Teaching Science for Motivation and Understanding

Teaching Science for Motivation and Understanding

Discussion with Knowles Fellows

November, 2003

Andy Anderson and Gail Richmond

Issues You Would Like to Discuss

Watching Jim Minstrell Teach about Newton’s Laws of Motion

• What do you notice that would cause you to change your answers to some of the questions about moving objects?

• What did you notice that would cause you to change or add to your answers to questions about problems of practice?

• What did Jim Minstrell need to know in order to teach this way?

Problems of Practicein Science Teaching

1. Science content: Goals and activities for student learning

2. Students and assessment

3. Classroom learning environments and teaching strategies

4. Professional resources and relationships

Niels Bohr on Scientific Reasoning

The task of science is both to extend our experience and reduce it to order, and this task represents various aspects, inseparably connected with each other. Only by experience itself do we come to recognize those laws which grant us a comprehensive view of the diversity of phenomena. As our knowledge becomes wider we must always be prepared, therefore, to expect alterations in the points of view best suited for the ordering of our experience.

Extending Experience and Reducing It to Order

Sense ExperienceDeepest scientific theories

Extending experience Reducing experience

to order

Pursuing the “turtles all the way down”

Piaget on Children’s First Inquiry: Developing a “Theory of Objects”

• Babies: Selective attention to faces, motion, unusual stimuli; no continuing interest when something disappears from view

• Peek-a-boo: Experience with objects disappearing and reappearing; encouraging adults to play

• Hide and seek: Finding hidden objects

• Object permanence as eventual outcome

Piaget on Conservation of Liquids

• Extending experience by pouring liquids from one container to another

• Early focus on only width or depth: More liquid in deeper container

• Later: coordinating thinking about width and depth

• Final: conservation of liquids; volume is always the same regardless of container

Experientially Real Objects, Systems, and Phenomena

Sense ExperienceDeepest scientific theories

Extending experience Reducing experience

to order

Experiences taken for granted as “real”

Explanations for those experiences

Edge of accepted experience

Development of Knowledge

• Extending experience: Adding to our stock of “experientially real” objects, systems, and phenomena – Adding new sense experiences– Adding vicarious sense experiences (e.g., pictures, video)– Adding believable, experientially real data (e.g., measurements,

carefully recorded observations)

• Reducing experience to order: Developing new and better models and theories– Conceptual change: Replacing old theories with new ones that account

for more data– Converting previous “theories” to taken-for-granted experientially real

objects, systems, phenomena (e.g., existence of objects, conservation of liquid volume)

Why Extending Our Experience and Reducing It to

Order Isn’t Always Science

Multiple Sense-making Strategies

What Counts as Experientially Real?

• Everyday judgments: Seeing (or hearing, touching, feeling) is believing– Vividness and immediacy of experience– Confirmation by peer group

• Scientific judgments: Creating data from experience– Reproducibility– Precision– Provenance of records– Confirmation by skeptical observers

Times When Everyday and Scientific Judgments Differ

• Rumors

• News, history

• Religious experience

• Data collected with complicated instruments

• Data presented in difficult-to-understand formats

What Counts as aGood Model or Theory?

• Procedural display: Whatever it takes to get a good grade

• Practical reasoning: Whatever it takes to get practical results (including inventing things)

• Narrative/metaphorical reasoning: Stories or metaphors that bring coherence to our experiences (including news, history)

• Model-based reasoning: Models that account for all relevant data in testable, parsimonious ways– “Unbroken chain of connections” from data to models– Consistency with other models and theories

Model-based Reasoning:Scientific Inquiry and Application

Experiences

(data,

phenomena,

systems,

objects,

evernts

Patterns

(generaliz-

ations,

laws)

Explanations

(hypotheses,

models,

theories)

Inquiry (constructing explanations from patterns in experience)

Application (Using scientific patterns and theories to describe, explain, predict, design )

Content Example:Newton’s Laws

What does it mean to “understand” Newton’s Laws?

