Taking a scientific approach to
undergraduate* science (chemistry) education
(as opposed to approaching as art form or random trial & error)
Carl Wieman
Physics and Graduate School of Education
Stanford University
Based on the work of many people, some from my 20+ yrs in
undergrad sci ed research (including chemistry)
* applies to all levels but with some caveats
How to optimize chemistry education in lieu of increasing
knowledge and needs?
New stuff and new skills to learn, more specialization–
Have to fit more in!
What should the curriculum look like?
Before any discussion of curriculum
What fraction of the material you learned in
classes do you use?
What fraction of the material you use did
you learn in classes?
So what is important for student to learn?
What should students learn?
The basic elements of chemistry expertise
(how to think more like chemist)
I. Nature of expertise and how it is learned
II. Implementation in science classroom and data on effectiveness
III. Some particular challenges in chemistry for improving
Major advances in past few decades
 Guiding principles for achieving learning
College sci
I. Expertise research*
historians, scientists, chess players, doctors,...
Expert competence =
• factual knowledge
• Mental organizational framework  retrieval and application
or ?
patterns, relationships,
scientific concepts,
• Ability to monitor own thinking and learning
New ways of thinking-- everyone requires MANY hours of
intense practice to develop.
Brain changed
*Cambridge Handbook on Expertise and Expert Performance
Learning expertise*
(any level)--
Challenging but doable tasks/questions
Practice all the elements of expertise with
feedback and reflection. Motivation critical!
• conceptual and mental models + selection criteria
• recognizing relevant & irrelevant information
• does result make sense? - ways to test
Exercise brain
Not listening passively to someone talk about subject
Subject expertise of instructor essential!
* “Deliberate Practice”, A. Ericsson research
accurate, readable summary in “Talent is over-rated”, by Colvin
II. Application in the classroom
(best opportunity for useful feedback
& student-student learning)
Student practicing thinking like scientist, with feedback
Example from teaching about current & voltage
1. Preclass assignment--Read pages on electric current.
Learn basic facts and terminology. Short online quiz to
check/reward. (Simple information transfer.
Accomplish without using valuable expert & class time)
2. Class starts with question:
When switch is closed, bulb 2 will
a. stay same brightness, b. get brighter
c. get dimmer, d. go out.
3. Individual answer with clicker
(accountability=intense thought, primed for feedback)
Jane Smith
chose a.
4. Discuss with “consensus group”, revote.
Practicing physicist thinking– conceptual model, examining
conclusion, finding ways to test, further testing & refining
Listening in! What aspects of student thinking right, what not?
5. Demonstrate/show result (phet cck)
6. Instructor follow up summary– feedback on which
models & which reasoning was correct, & which
incorrect and why. Large number of student
Students-practicing thinking like scientist (with feedback)
Instructor talking ~ 50% time, but responsive
Chemistry clicker/peer discussion/practicing-expert-thinking question examples (analytic):
Research– comparing learning in the
in classroom*
two ~identical sections of 1st year
college physics.
270 students each.
Control--standard lecture class– highly experienced
Prof with good student ratings. (A “good teacher”)
Experiment–- physics postdoc trained in principles &
methods of effective teaching.
They agreed on:
• Same learning objectives
• Same class time (3 hours, 1 week)
• Same exam (jointly prepared)- start of next class
*Deslauriers, Schewlew, Wieman, Sci. Mag. May 13, ‘11
Class design- as described
1. Targeted pre-class readings
2. Questions to solve, respond with clickers or on
worksheets, discuss with neighbors (“Peer Instruction”)
3. Discussion by instructor follows, not precedes.
4. Activities address motivation (relevance) and prior
Histogram of test scores
number of students
ave 41 ± 1 %
74 ± 1 %
Test score
10 11 12
Clear improvement for entire student population.
Engagement 85% vs 45%.
Most research --Learning in a course (class, homework, exam studying)
~ 1000 studies, all fields of STEM (~20 by me)
Active practice and feedback versus conventional lecture
Typical-• x 50-100% more learning on instructor-independent measures
• 1/3 -2/3 lower failure and drop rate
Meta-analyis of several hundred studies (Freeman et al PNAS 2014)
--gains similar all levels, all sci & eng disciplines
NRC-- “Discipline-based Educ. Research in Sci & Eng.” (NAS Press 2012)
• Cal Poly-- improved learning & teaching methods dominant
factor in teacher effectiveness (=amount learned)
• UCSD– failure rates
average trad. Cal Poly instruction
1st year mechanics
Hoellwarth and Moelter,
Am. J. Physics May ‘11
9 instructors, 8 terms, 40 students/section.
Same prescribed set of in-class learning tasks.
U. Cal. San Diego, Computer Science
Failure & drop rates– Beth Simon et al., 2012
4 different instructors
Standard Instruction
Peer Instruction
Fail Rate
III. Cultural challenges to improving chem ed
(relative to other sciences)
• Instructors feel compelled to cover too much, too fast.
• Excessive reliance on poor exams. High failure rates OK.
• Data has less impact-- how well expertise being learned &
conditions for long term retention.
1. a. What is in the bubbles in boiling water?
(After completing 1st year chem class less than half
get correct,~ 40% say H and O atoms,. Only 6%
change due to course.) Even a few grad TAs miss!!
Similar on other very basic questions like conservation of
mass and number of each type of atom in chemical reactions.
Examples (cont.)
2. Not just in intro. We observed profound conceptual
deficiencies in 3rd year P-chem.
3. Belief that “equilibrium means everything has
stopped” still present in many upper level students.
Most fundamental aspect of chemistry expertise– basic
mental models and when to apply.
Results like #1-3 known but much less concern/response
in chemistry than similar results in physics.
