educators to re-embed it into training students or retooling teachers or professionals.

Blake went on to explain that his experience over the past year, based on the first workshop and his own personal observations of his son’s learning progression from kindergarten to first grade, had caused his thinking to evolve. Now, the notion of developmental milestones is very important to him. He believes that the understanding of computational thinking should be thought of in terms of decomposing computational thinking “elements” into developmental milestones.

Blake noted that during Peter Henderson’s presentation on the efforts underway at Shodor, Henderson’s example featuring Thomas the Train in solving a routing challenge demonstrates that there seems to be an opportunity to start to understand computational thinking at the lowest levels, and then as we move from K-12 into postsecondary education, we can explore increasing complexity within the milestones.

Blake summarized several main points he had gathered from the second workshop’s presentations. There may be an opportunity very early in a child’s learning progression to identify significant computational thinking talent. This might be done by looking at specific instances where computational thinking might fold into a learning activity, and then assessing a student’s competency with respect to these computational elements. To illustrate, Blake pointed back to Henderson’s Thomas the Train example and suggested that a simple activity with embedded computational thinking challenges might be a means of identifying talent. Concerning the idea of training, Blake argued that by taking opportunities to identify and assess computational thinking talent in individual students, and to start to enumerate indicators of such talent, a researcher or an educator might be able to recognize when a student either is demonstrating a significant talent in computational thinking or is at least at the appropriate learning progression level for that age range.

Blake argued that the next step would be to use this process of embedding, assessing, and identifying at the macro level over a longer period of time to identify learning progression baselines. This technique utilizes assessment and evaluation to determine where in learning development a particular baseline is situated.

From the perspective of learning progression at the macro level, the types of concepts to be enumerated so as to identify potentially talented computational thinkers at young ages are not limited solely to concepts related obviously to computer science thinking, math thinking, or even scientific thinking. Instead, these concepts are likely to span all of these types of thinking and analysis. As the emerging computation community moves forward, scholars should perhaps target these sorts of concepts to specify them more clearly and possibly re-embed them for identification of talent and for determination of learning progression.

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