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DTSTART;TZID=America/Chicago:20181112T111000
DTEND;TZID=America/Chicago:20181112T113000
UID:submissions.supercomputing.org_SC18_sess166_ws_bphpcte111@linklings.co
 m
SUMMARY:Evaluating Active Learning Approaches for Teaching Intermediate Pr
 ograming at an Early Undergraduate Level
DESCRIPTION:Dhruva Chakravorty, Donald McMullen, Honggao Liu, Noushin Ghaf
 fari, Dylan Rodriguez, and Shaina Le (Texas A&M University)\n\nThere is a 
 growing need to provide intermediate programing classes to STEM students e
 arly in their undergraduate careers. These efforts face significant challe
 nges owing to the varied computing skill-sets of learners, requirements of
  degree programs and the absence of a common programing standard. Instruct
 ional scaffolding and active learning methods using Python offer avenues t
 o support these students with varied needs. Here, we report on quantitativ
 e and qualitative outcomes from three distinct models of programing educat
 ion that (i) connect coding to hands-on “maker” activities; (ii) increment
 al learning of computational thinking elements through guided exercises us
 ing Jupyter Notebooks; and (iii) problem-based learning with step-wise cod
 e fragments leading to algorithmic implementation.  Performance in in-clas
 s activities, capstone projects, in-person interviews and extensive survey
 s informed us about the effectiveness of these approaches on various aspec
 ts of student learning.  Students with previous coding experience were abl
 e to rely on broader skills and grasp concepts faster than students who re
 cently attended an introductory programing session. We find that while mak
 er-space activities were engaging and explained basic programing concepts,
  they lost their appeal in complex programing scenarios. Students grasped 
 coding concepts fastest using the Jupyter notebooks, while the problem-bas
 ed learning approach was best at having students understand the core probl
 em and create inventive means to address them.\n\nTag: Education, Scientif
 ic Computing, Training, Scalable and Sustainable Approaches for HPC Traini
 ng and Education, Emerging Tools enabling HPC Training and Education, Ligh
 tning Talks and Demos\n\nRegistration Category: Workshop Reg Pass\n\nSessi
 on Chairs: Evguenia Alexandrova (Hartree Centre, STFC; Science and Technol
 ogy Facilities Council (STFC)); Scott Lathrop (University of Illinois Urba
 na-Champaign); Susan Mehringer (Cornell University); Julie Mullen (Massach
 usetts Institute of Technology (MIT), Lincoln Laboratory); Nitin Sukhija (
 Slippery Rock University of Pennsylvania); and Aaron Weeden (Shodor Educat
 ion Foundation)\n\n
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