Historical Sense-making Strategies for Explaining Motion• Aristotle, Ptolemy, and Aquinas

• Setting the stage for Galileo: Impetus theorists and Copernicus

• Galileo

• Newton

Aristotle, Ptolemy, and Aquinas

• Practical reasoning: Moving objects with simple machines, throwing,pushing, bows and arrows

• Narrative reasoning: Where and why do objects move– Animate objects (animals) move on their own– Natural motion: Inanimate objects tend toward their own spheres (earth,

water, air, fire)– Violent motion: Animals can impart motion to inanimate objects– Heavenly objects are kept in motion by the Prime Mover– Aquinas: Prime Mover is Christian God

• Model-based reasoning: Ptolemaic system explains motions of sun, moon, planets

Setting the stage for Galileo

• Practical reasoning: Siege engines (catapults, trebuchets, cannon); accuracy depends on direction and speed (not just personal skill)

• Narrative reasoning: Protestant reformation emphasizes personal God rather than distant Prime Mover

• Model-based reasoning: Copernicus suggests sun-centered model that fits observations better

Galileo

• Practical reasoning: Inventing better telescopes, measuring speed and direction of rolling and falling objects

• Narrative reasoning:– Challenging Ptolemy and Aquinas: Copernicus’ model

is true, not just way to calculate positions– Telescopic observations of corruptible heavens

• Model-based reasoning: Mathematical predictions of speed of falling objects

Newton

• Practical reasoning: Mathematical predictions of trajectories (models improve practical reasoning rather than the other way around)

• Narrative reasoning:– Anti-Trinitarian Biblical text criticism: God does not

intervene in everyday events– Newton’s apple: The apple and the moon are

following the same laws

• Model-based reasoning: Newton’s Laws of motion and universal gravitation

Newton’s First Law

Traditional wording

• Every object continues in a state of rest, or of motion in a straight line at a constant speed, unless it is compelled to change that state by unbalanced forces exerted on it.

Contrasting Newton and Aristotle

• Motion doesn’t need to be explained, only changes in speed or direction (velocity).

• Necessity: No forces or balanced forces always mean no change in speed or direction, and vice versa.

Newton’s Second Law

Traditional wording

• The acceleration produced by a net force on an object is directly proportional to the magnitude of the net force, is in the same direction as the net force, and is inversely proportional to the mass of the object (F = ma).


• Forces do not cause motion. Instead they cause acceleration, or change in speed or direction (i.e., velocity).

Newton’s Third Law

Traditional wording

• For every action there is an equal and opposite reaction.


• Forces always come in pairs. When A exerts a force on B, B exerts an equal and opposite force on A. This does not mean that the forces on A or B are balanced.

Aristotelian and Newtonian Answers to Questions

1. Book on the table• Aristotelian: Table blocks book from falling• Newtonian: Table exerts an upward force

that balances the downward force of gravity

2. Coin in the air• Aristotelian: Coin’s upward flight is sustained

by a “force from the hand”• Newtonian: Continuing upward motion

doesn’t need to be explained. Unbalanced force of gravity slows the coin down.

Aristotelian and Newtonian Answers to Questions (cont)

3. Cart at constant velocity• Aristotelian: Continued motion requires

continued force• Newtonian: Net force is 0 for motion at

constant speed and direction

4. Accelerating cart• Aristotelian: Increasing motion requires

increasing force• Newtonian: F = ma. Constant acceleration

requires a constant net force






Purposes for Classroom Assessment

• Understanding your students

• Helping your students to assess and improve their own understanding

• Grading

Criteria for Assessments that Help You Understand Students

• Connection to goals: The questions address important objectives you have for student learning

• Interesting wrong answers: Even incorrect answers reveal students' thinking

• Insight into students’ sense-making: The students’ answers help you understand how they make sense of the world, not just where their knowledge of science is weak.

• Starting a dialogue with students: The questions help you to start discussions with students where they can compare their ideas with scientific ideas.

Types of questions that produce interesting wrong

answers

Backwards reasoning

• If --- is the answer, then what was the question?• What question were scientists trying to answer:

– …when they discovered photosynthesis? (e.g., why do plants need light?)

– …when they discovered atomic theory (e.g., why do elements always combine in certain proportions?)

Familiar situations

• Getting students’ theories about familiar examples.– What are the forces on a coin flipped into the air?– Are your eyes the same color as your mother’s? How

do you think that happened?– What’s inside the bubbles of boiling water?

