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DTSTART;TZID=America/Denver:20231113T143100
DTEND;TZID=America/Denver:20231113T143900
UID:submissions.supercomputing.org_SC23_sess454_ws_eduhpcp111@linklings.co
 m
SUMMARY:Data-Driven Discovery of Anchor Points for PDC Content
DESCRIPTION:Matthew McQuaigue, Erik Saule, and Kalpathi Subramanian (Unive
 rsity of North Carolina, Charlotte) and Jamie Payton (Temple University)\n
 \nThe Parallel and Distributed Computing community has been interested in 
 integrating PDC content into early CS curriculum to prime the students for
  more advanced materials and build a workforce able to leverage advanced c
 omputing infrastructure. To deploy this strategy at scale, it is important
  to identify anchor points in early CS courses where we can insert PDC con
 tent.\n\nWe present an analysis of CS courses that primarily focuses on CS
 1 and Data Structure courses. We collected data on course content through 
 in-person workshops, where instructors of courses classified their course 
 materials against standard curriculum guidelines.\n\nBy using these classi
 fication, we make sense of how Computer Science is being taught.  We highl
 ight different types of CS1 and Data Structure courses.  And we provide re
 flection on how that knowledge can be used by PDC experts to identify anch
 oring points for PDC content, while being sensitive to the needs of instru
 ctors.\n\nTag: Education, Heterogeneous Computing, Reproducibility, State 
 of the Practice, Sustainability\n\nRegistration Category: Workshop Reg Pas
 s\n\nSession Chairs: David P. Bunde (Knox College); Sushil K. Prasad (Univ
 ersity of Texas at San Antonio); Satish Puri (Missouri University of Scien
 ce and Technology); Apan Qasem (Texas State University); and George K. Thi
 ruvathukal (Loyola University, Chicago; Argonne National Laboratory (ANL))
 \n\n
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