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InfoTech as Gateway to Undergrad Computational Science building assessment into the curriculum

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SIAM02 Philadelphia MS 58 Undergrad Programs in CSE Rm413/Level4 ... SIAM02 Philadelphia MS 58 Undergrad Programs in CSE Rm413/Level4. 1998/99 Assessment by LEAD ... – PowerPoint PPT presentation

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Title: InfoTech as Gateway to Undergrad Computational Science building assessment into the curriculum


1
InfoTech as Gateway to Undergrad Computational
Sciencebuilding assessment into the curriculum
  • Kris Stewart
  • San Diego State University
  • NPACI/CSU Ed Center on CSE
  • stewart_at_sdsu.edu
  • www.edcenter.sdsu.edu

2
Outline
  • What is InfoTech (to me and to others)?
  • What is Computational Science?
  • Assessment
  • - formative can be simple
  • - summative can build on formative and be simple

3
What is Information Technology?
  • To me
  • Using web-enabled tools to assess student
    attitudes
  • Writing code to solve problems from science
  • To others (peers outside CS, taxpayers supporting
    CSU, students)
  • Using MS Word, Excel, Access
  • Email
  • Creating Web Page
  • Performing Google Search

4
What is Computational Science?

Teamwork and Collaboration
Science Discipline Biology, Physics, Chemistry,
etc.
Computer Science Hardware/Software
Applied Mathematics Numerical Analysis, Modeling,
Simulation
5
Who is Doing Computational Science?
  • NPACI is The National Partnership for Advanced
    Computational Infrastructure
  • http//www.npaci.edu/
  • NPACI is a partnership of over 40 institutions in
    the US and more worldwide
  • http//www.npaci.edu/Partners/

6
The PACI Partnerships
6
7
NPACI-NCSA/Alliance Partnerships are NSF Programs
8
California Networking the State all 3 college
tiers and schools
9
EOT PACI
9
  • 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.
    http//www.eot.org/

10
Education
10
Goal Support a national level systemic impact
on CSE education (k-12, undergrad,
grad/training, informal science)
11
Access Inclusion
11
Goal Increase participation and success of
women, minorities and people with disabilities
in CSE and in PACI
12
Education Center on Computational Science
Engineering
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Mission
  • Foster the incorporation of high performance
    research
  • tools for scientific investigation into the
    undergraduate
  • curriculum to better prepare learners for
    post-Baccalaureate
  • activities where
  • Collaborative, interdisciplinary teams,
  • Sophisticated computer tools and
  • Effective communication among the team members
    and with others
  • are used in research and problem solving.

13
NSF/EHRNational Science Foundation/Education and
Human Resources Directoratewww.ehr.nsf.gov/EHR/
RED/EVAL/handbook/handbook.htm
LEADAssessment and Evaluation1998 Formative for
the EC/CSEhttp//www.cae.wisc.edu/lead/pages/pr
oduts/eot-paci.pdf
14
Evaluation and Assessment of Classroom Practice
  • Student Surveys - Resources for proven
    instruments from College Level 1
    http//www.wcer.wisc.edu/nise/cl1/
  • National Institute for Science Education (NISE)
  • Online sample survey you can easily adapt
  • Field Tested Assessment Guide (FLAG)
  • Classroom Assessment Techniques (CAT)
  • Student Assessment of Learning Gains (SALG)
  • Excellent collection of case studies
  • Learning Through Technology

15
UCES Paradigm(thanks Tom Marchioro and the DOE
crew, 1994)
My previous exposure to assessment
16
1998/99 Assessment by LEAD
Assessment as a Collaboration
  • Background
  • Workshop in Wisconsin April 1997 to learn
    about assessment and make it real
  • NPACI starts 1 October97
  • EC/CSE requested assessment for 1998
  • Preparation for SDSU Campus Visit by Baine
    Julie
  • Discussions at SC98
  • Email to SDSU faculty gather attitudes