My groups work studying learning of Intro Quantum Mech.–
Students leave intro chem class with some memorized QM facts
& small mangled pieces of the concepts
Instruction-induced perceptions of subject (expert-novice)
Chemistry vs. Physics
Measured for bio majors taking both intro chem and physics
Both courses generally bad results but two particularly surprising*
1. Significantly more likely to agree with
“It is impossible to discuss ideas in chemistry without using
equations.” than with physics equivalent.
2. Significantly less likely to perceive chemistry as
having real world connections compared to physics.
real world connections response strongly correlates with
interest & choice of major
* --survey and some research papers
Summary: Taking a scientific approach to chemistry teaching
Tremendous opportunity for improvement–
• What is desired chemistry expertise?
• How to provide sufficient practice and
feedback to learn?
• Measure results rigorously, use data to
guide instruction
Good References:
S. Ambrose et. al. “How Learning works”
Colvin, “Talent is over-rated”
copies of slides
+ 20 available
Discipline-based Educ. Research in Sci. & Eng. Nat. Acad. Press (2012) resources, references, and videos
CBE—Life Sciences Education Vol. 13, 552–569, Fall 2014
The Teaching Practices Inventory:
Wieman & Gilbert
Effective teaching practices, ETP, scores
various math and science departments at UBC
before and after for dept
that made serious effort
to improve teaching
extras below, may need to answer questions
Some ideas for moving ahead
1. Use new educational tools that enhance learning
(e.g. simulations -- show gas and salts sims)
2. Chem Curriculum and Teaching of the Future
a. Delineate desired cognitive capabilities
(What can they do that indicates success?)
Look for common cognitive processes across areas
of chemistry and chemical engineering practice
b. Design curriculum by figuring out how to embed
these mental processes into range of desired contexts.
c. Always focus on “What thinking can they do?”,
not “What material has been presented to them?”
and be scientific--measure results and iterate
II. What does it look like in classroom?
(can go into more details later if desired)
• Designed around problems and questions, not
transmission of information and solutions
• Students actively engaged in class and out with
thinking and solving, while receiving extensive
• Teacher is “cognitive coach”-- designing practice
tasks, motivating, providing feedback
Me—Hypothesis. Jargon in biology
increases processing demands. So
presenting concepts before jargon would
achieve better learning.
Biologists Lisa M. & Megan B. to test
Reading before class. Textbook vs. textbook
without jargon. Then same active-learning
class for both with jargon.
Total Score
My most recent paper…
Cog. psych– “cognitive load” (processing
demands on brain) impacts learning.
DNA Structure
Free response question
test of learning at end of class
Lisa McDonnell & Megan Barker & CW
II. Role of faculty
Practice tasks– challenging but achievable. (and motivating)
Explicitly practice expert-like thinking.
Specific and timely feedback to guide thinking.
expertise in
teacher as “expertise coach”
Unique at Stanford– extraordinary expertise of faculty
“Talking textbook”—little expertise needed or transferred
Effective teaching (exercising learner’s brain)– demands and transfers expertise
IV. What does “transformed teaching” feel like to faculty?
led large-scale experiment– changing how entire large science departments teach
Is possible, but is a new expertise. Takes ~~ 100 hours to master basics.
Normally, no incentive to. (teaching practices & student learning never count)
Requires changing beliefs about learning--What is best, what is possible.
New faculty perspectives:
• teaching more rewarding & intellectually challenging
• different limitations on learning
Role of technology
Useful (=evidence of improved learning) at college level so far only when enhances capability
of teachers.
• task accountability and feedback to more students (online homework, in-class clickers)
• interactive simulations online--better convey expert conceptual models
(e.g. ~ 130 Million delivered, 75 languages)
Large part of my time.
Crusading for improved undergrad math and science teaching. (outside Stanford)
Talk & write about & my large scale experiments in change– UBC and CU science depts.
Better ways to evaluate university teaching
What about K-12?
These effective methods work at all levels, but require much more subject mastery
than does lecture.
K-12 science teachers need much better college science education and better model
for teaching science before they can use these methods effectively.
Compare with typical HW & exam problems, in-class
• Provide all information needed, and only that
information, to solve the problem
• Say what to neglect
• Not ask for argument why answer reasonable
• Only call for use of one representation
• Possible to solve quickly and easily by plugging into
• concepts and mental models + selection criteria
recognizing relevant & irrelevant information
what information is needed to solve
How I know this conclusion correct (or not)
model development, testing, and use
moving between specialized representations
(graphs, equations, physical motions, etc.)
The conventional alternative:
“Here is circuit with resistors and
voltage sources. Here is how to
calculate currents at A and B and
voltage difference using the proper
equations.... “
12 V
What expert thinking will students not practice?
Has NONE of the expertise in light bulb question design:
• Recognize expert conceptual model of current.
• Recognize how physicists would use to make predictions in
real world situation.
• Find motivational aspects in the physics
(“Lets you understand how electricity in house works!”)
When switch is closed,
answer &
bulb 2 will
a. stay same brightness,
b. get brighter
c. get dimmer,
d. go out.
Physics expertise in question design:
• Recognize expert conceptual model of current.
• Recognize how physicists would use to make predictions in
real world situation.
• Find motivational aspects in the physics
(“Lets you understand how electricity in house works!”)
Some components of S & E expertise
concepts and mental models + selection criteria
recognizing relevant & irrelevant information
what information is needed to solve
does answer/conclusion make sense- ways to test
model development, testing, and use
moving between specialized representations
(graphs, equations, physical motions, etc.)
• ...
Only make sense in context of topics.
Knowledge important but only as integrated part– how to
use/make-decisions with that knowledge.

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