THINKING LIKE A SCIENTIST

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THINKING LIKE A SCIENTIST

• Principal Investigator
• Wendy M. Williams
• Cornell University
• Graduate Student Collaborators
• Paul Papierno, David Biek, Matthew Makel, David
  Battin, Kim Kopko, Loren Frankel

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The Problem

• Minority, female, and low-SES youth tend not to
  pursue science education and careers

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Observations about Women in STEM Education and
Careers

• Women comprise less than 25 of all science and
  engineering jobs in govt and private sectors
• In select university science and engineering
  depts., only 15 of tenured and tenure-track
  professors are women

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Female share of SE graduate students, by field
1991 and 2001
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Employed SE doctorate holders, by sexand years
since doctorate 2001
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SE bachelors degrees awarded per 1,000 U.S.
citizens and permanent residents 2024 years old,
by race/ethnicity 19892000
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Minority undergraduate engineering students,by
race/ethnicity 19902002
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Minority share of SE masters degrees awarded to
U.S. citizens and permanent residents,by
race/ethnicity 19892001
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Employed SE doctorate-holders, by race/ethnicity
and field of doctorate 2001
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Long Reach of Family S.E.S.

• Looking at the student body of the top 126
  colleges/universities in the U.S.
• Only 10 of students come from the bottom 50 of
  the income distribution
• Only 3 of students come from the bottom 25 of
  the income distribution
• We need to reach the youth left behind.

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Concept/Goals

• Minority and low-SES youth tend not to pursue
  science education and careers
• Traditional content-based science education
  (e.g., Mendel, Periodic Table, plate tectonics)
  seems abstract to these students they turn off
• By linking science to everyday decisions that
  affect their lives, we can teach these youth to
  think like scientists and show them the value of
  science in their daily lives

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IDEA SUMMARY

• Most formal science instruction focuses on
  content. (examples Gregor Mendel and his peas
  Periodic Table of Elements)
• Content is quickly forgotten
• Even if remembered, knowledge derived from
  content-based instruction is rarely transferred
  to new problems/situations
• For a few fortunate, motivated, talented
  students, taught by terrific teachers, underlying
  principles are first extracted from content-based
  instruction, then learned, remembered, and
  applied broadly
• BUT what about the vast majority of students not
  in this group?

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One SolutionThinking Like A Scientist

• Generate topics relevant to everyday lives of
  low-SES/minority youth young adults
• Choose exciting topics for which a recent
  meta-analysis exists in major journal (scientific
  consensus)
• Develop education-outreach materials with catchy
  design that are easy to use
• Link science to daily life
• Discuss science careers

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Ultimate Audience

• Low-SES and minority youth/young adults in high
  schools, technical schools, and community
  colleges across the U.S.
• Same population in community centers, religious
  organizations, adult-education venues

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DESCRIPTION OF PROGRAM

• Part 1 THEMES
• 1. Ask What is science? (Scientific way of
  knowing.)
• 2. Define the problem see many sides. (Define,
  consider, and argue multiple sides of an issue.)
• 3. Distinguish fact from opinion Know what
  constitutes evidence.
• 4. Weigh evidence and make decisions.
• 5. Move from science to society. (From knowing
  to doing.)
• 6. Revisit, reflect, re-evaluate, and review.

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DESCRIPTION OF PROGRAM

• Part 2 CONTENTS
• Major journalsmeta-analyses with consensus
• Vetting of topics
• Sample topics
• Videogames
• Smoking
• Depression
• John-Joan (gender re-assignment)

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DESCRIPTION OF PROGRAM

• Part 3 ORGANIZATION AND LAYOUT
• Themes
• Activities (e.g., Think Write)
• Careers
• References and key words
• Quizzes
• Visual Impact (color blocks)
• Ease of Use (spiral notebooks)

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EVALUATION

• Need for comprehensive evaluation with
  pretest-posttest design including
  demographically-matched control groups
• Comprehensive evaluation not possible in context
  of community colleges, religious organizations,
  and adult-education venues
• Comprehensive evaluation conducted in high
  schools offering large samples matching target
  demographic profile, plus extensive time period
  for assessment and instruction with TLAS
  materials

