HPC Technologies

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HPC Technologies PreService Teacher Prep
Overlap?Post Evaluation Thoughts

• Kris Stewart
• Ilya Zaslavsky
• San Diego State University
• NPACI Ed Center on Computational Science
  Engineering

stewart_at_sdsu.edu www.edcenter.sdsu.edu
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Outline of SITE2000 Talk

• Background
• Projects and Evaluations
• Strategies We Have Developed
• Lessons Learned
• STEP
• EC/CSE
• Building Infrastructure through Community
• Will it count? How?

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Background for SITE2000 talk

• What is Computational Science Engineering?
• What is NPACI? National Partnership for Advanced
  Computational Infrastructure
• What is EOT-PACI?
• What is the Ed Center on Computational Science
  Engineering EC/CSE?

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What is Computational Science?Science
Simulation/Modeling Computer Science

Science Discipline Physics, Chemistry, Biology,
etc.
Applied Mathematics Numerical Analysis, Modeling,
Simulation
Computer Science Hardware/Software
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Computational Science is Teamwork

Teamwork and Collaboration
Science Discipline Physics, Chemistry, Biology,
etc.
Computer Science Hardware/Software
Applied Mathematics Numerical Analysis, Modeling,
Simulation
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NPACI Advancing the Computational Infrastructure
NPACI Advancing the Computational Infrastructure

• Resources -- Todays Digital Laboratory
• High-performance computing available today to the
  academic community
• Develop and Deploy
• Technology and application collaborations to push
  the capabilities of tomorrows digital laboratory
• Use and Apply
• Computational scientists applying enhanced
  capabilities to achieve new scientific results
• Disseminate and Incorporate
• Incorporating technologies into the digital
  laboratory and disseminating them for use in new
  communities

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NPACI Sources of Information
NPACI Sources of Information
NPACI Partnership Report enVision quarterly
science magazine, especially June99The
Importance of Science Literacy in a Computing
World, Sid Karin www.npaci.edu/envision/v15.2/dir
ector.html Online biweekly electronic
publication, www.npaci.edu/online/ www.npaci.edu

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Mission of EOT-PACI

• The mission of EOT-PACI is to develop human
  resources through the innovative use of emerging
  information technologies in order to understand
  and solve problems in education, science,
  business, government, and society.

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EOT-PACI Education Projects
Goal Support a national level systemic impact
on CSE education (k-12, undergrad,
grad/training, informal science)
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EOT-PACI some remarkable projects

• Chickscope
• students watch embryo maturing using magnetic
  resonance imaging (MRI) over the Web
• Chemviz
• visualization tools and curriculum for
  computational chemistry (quantum chemistry
  computations, web crystallographic databases,
  etc.)
• The WHY files
• explanation of science behind the news (NISE)
• Biology Workbench
• collection of computational biology tools and
  databases
• Maryland Virtual High School
• Core models in the K12 classroom
• Sociology Workbench
• Online tools for survey data analysis, e.g.
  student evaluations

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EOT-PACI Learning Technologies
Goal Develop, apply, and assess computational
tools that enhance learning
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EOT-PACI Access Inclusion
Goal Increase participation and success of
women, minorities and people with disabilities
in CSE and in PACI
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The STEP Project, and its Evaluation

• Goal Introduce in-service science teachers to
  computational science (NSF support 1993-97)
• Lessons learned
• Teachers need to be convinced that new
  technologies significantly improve student
  learning
• Institutional support required for program to be
  sustainable (and teachers need to be aware of
  this support)
• Continuous monitoring through interviews,
  surveys, discussions
• Included in Smithsonian permanent collection!

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The Ed Center Project and its Evaluation

• Goal incorporate computational science
  techniques in undergraduate curricula
• Differences from STEP target audience,
  institutional arrangements
• Methods and Strategies
• Faculty Fellows
• Workshops, presentations, in-house projects,
  trying out new approaches in own teaching, tools
  development
• Computational Science Olympics (curriculum from
  the bottom-up!!)
• Surveys, continuous assessment of faculty
  involvement and learning outcomes
• Evaluated by the LEAD Center in 1998-99

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Introducing the EC/CSE
The mission of the Ed Center on Computational
Science and Engineering? www.edcenter.sdsu.edu Who
are the people involved? www.edcenter.sdsu.edu/st
aff Some of our projects www.edcenter.sdsu.edu/pr
ojects/ Some of our activities
www.edcenter.sdsu.edu/news/ Some resources
www.edcenter.sdsu.edu/repository
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Undergraduate Faculty A Tough Target Group

