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Working memory capacity is known to predict the performance of novices and experts on a variety of tasks found in STEM (Science, Technology, Engineering, and Mathematics). A common feature of STEM tasks is that they require the problem solver to encode and transform complex spatial information depicted in disciplinary representations that seemingly exceed the known capacity limits of visuospatial working memory. Understanding these limits and how visuospatial information is encoded and transformed differently by STEM learners presents ne