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IMPLEMENTATION

• Phase OnePilots
• (Taught by Graduate Students)
• Summer 2002 Cornell Cooperative Extension, 4-H
  residential Youth Camp--Camp Wyomoco, Warsaw,
  Wyoming County, New York David Biek piloted
  several preliminary lessons.
• Fall 2002 Edison Technical High School,
  Rochester, New York David Biek piloted CIRC
  lessons in a remedial science classroom of 9th
  and 10th graders, 75 African American and 25
  Latino.

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Phase OnePilots

• Spring 2003
• January, 2003, East High School, Rochester, New
  York--one class taught one in-depth, detailed
  CIRC lesson per week for ten weeks remedial
  science class with 80 African American, 15
  Latino, 5 White/Other students.
• February, 2003, Franklin High School, Rochester,
  New York--one Biotechnology class taught one
  lesson per week for ten weeks, inner-city magnet
  school juniors and seniors interested in
  science 60 African American, 30 Latino, 10
  White.

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Phase OnePilots

• Summer 2003 Cornell Summer Science Seminar
  taught by graduate students.
• also taught summers of 2004, 2005, 2006
  scheduled for 2007.

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IMPLEMENTATION

• Phase 2Expanded Pilot, Spring 2004
• (Taught by Classroom Teachers)
• Multiple at-risk populations, multiple sites,
  program taught by classroom teachers
• Low-SES and middle-SES White, Spencer-Van Etten
  and Candor High Schools, NY (n290 e190,
  c100).
• Low-SES Native American Reservation High Schools,
  Minnesota and North Dakota (n80 e55, c25).

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IMPLEMENTATION

• Phase 2Expanded Pilot
• Focus Group 7th and 8th graders at Catholic
  School, Ithaca, NY low- and middle-SES Whites
  (n50 e24, c26).
• Taught by research team
• Every class videotaped for microanalysis of
  development of scientific reasoning skills over
  term.
• Assessed in one-on-one setting, assessment read
  aloud to students, students verbal answers
  written down by experimenters.

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IMPLEMENTATION

• Phase 2Expanded Pilot
• 100 African American, public assistance
  population of Chicago High Schoolers
• 5-week summer program for inner-city youth
• Taught by University of Chicago graduate students

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Phase 3Intensive National Pilot EXPERIMENTAL
DESIGN

• Overall n 206 (e 123, c 83).
• Controls matched on demographics, age, grade,
  background, geographical area, curriculum.
• Assessment administered late January (pretest)
  and early June (posttest) to all experimental and
  control students.

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Fort Totten
Ballston Spa
Waterloo
Marion
Pella
Scottsdale
Hoover
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ASSESSMENT EVALUATION

• OVERVIEWKEY GOALS
• How to measure scientific reasoning,
  independently of content of our program.
• How to be fair to controls.
• How to fit within confines of one class period40
  minutes maximum.
• How to measure ability to transfer what has been
  learned to real-world contexts to answer
  real-world questions.

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ASSESSMENT EVALUATION

• OVERVIEWOUR MEASURE
• 3 types of questions
• general, independent examples of scientific
  reasoning
• complex, interdependent examples of scientific
  reasoning
• attitudes about science and school

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ASSESSMENT EVALUATION

• SAMPLE QUESTIONS--type 1,independent judgments
• Jed the farmer plants two different types of corn
  next to each other in the same field to see which
  will grow faster. Is Jed behaving scientifically?
  (Definitely Not, Probably Not, Maybe, Probably,
  Definitely) Why?
• Loris friend tells Lori that she should not take
  a job at the local gas station because another
  student who took the same job last year failed
  math. Is her friend behaving scientifically? Why?