Connecting different representations

• Seeing what happens when students represent the same example in different ways.– Draw a picture of what is happening to the atoms of

NaCl as solid salt dissolves in water.– Show how the light rays travel that enable a person to

see a tree as she looks out the window.

Types of Representations

Most concrete• Close to experiences, observations, data• Misconceptions (matching incorrect

models to the experience) are a keyproblem

Most abstract• Close to models or theories• Empty symbol manipulation is a key

problem

Observations of actual phenomena

Analogous phenomena (e.g., condensationon glass compared to cloud formation)

Physical models

Simulations

Drawings, diagrams

Data tables

Graphs showing data or relationships

Verbal explanations

Formulas and equations

Short answer + explanation

• Ask students to make a choice or draw arrows, then explain their reasoning.– Does food normally move up or down a

plant’s stem? Explain your reasoning.– Will the “ashes” left after magnesium burns

weigh more or less than the original metal? Explain your reasoning.

Use misconceptions research

• Ask questions that will reveal common misconceptions (as reported in research).– What question would reveal a belief that liquids

disappear when they evaporate?– What questions would reveal a belief that plants get

their food from the soil?– What question would reveal a belief that the phases

of the moon are caused by the earth’s shadow?

Comparing examples or concepts

• Ask students to compare and contrast different real world examples or familiar terms – heat vs. temperature– force vs. momentum– Current vs.voltage– Green plants vs. fungi– Volcanoes vs. other mountains

Critique of suggested responses

• Ask students whether they agree or disagree with responses that reveal misconceptions, and why.– My friend says that sunlight is food for plants. Do you

agree? Why or why not?– My friend says that when water evaporates, the water

vapor weighs just as much as the liquid water. Do you agree? Why or why not?

Teaching Newton’s Laws to (Aristotelian) High School Students

• Describing motion: Focusing on speed and direction rather than destination and reason for motion

• Negotiating standards for what counts as evidence (“experientially real”)

• Extending experience: Collecting data in situations where Aristotle’s rules break down

• Questioning students’ narrative and practical knowledge• Model-based reasoning: Finding consistent,

parsimonious explanations that fit all the data

• Quantitative rigor: Using models to make precise, quantitative predictions

Watching Jim Minstrell Teach Again

How does he address each of the challenges to his students’

learning with understanding?






Approaches to Teaching Science (from Mark Olson)

Carol: Science Curriculum as a Progression of Models

Jennifer: Science Curriculum as “Chapters in the Story”

Bar magnets

Electromagnets

Magnetic Induction

Ferromagnetism

Magnetic Domains

Example

Example

Example

Example

Example

Problems with Carol’s approach:

oversimplified modelsleaves out the good partnot part of Kuhn’s normal science

Problems with Jennifer’s Approach:

students can only tell story no model-based reasoningstudents forget what they studied

Experiences

(data,

phenomena,

systems,

objects,

evernts

Patterns

(generaliz-

ations,

laws)

Explanations

(hypotheses,

models,

theories)



Experiences

(data,

phenomena,

systems,

objects,

evernts

Patterns

(generaliz-

ations,

laws)

Explanations

(hypotheses,

models,

theories)



Experiences

(data,

phenomena,

systems,

objects,

evernts

Patterns

(generaliz-

ations,

laws)

Explanations

(hypotheses,

models,

theories)



General Teaching Strategies

• Covering content: Telling the story with examples and expecting students to tell it back (Jennifer’s approach)– Leads to narrative understanding or procedural

display

• Learning cycles focusing on application of model-based reasoning (Carol’s approach)

• Inquiry cycles focusing on developing new models through reasoning about data (Minstrell’s approach)

Classroom Environments for Learning and Inquiry Cycles

• Personal and emotional safety for students, including moderate levels of risk and ambiguity

• Motivating students to learn: Expectancy times value

• Social norms for participation and communication

Model-based Reasoning:Scientific Inquiry and Application

Experiences

(data,

phenomena,

systems,

objects,

evernts

Patterns

(generaliz-

ations,

laws)

Explanations

(hypotheses,

models,

theories)



Learning Cycles

Transfer of Responsibility in the Learning Cycle

Stages in the Learning Cycle

• Establishing the problem: Connecting with prior knowledge and establishing motivation to learn

• Modeling: Exposing learners to comprehensible models of good practice

• Coaching: Providing opportunities for practice with scaffolding or support

• Fading: Gradually removing support until learners engage in the practice independently

• Maintenance: Continuing practice after initial learning is over

Prerequisites for Successful Learning Cycles (Focused on

Application)

• Model or theory that you want students to be able to apply

• Set of real-world examples• Pattern for students to follow in applying

theory to examples

Important Points about Learning Cycles• Assessing student thinking. Include embedded

assessment that will help you and your students understand their ideas and practices—both correct and incorrect.