17
Grand Challenges for HPC (Stewart Zaslavsky,
SC98)
  • Faculty system of rewards does not encourage
    teaching innovations
  • Lack of awareness of HPC technologies already
    used in research or teaching for different
    fields
  • Faculty students unaware of benefits and
    accomplishments of HPC
  • HPC technologies considered too
    complex/inaccessible for undergraduate
    instruction
  • Sequential HPC-related curricula is absent
  • Curricula using very large data sets not widely
    available
  • Adjust to different learning styles when material
    is complex
  • Variety of platforms/software leads to fragmented
    curricula
  • School administration/support staff not ready for
    HPC
  • Specs of computers and networks below user
    expectations
  • We had been thinking about this (based on April
    97 LEAD Workshop in WI)

18
Assessment not just requirement
  • Rather, found to be
  • vital tool to assist in clarifying student and
    faculty needs
  • improve prioritization skills
  • validation of focus on human factors to integrate
    HPC (modeling visualization) into undergrad
    curriculum

19
Student Assessment of Learning Gains(SALG)
  • Four Main Questions
  • How much each aspect of the class helped your
    students learn
  • How much students gained in understanding,
    ability, subject appreciation and confidence
  • How much the course added to particular skills
  • How well student think they will retain material
    learned
  • http//www.wcer.wisc.edu/nise/cl1

20
Sociology Workbench (SWB)http//www.edcenter.sdsu
.edu/swb/
  • Online analysis tool for categorical data.

21
Sociology Workbench
  • Student Surveys - Need additional tools for
    instructor to examine results and DISCOVER
    RULES
  • Given an outcome, B, what factors, A, contribute
    to explaining it.
  • If A Then B or If A -gt B

22
SWB Functions
  • Analyzing existing surveys user-defined or built
    in
  • Distribution tables
  • Tables of rules
  • Secondary variables
  • Creating new surveys
  • Convert survey data from other formats, or
    capture form input, place on a public FTP,
    register to SWB

23
SWB Convenient Tool to Learn from Student Survey
Data
  • Online tool for standard public data sets or
    your own data set http//www.edcenter.sdsu.edu/sw
    b/
  • Small Sample, therefore only useful as feedback
    for the instructor
  • Has been used with forms interface directly
    into SWB format, as in July 00 Bioinformatics in
    the Biology Curriculum with Biology Workbench
  • Can now be used with Automatic Survey Creation
    Process (ASCP)

24
SWB as Analysis ToolView Student Comments (text)

25
SWB as Analysis ToolIsolate on Specific Survey
Response

26
What do I want to Explain with SWB?

Course had an initial, individual computational
experimentand a group computational experiment
later in the semester. More than half the
students indicated they learned more in the
laterproject. I wanted to explore the
characteristics (If A) of thosewho recognized
they learned more in a group.
27
SWB as Analysis ToolExplain learning with
active participation
Not surprising
28
Evaluation and Assessment of Classroom Practice
  • Automatic Survey Creation Process (ASCP)
  • Survey Student Attitudes (pre and post)
  • - Need a compatible tool for instructor to create
    survey instruments
  • - Need a convenient mechanism to administer
    surveys and gather data
  • Sociology WorkBench (SWB)
  • Online categorical data analysis tool - developed
    by team of undergraduate computer science majors
    employed by the ECCSE

29
Whats Next?
  • Keck Undergrad Computational Science Education
    Consortium (KUCSEC)
  • Capital University, Wofford College, San Diego
    State University, San Diego Supercomputer Center,
    Pomona College, Cal Poly Pomona, and more each
    developing an undergrad computational science
    module
  • Mine is performance of MPI with assessment of
    student learning goals and accomplishments

30
SDSC Refines Focus 5 Strategic Program Areas
  • Integrative BiosciencesPhil Bourne, lead
  • Data and Knowledge SystemsChaitan Baru and Phil
    Andrews, lead
  • Grid and Cluster Computing (TeraGrid more)Phil
    Papadopoulos, lead
  • High-End ComputingMike Vildibill, lead
  • Computational SciencePeter Taylor, lead

31
Updates for CS 575 SupercomputingSpring 2003
Based on IBM SP2 Blue Horizon and Sun E10K
Workshops, will incorporate MPI
http//www.npaci.edu/enVision/v16.1/
32
Subscribe to the Online Magazine and Envision
Quarterly
33
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