How can learning be computed? Curriculum, using visual language as the motivational context with embedded computer science content was utilized in one college computer science class and two middle school technology classes. From the data collected in these three classes over the course of a semester, associated learning progressions were computed from several computational thinking patterns. By comparing the results (learning progressions), some obvious and some not so obvious indications emerged. We believe that the more obvious indications give credence to the less obvious, and hence the measurement tool. This comparison between middle school students and college students demonstrated that middle school students?' learning progressions are slower than college level students (obvious), but middle school students?' learning skill scores reached/surpassed the entry level scores of students in the college class after designing only two or more games. Consequently, these results tell us that this measurement tool although not validated yet, could measure accumulated learning in certain contexts. Although this is just the first “outing” of this tool these results strongly indicate that the tool provides an accurate measure of the concept, in this case, learning accumulation or transfer.