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UID:20250825T165120EDT-5008ia5u7h@132.216.98.100
DTSTAMP:20250825T205120Z
DESCRIPTION:Title: Opinionated practices for teaching reproducibility: moti
 vation\, guided instruction and practice.\n\nTitle: In the data science co
 urses at the University of British Columbia\, we define data science as th
 e study\, development and practice of reproducible and auditable processes
  to obtain insight from data. While reproducibility is core to our definit
 ion\, most data science learners enter the field with other aspects of dat
 a science in mind\, for example predictive modelling\, which is often one 
 of the most interesting topic to novices. This fact\, along with the highl
 y technical nature of the industry standard reproducibility tools currentl
 y employed in data science\, present out-ofthe gate challenges in teaching
  reproducibility in the data science classroom. Put simply\, students are 
 not as intrinsically motivated to learn this topic\, and it is not an easy
  one for them to learn. What can a data science educator do? Over several 
 iterations of teaching courses focused on reproducible data science tools 
 and workflows\, we have found that providing extra motivation\, guided ins
 truction and lots of practice are key to effectively teaching this challen
 ging\, yet important subject. Here we present examples of how we deeply mo
 tivate\, effectively guide and provide ample practice opportunities to dat
 a science students to effectively engage them in learning about this topic
 .\n\n \n\nColloque des sciences mathématiques du Québec\n	Zoom:To register:
  http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#csmq\n\nS
 ite web : http://crm.umontreal.ca/colloque-sciences-mathematiques-quebec/#
 csmq\n
DTSTART:20211029T193000Z
DTEND:20211029T203000Z
SUMMARY:Tiffany Timbers (University of British Columbia)
URL:/mathstat/channels/event/tiffany-timbers-universit
 y-british-columbia-334244
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