• Obstacles lack of time, tenure and review
  considerations, lack of awareness about available
  technologies
• Undergraduate faculty
• ¾ have used WWW often or sometimes (1997), but
  not in the classroom (only 18 - 1998)
• The gap between those NEVER using computers in
  the classroom, and those using them OFTEN, is the
  largest for untenured faculty, increasing towards
  tenure review
• Only 12 of surveyed faculty saw themselves as
  having a use for HPC applications in courses
  (higher for Sciences and Engineering)
• 11 of faculty have students working with
  computer models OFTEN

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Using computers in the classroom versus number of
years as a faculty member (1997 Faculty Survey)
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Students Using Computers in the Classroom (1997
Faculty Survey)
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Strategies for Building Faculty Community

• Reliance on most enthusiastic and technically
  advanced instructors who are already using
  computing and modeling in classes
• The Faculty Fellows program
• Stakeholders
• College Deans - Specific support
• Faculty - Compensation, and acknowledgement, of
  the value of the faculty members contribution
• Benefits
• College
• Department (Faculty Fellows as discipline-specific
  spokespersons for EC/CSE)
• Faculty (as individuals)
• Ed Center on Computational Science and
  Engineering
• Building a special infrastructure for curriculum
  transformation human, institutional, technical
  is a requirement for successful introduction of
  advanced techniques (since they are more
  demanding on faculty time and efforts)
• The problems and strategies are not that much
  different from STEP!!

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Faculty Fellows during 1998-2000

• Faculty Fellows representing four departments
  from four colleges Geological Sciences,
  Geography, Computer Engineering, Business
  Information Systems
• Bi-weekly meetings at the Ed Center
• Faculty Fellows as ambassadors of computational
  science
• Partnership with LEAD for evaluation during
  1998-99
• Follow-on Activities (Susan Millar, LEAD)
• CATS (Classroom Assessment Techniques)
• FLAG (Field-tested Learning Assessment Guide)
• SALG (Student Assessment of Learning Gains)

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More Strategies

• Trying the new approaches in our own teaching
• Teaching the Supercomputer class with group-based
  problem-solving environments
• Real-time distance teaching with Web-based
  collaborative software (featured as Microsoft
  Case Study in Higher Ed.)
• Development of Sociology Workbench, a free
  on-line survey data analysis system that can be
  used for evaluation of student outcomes and other
  surveys

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Channels for Influencing Pre-Service Teacher
Preparation

• Use of advanced computing modules in general ed
  courses (e.g. Geol 303 Natural Hazards)
• Cooperation with College of Education faculty and
  students, esp. in Education Technology focus on
  experimentation with new technologies in
  classroom setting
• Computational Science Olympics supporting the
  bottom-up development of computational science
  curricula
• Providing on-line assessment technologies
• Sociology Workbench http//edcenter.sdsu.edu

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SWB Convenient Tool to Learn from Student Survey
Data

• Online tool for standard public data sets or
  your own data set http//edcenter.sdsu.edu
• Small Sample, therefore only useful as feedback
  for the instructor
• Can be used with forms interface directly into
  SWB format, as in June 99 CSU Faculty Workshop

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SWB as Analysis ToolView Student Comments (text)

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SWB as Analysis ToolIsolate on Specific Survey
Response

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SWB as Analysis ToolExplain the Response on
Learning with doing more

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SWB as Analysis ToolExplain learning with
active participation
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Lessons Learned

• Institutional support required for program to be
  sustainable
• Individual reform-ready faculty is focus for
  support
• Infrastructure
• Build a Synergistic Environment (across
  disciplines) for Faculty
• Continuous monitoring through interviews,
  surveys, discussions

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Whats Next

• The approaches we described proved useful for two
  target audiences. We believe that the strategies
  and lessons learned can be extrapolated in a
  targeted effort to incorporate computational
  science technologies in pre-service teacher
  preparation
• This may be a funding opportunity?
• We will be happy to contribute our knowledge and
  share experiences

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References SITE2000

• User-Friendly Handbook for Project Evaluation
  Science, Mathematics, Engineering and Technology
  Education, NSF 93-152 www.ehr.nsf.gov/EHR/RED/EVAL
  /handbook/handbook.htm
• Sid Karin The Importance of Science Literacy in
  a Computing World (see enVision Science Magazine,
  V.15 No. 2
• Smithsonian Institution STEP is in the Archive
  for 1996, Education Academia San Diego
  http//innovate.si.edu/
• K. Stewart I. Zaslavsky, Ten Grand
  Challenges, Supercomputing 98 Orlando FL SC98
  Conference Paper
• J. Foertsch B. Alexander, Integrating HPC into
  the Undergraduate Curriculum, report by LEAD
  Center June 1999 http//www.cae.wisc.edu/lead/pag
  es/products/eot-paci.pdf