Welcome and
Challenge
Pat Marsteller
BQ Faculty Workshop
June 2013
Cases, Data, Simulations, Tools
We use Math Everyday!
 http://www.youtube.com/watch?v=TaAftRgptkQ
Reports, Reports, Reports
 Using Data in Undergraduate Science
Classrooms (2002)
 Shaping the Future: New Expectations for
Undergraduate Education in Science,
Mathematics, Engineering, and Technology (NSF
96-139)
 Shaping the Future Volume II: Perspectives on
Undergraduate Education in Science,
Mathematics, Engineering, and Technology NSF
98-128
NRC Board
on Life Sciences
(2003)
NRC
Board on
Life
Sciences
(2009).
MAA
(2004)
MAA
(2005)
American Association for the
Advancement of Science &
National Science Foundation
(2011)
Association of American
Medical Colleges &
Howard Hughes Medical
Institute
(2009)
College Board (2011)
Bio 2010 Recommendations
Biology education should be interdisciplinary with a strong
emphasis on developing quantitative skills.
Laboratory courses should focus on developing critical
thinking skills.
Students should pursue independent research.
Teaching methods should be examined.
Resources must be adequate.
Faculty should be rewarded.
Core competencies V&C
 Fundamental Understanding of the Process of science
 Quantitative competency and the ability to interpret data
 Basic computational skills
 The ability to see connections between biology and other
disciplines
 Competency in communication and collaboration
 Understanding of how biology is practiced in a societal context
with potential to address critical issues in society and global
issues
National Research Council 2000
National Research Council 2003
9
What are we waiting for?
The collaborative investigation of cases (and
problem spaces) provides opportunities for
learners to share and question what they
already know with their peers.
Learners come “to formal education with a range of
prior knowledge, skills, beliefs and concepts” which
affect:
• what learners notice,
• how they reason and solve problems,
• how they remember (p.10).
How People Learn: Brain, Mind, Experience and School.
National Research Council, National Academy Press, 2000.
Effective Learning and Teaching
 Quality, not Quantity
 Connects New Knowledge to Old
 Constructive, restructures old frameworks based on new
knowledge
 Concrete to Abstract: embed specifics in organized,
coherent frameworks
 Relevant and Real
 Active
 How People Learn: Brain, Mind, Experience and School.
National Research Council, 2000
AP Redesign
Biology, Chemistry, Environmental Science, Physics (2012-16)
Evidence of Learning
• Big Ideas / Unifying
Themes
• Enduring Understandings
• Competencies
• Evidence Models
(Formative Assessments)
•
The student can use representations
and models to communicate scientific
phenomena and solve scientific
problems.
•
The student can use mathematics
appropriately
•
The student can engage in scientific
questioning
•
The student can perform data analysis
and evaluation of evidence
•
The student can work with scientific
explanations and theories
•
The student is able to transfer
knowledge across various scales,
concepts, and representations in and
across domains
Next Generation Science Standards
 Investigate, build models
& theories
 Includes engineering
practices
 Crosscutting patterns,
scale, cause & effect etc
 Core ideas; key concepts,
broad import, relate to
student interests,
learnable across grade
levels
http://nextgenscience.org/
I repeat
What are we waiting for?
Cases, Simulations, Games & Problem Spaces Can Integrate
Core Concepts and Competencies throughout the Curriculum
 Introduce science process skills early and reinforce in all courses
 Learning goals focus on core concepts & assessments align with
learning goals
 Real world examples and relevance
 Develop lifelong science learning competencies
 Fewer concepts in greater depth
 Stimulate curiosity about the natural world
 Help scientists demonstrate passion for the discipline and delight in
sharing passion with students
What do you want your learners to do?
 Learn specific disciplinary content?
 Use interdisciplinary skills to answer their questions?
 Develop scientific data literacy?
 Engage in collaborative problem solving?
 Relate the disciplinary content to their own lives?
 Learn how to use tools such as BLAST?
 Navigate the online environment?
 Make evidence-based decisions?
 Develop an appreciation for scientific thinking?
 Discover their strengths and weaknesses as learners?
Shouldn’t all Students Understand the Evidence
Behind the Headlines?
 Wider Warnings after 3rd hanta virus death
 Corporations Slow to Act on Climate Change
 Earlier Mass Extinction for Most of Marine Life
 New York Is Lagging as Seas and Risks Rise, Critics Warn
 Ovarian Cancer Screenings Are Not Effective, Panel Says
 Literacy and the Population Problem
And Know about Big Questions that remain?
 http://www.sciencemag.org/site/feature/misc/webfeat/125th/
Why we care !
 we have recognized the
importance quantitative
biology in the
undergraduate curriculum
 we want to identify and
share best practices and
resources
 we want to work together
to create new materials
 establish a community of
educators who will
continue advancing this
effort for many years to
come
 properly done,
quantitative methods must
be part of the first biology
courses an undergrad takes
(and biological concepts in
early mathematical
courses,too)
To do list
 efforts must be scalable
and sustainable (from
fiscal and human resource
perspectives)
 activities should count
toward graduation
 must included research or
research-like experiences
 We must make efforts to
push the adoption curve
forward
 make our work visible to
those outside this
community
 persuade others that our
innovations work prepares
students (assessment!)
 give others the tools and
support that will guarantee
their success
Additional Challenges
 Increasing STEM
undergraduate degree
production
 Increasing participation of
traditionally
underrepresented groups
 Involve pre-K thru 12 and
community college
teachers in “the
revolution”
Where are we now?
 General biology texts:

have less than 3 equations
 Rarely have quantitative
data
 Graph complexity primarily
linear
 No quantitative problems
Where do we need to go?
 Biology education that
uses calculus, discrete
mathematics, &
statistics
 Quantitative problem
solving throughout
 Modeling top down,
bottom up, nonlinear
feedback
 Deal with complexity of
terabytes of data per
day
John Jungck 2007 and every time I’ve seen him since
2002
Central role of problem-solving environments:
 Powerful tools that develop professional skills
 Interactive
 Open-ended
 Challenging
 Research-related
 Depth of analysis
 Empowering
 Lend themselves to collaborative learning
Goals of a Bioscience Curriculum
Students should “be conversant not only with the
language of biology but also with the languages of
mathematics, computation, and the physical
sciences”
Bialek & Botstein 2004, Science 303:788
Institutionalizing innovations in science
education requires
 Support from faculty
 Support from administration
 Recognition through competitive grant funding
and national awards
 Dissemination through articles, books,
workshops, and national meetings
– Joint Meeting of HHMI Program Directors and HHMI Professors, 2006
The important thing in science is not so much to obtain
new facts as to discover new ways of thinking about
them.
Sir William Bragg (1862 - 1942)
Go forth and create new problem spaces!
Join us for the HHMI Workshop, too!