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ASSESSMENT EVALUATION

• SAMPLE QUESTIONStype 1,independent judgments
• Colleen is planning to buy a new camera. Before
  she buys one, Colleen checks all the local camera
  stores to see which has the best selection and
  price in order to find a camera that best fits
  her needs. Is Colleen behaving scientifically?
  Why?
• Mike, who is 17, decides to stop drinking soda.
  Six months later, Mike realizes he has stopped
  growing. Because he wants to start growing again,
  Mike begins drinking soda again. Is Mike behaving
  scientifically? Why?

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ASSESSMENT EVALUATION

• SAMPLE QUESTIONS, type 2
• complex, interdependent judgments
• Carlos has a sore knee. It hurts whenever he
  plays sports. He is thinking about trying a
  special knee brace. Carlos wants to make a
  decision based on science. How important should
  each of the following pieces of information be to
  Carlos when he makes his decision? (Not
  Important, A Little Important, Somewhat
  Important, Very Important, Extremely Important)

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• Carlos thinks the brace looks stupid.
• A television commercial for the brace claims it
  always works.
• His doctor said 8 out of 10 people who use the
  brace feel better.
• His neighbor tried the brace and it did not work.
• Carloss coach said the brace helped three other
  boys on the team.
• If Carlos has all of the above information and if
  he wants to make a decision based on science,
  should he wear the brace? (Definitely Not,
  Probably Not, Maybe, Probably, Definitely)

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ASSESSMENT EVALUATION

• SAMPLE QUESTIONS, type 3Attitudes about School
  Science
• SCALE Definitely Not, Probably Not, Maybe,
  Probably, Definitely
• In general, I like school.
• I plan on attending college after high school.
• I think science is a boring class.
• I am interested in a career in science.
• I think scientists are interested in real-world
  problems.
• I talk about science with my friends when Im
  outside of school.
• I think women can be good scientists.
• I trust the ideas that scientists come up with.
• My friends think scientists are nerds.
• There are a lot of science-related careers
  available for me to choose from.
• My favorite subject is
• My least favorite subject is

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ASSESSMENT EVALUATION

• RECAP TYPES OF DATA COLLECTED
• General, independent science-reasoning questions
  (numerical answers plus longhand explanations)
• Complex, interdependent science-reasoning
  questions (numerical answers plus longhand
  explanations)
• Evaluating an experimentpros and cons
• Attitudes about science and schooling
• Demographic information

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ASSESSMENT EVALUATION

• SCORING ISSUES APPROACHES
• Use of expert exemplarseminent scientists
  provided correct answers
• Rating student responses--Multiple raters blind
  to student group membership (TLAS vs. control)
  answers randomly mixed

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THINKING LIKE A SCIENTIST IOWA GRADE 12
IMPLEMENTATION (n 43 e 20, c 23 26 girls,
17 boys) Wendy M. Williams Paul B. Papierno
KEY RED General
independent scientific
reasoning BLUE Interdependent
judgments GREEN Experimental Eval - Cons
PINK Experimental Eval - Pros
? Experimental
? Control
POSTTEST
PRETEST
F(1,40) 4.25, p.046 F(1,40) 27.31,
plt.0001 F(1,39) 4.51, p.040 F(1,36)
2.76, p.105 significant difference
at pretest
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OBSTACLES CHALLENGES

• Controlling the uncontrollable
• chaos of real classrooms
• teacher differences
• selection biases
• Gaining access to at-risk populations
• not available near Ithaca elsewhere tough to
  oversee
• Challenges in working with Native Americans
• trouble getting controls
• Measuring ability to think like a scientist
• Must be fair to controls
• No longer than 40 minutes
• Issues construct validity scoring
  protocols/expert exemplars

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OBSTACLES CHALLENGES, TAKE TWO

• Tyranny of unanticipated snags
• TRAGIC LOSS OF BELOVED GRANT OFFICER AND GRADUATE
  STUDENT
• MIDDLE-SCHOOL STUDENTS--OR MISCREANTS?
• NOSEY NEWSPAPER REPORTERS
• IDENTITY DISSOCIATION (DR. MILLER INCIDENT)

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