Tranquillo, J. (2011, June), A Semester-Long Student-Driven Computational Project  Paper presented at 2011 ASEE Annual Conference & Exposition, Vancouver, BC. 10.18260/1-2--17380

\bibitem{asee_peer_17380}
  Tranquillo, J. (2011, June), \emph{A Semester-Long Student-Driven Computational Project}
  Paper presented at 2011 ASEE Annual Conference \& Exposition, Vancouver, BC.
  10.18260/1-2--17380

Joe Tranquillo.  "A Semester-Long Student-Driven Computational Project".  2011 ASEE Annual Conference & Exposition, Vancouver, BC, 2011, June.  ASEE Conferences, 2011.  https://strategy.asee.org/17380 Internet.  14 May, 2024

\bibitem{asee_peer_17380}
  Joe Tranquillo.
  "A Semester-Long Student-Driven Computational Project".
  \emph{2011 ASEE Annual Conference \& Exposition, Vancouver, BC, 2011, June}.
  ASEE Conferences, 2011.
  https://strategy.asee.org/17380 Internet.  14 May, 2024

@INPROCEEDINGS{asee_peer_17380
author = "Joe Tranquillo"
title = "A Semester-Long Student-Driven Computational Project"
booktitle = "2011 ASEE Annual Conference \& Exposition"
year = "2011"
month = "June"
address = "Vancouver, BC"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/17380}
number = {10.18260/1-2--17380}
}

TY  - CPAPER
AB  -                   A  Semester-­Long  Student-­Driven  Computational  Project    Engineering  computing  is  a  topic  that  many  biomedical  engineering  departments  include  in  their  curriculum.  Yet,  the  philosophical  underpinnings  and  pedagogical  goals  of  a  computing  course  are  often  nebulous.  Should  the  course  lean  toward  an  advanced  math  course  (e.g.  Linear  Algebra,  Splines,  Numerical  Methods,  Non-­‐linear  dynamics),  with  programming  as  a  means  to  an  end?  Or  should  the  course  be  designed  to  learn  a  specific  computer  language,  such  as  Matlab,  as  an  example  of  an  engineering  tool?  Alternatively,  the  course  could  be  structured  to  teach  algorithmic  thought  processes.  No  one  way  is  best  and  any  computing  course  should  address  all  three  to  some  extent.  The  lecture-­‐homework-­‐test  progression  may  be  excellent  at  addressing  the  applied  math  objective,  while  short  programming  assignments  may  address  the  learning  of  syntax.  Here  we  present  a  semester-­‐long  project  that  aims  to  address  algorithmic  thinking.      The  semester-­‐long  project  presented  below  is  incorporated  into  half-­‐credit,  Junior-­‐level  biomedical  engineering  course.  Students  are  exposed  to  more  advanced  applied  math  in  lectures,  and  learn  the  syntax  of  matlab  through  short  programming  assignments.  Although  writing  short  scripts  can  allow  students  to  practice  simple  algorithm  development,  the  semester-­‐long  project  provides  an  opportunity  to  focus  on  deeper  and  more  complex  algorithmic  thinking.  As  a  team-­‐based  project  could  too  easily  allow  one  person  to  perform  the  high-­‐level  algorithmic  development  and  farm  out  the  writing  of  functions  to  other  team  members,  each  student  completes  their  own  project.  There  are  three  guiding  principles  behind  the  projects:  1)  To  learn  to  program  beyond  the  most  basic  level  a  student  must  write  a  complex  section  of  code  that  requires  planning,  iteration,  encapsulation  and  documentation,  2)  The  project  must  demonstrate  that  the  student  can  move  from  “Idea  to  Code”  (a  phrase  that  is  mentioned  in  class  at  least  once  a  week)  and  3)  Programming  a  calculator  or  excel  only  covers  the  simple  aspects  of  algorithmic  thinking.      The  project  is  broken  into  7  assignments.  First,  an  initial  one-­‐page  abstract  outlines  at  least  three  biomedically  relevant  projects.  A  meeting  with  the  instructor  guides  each  student  toward  one  idea  in  particular.  Second,  a  five-­‐minute  class  presentation  gives  an  overview  of  the  background  and  general  data  structures  that  will  be  used.  Third,  a  written  description  of  a  parametric  study  is  submitted  along  with  an  explanation  of  a  single  summary  graphic  to  display  the  results.  Fourth,  a  meeting  with  the  instructor  is  held,  at  which  time  the  student  must  show  a  draft  of  their  code,  a  demonstration  of  basic  functionality,  and  a  plan  for  completing  the  project.  All  code  must  contain  matrix-­‐vector  operations,  loops,  functions,  conditional  logic,  data  output  and  graphical  output.  Fifth,  a  one  page  technical  abstract  is  submitted  and  included  in  a  class  booklet.  Sixth,  a  public  10  minute  presentation  is  delivered  with  a  focus  on  results  and  conclusions.  Seventh  an  electronic  submission  consists  of  all  code,  written  and  presented  work  as  well  as  a  one  page  users  manual.        A  full  conference  proceeding  will  include  outcomes  assessment,  student  and  faculty  comments,  suggested  improvements  and  adaptations  and  ABET  assessment  measures.    
AU  - Joe Tranquillo
CY  - Vancouver, BC
DA  - 2011/06/26
PB  - ASEE Conferences
TI  - A Semester-Long Student-Driven Computational Project
UR  - https://strategy.asee.org/17380
DO  - 10.18260/1-2--17380
ER  -