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Figure 1. Example of ONACT Assessment Dashboard showing every student’s performance in a given classroom.
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Figure 2. The Computational Thinking Pattern Analysis Forensics graph explains how a student has progressed their computational thinking pattern implementations by programming with AgentSheets (or AgentCubes).



ONline Assessment of Computational Thinking (ONACT) [3] is an embedded, formative, real-time graphical assessment tool that quickly gives teachers insight into student mastery of computational thinking constructs as they are creating games and simulations. ONACT provides teachers with the most useful representations of class and individual progress, allowing them to make effective instructional decisions. The ONACT system breaks down all collectable student project information and records it in the ONACT database. ONACT analyzes the student project information stored in this database through Computational Thinking Pattern Analysis in real time. This analysis extracts semantic meaning out of the code by interpreting which Computational Thinking Patterns have been implemented by students. The analyzed data are illustrated through different levels of visualization: Computational Thinking Pattern Analysis Graph, Computational Thinking Pattern Analysis Forensics (Figure 2), and Assessment Dashboard (Figure 1).
The Assessment Dashboard indicates to teachers where students are in their programming tasks. The dashboard visualizes the programming progression for each student in the class through CTPA [1, 2]. In Figure 1, green indicates students who are completing the program correctly, orange indicates students who may need some help with their program, and red indicates students who are in significant need of scaffolding. The Dashboard clearly shows students that might be in trouble. By selecting a specific student in the Dashboard, a teacher can see in-depth representations of that student’s progression in their Computational Thinking Pattern Analysis Graph [1, 2] and Computational Thinking Pattern Analysis Forensics.

  • Koh, K. H., Basawapatna, A.,Bennett, V., Repenning, A., Towards the Automatic Recognition of Computational Thinking for Adaptive Visual Language Learning, IEEE International Symposium on Visual Languages and Human-Centric Computing 2010, Leganés-Madrid, Spain, September 21-25, 2010
  • Ioannidou, A., Repenning, A. and Webb, D., AgentCubes: Incremental 3D end-user development, Journal of Visual Language and Computing (2009)
  • Koh, K. H., Basawapatna, A., Nickerson, H., Repenning, A., Real Time Assessment of Computational Thinking, IEEE International Symposium on Visual Languages and Human-Centric Computing, Melbourne, Australia, July 28-Aug 1, 2014