• Keeping the objective whole. Students work through several examples where they see or do the whole task.

• Learning as transfer of responsibility. Students take more responsibility for doing the task.

• Scaffolding is temporary. Learning cycles are complete when students can accomplish the objective on their own.

Inquiry Cycles

Essential Features of Classroom Inquiry

1. Questions. Students engage in scientifically oriented questions.

2. Evidence: Data and patterns. Students respond to questions by looking for patterns in data—their own experiences and/or data supplied by the teacher.

3. Students’ explanations. Students formulate explanations from evidence.

4. Scientific theories or models. Students compare their explanations to explanations based on canonical scientific models or theories

5. Communication: Argumentation and justification. Students explain and justify their methods, results, and conclusions.

Prerequisites for Successful Inquiry Cycles

• Experiences: “Experientially real” data from students’ personal experience, classroom observations, simulations, or archived data sets

• Pattern(s) in experience that students will be able to see

• Theory or model that explains patterns

Lab Activities that Are Not Inquiry1. Confirmation labs: students follow directions. Purposes:

Practicing lab techniquesConfirming accuracy of laws and theories

2. “Consumer reports” labs: students compare products or practices to find the best one. Purposes:Reasoning about and developing experimental techniquesPracticing evidence-based argumentation and decision making

3. Explanation labs: students observe phenomena, then use models and theories to explain what they saw. Purposes:Connecting representations at different levels of abstractionPracticing detailed explanations of real-world examples

4. Design labs (engineering inquiry): students use scientific principles to design systems that accomplish specific purposes (e.g., egg drop lab, building bridges, maximizing crop yield). Purposes:Applying scientific theories to practical design problem.Building engineering skills

Inquiry Activities1. Naturalistic or field inquiry: students look for patterns in observations that

they make. Examples:Geological or ecological field workAstronomical observations, such as sun and moon

2. Experimental inquiry: students create new experience in the lab, often with planned variation. Examples:Systematically observing products of different reactionsComparing plant growth under different conditions

3. Data analysis: students look for and explain patterns in “experientially real” data sets that are given to them. Examples:Looking for patterns in weather or geographic dataExplaining reported results of dangerous experiments

4. Simulations: students look for patterns and explain results in “virtual worlds” that imitate reality. Examples:Models of moving objects or electrical circuitsEcosystem models

Learning and Inquiry Cycles

• Prerequisiteso Model or theory o Set of real-world exampleso Pattern for students to

follow in applying theory to examples

• Stages or activitieso Establishing the problemo Modelingo Coachingo Fadingo Maintenance

• Prerequisiteso “Experientially real” datao Pattern(s) that students

will be able to seeo Theory or model that

explains patterns

• Activitieso Questionso Evidence: Data and

patternso Students’ explanationso Scientific explanationso Communication

Jim Minstrell’s Teaching Strategies

• Classroom environment

• Learning cycles

• Inquiry cycles






Key Issues in Professional Resources and Relationships

• Finding, using, and adapting resources

• Learning from imperfect mentors

• Using assessment to learn from experience

• Explaining yourself and your practice to colleagues, administrators, parents

Revisiting Questions

What else do we need to discuss?

Contact Us

• Andy Anderson– [email protected]– 319A Erickson Hall, Michigan State University, East

Lansing, MI 48824– 517-432-4648

• Gail Richmond– [email protected]– 319 Erickson Hall, Michigan State University, East

Lansing, MI 48824– 517-432-4854

• Website: http://SciRes.educ.msu.edu/TEScience/index.htm

http://SciRes.educ.msu.edu/TEScience/index.htm

Documents

Teaching Science for Motivation and Understanding