Learning to program is a complex task and is a documented persistent challenge. We are intermingling Writing-to-Learn (WTL) strategies in support of learning to program. Initial efforts examined existing writing in the form of guided source code comments. This poster displays the results for the following three research questions: RQ1) What do source code comments tell us about novice programmers' thinking processes while coding? RQ2) What do source code comments tell us about how students visually organize their source code? RQ3) What differences exists for students receiving traditional instruction versus WTL instruction? To answer these questions, we analyzed students' programming assignments from an introductory programming course with and without WTL instruction. The analysis generated a qualitative codebook that can be used to classify source code comments with respect to thinking processes and organizational patterns. The resultant qualitative codebook is displayed and audience members can use the codebook to classify comments. We are soliciting feedback regarding the reliability, validity, and completeness of the codebook, and future project plans. This material is based upon work supported by the National Science Foundation under Grant No. DUE-1612132. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. In this paper, we present a feature-based vortex detection and visualization technique that is appropriate for large computational fluid dynamics data sets computed on unstructured meshes. In particular, we focus on the application of this technique to visualization of the flow over a serrated wing and the flow field around a spinning missile with dithering canards. We have developed a core line extraction technique based on the observation that vortex cores coincide with local extrema in certain scalar fields. We also have developed a novel technique to handle complex vortex topology that is based on k-means clustering. These techniques facilitate visualization of vortices in simulation data that may not be optimally resolved or sampled. Results are included that highlight the strengths and weaknesses of our approach. We conclude by describing how our approach can be improved to enhance robustness and expand its range of applicability.