking. It does this by analyzing the semantic meaning of a student's work, and comparing it to a set of pre-defined computational thinking patterns. CTPA can be used to assess student learning in a variety of contexts, including natural language processing, visual end-user programming, and computer science.

CTPA uses a Latent Semantic Analysis (LSA) inspired technique to analyze the semantic meaning of a student's work. LSA is a technique for finding the hidden relationships between words. CTPA uses LSA to find the hidden computational thinking between the programming blocks in a student's work, and to identify the computational thinking patterns that are being used.

CTPA is a powerful tool for measuring student learning in computational thinking. It can be used to assess student learning in a variety of contexts, and it can be used to identify areas where students need additional support.

Here are some of the benefits of using CTPA:

• CTPA can be used to assess student learning in a variety of contexts, including natural language processing, visual end-user programming, and computer science.

• CTPA can be used to identify areas where students need additional support.

• CTPA can be used to track student progress over time.

• CTPA can be used to compare student performance to a set of benchmarks.

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2. Ioannidou, A., Repenning, A. and Webb, D., AgentCubes: Incremental 3D end-user development, Journal of Visual Language and Computing (2009)

3. Landauer, T. K., Foltz, P. W., Laham, D. Introduction to Latent Semantic Analysis. Discourse Processes, 25, 1998, 259-284

4. 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