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The Learning Process I:
Observing - Communicating - Classifying - Measuring - Inferring - Predicting
I. Observing: Use
of senses to observe objects and events searching for patterns. Senses:
sight, smell, touch, taste & hearing. Observing leads to curiosity,
questions and interpretations.
Q&Q
Observations: Qualitative:
light green (sight) - pungent odor (smell) - tastes sour (taste) - leaf is waxy
(touch) - sharp sound (hearing). Quantitative: - Leaf is 7 cm long - Rock
weighs 5 g - Temperature is 22C - Plant is as wide as 3 paper clips - This plant
is larger than that plant.
II. Communicating: Everything
we do! - Graphs, charts, maps, symbols, diagrams… Clear, precise,
unambiguous. Practice! Express ideas, feelings, and thoughts.
Describing
Objects to Others - Think
of one of the many traditional "optical illusions", i.e. Old
lady/young lady, Escher drawings, cubes, vase/lady.
Communicating with MAPs: A
symbolic representation - must have:
Title, symbols, key and scale.
III. Classifying Why
is classification important? Order with respect to similarities and differences
How are we classified? Demographics, telephone, address, occupation, etc.
IV. Measurement - Metric Essential
in making quantitative observation, comparing and classifying items, and
communicating effectively. Metric - SI: Volume - Lit er;
Mass - Gram; Distance - Meter.
Distance - scale or metric tape -
meters. Mass - equal-arm
balance - grams. Volume - calibrated containers - liters. 1 cubic cm (cc) = 1 mL.
Measuring liquid uses bottom of meniscus. Temperature
- thermometer. Water boils
@ 100C and freezes @ 0C
V.
Inferring Interpretation
of an observation. Recognize patterns and expect these to reoccur under the same
conditions. Form hypothesis based on inferences. Teachers make inferences as to
why students behave as they do. Learning is an inference made from observed
changes in behavior. (Schunk)
Inference Examples - The
brass knob is not shiny. I infer that the office is not used often. Iodine turns
purple on a potato chip. It can be inferred that it contains starch. Through the
window I see the flag waving. It must be windy out. That star is brighter than
the others. I infer it is closer to Earth than the others.
Steps for Inference - Make
as many observations as possible. Recall from prior experiences (*) as much
relevant material which can be integrated. State inference that clearly
distinguishes it from an observation or prediction. Monitor and evaluate your
statements.
Power of Inferences - Learning:Makes
sense of things, thus it is an inference. Based on observation - previous and
current. Based on individual differences and perspectives. Facilitate by linking
new concepts.
Teaching: Expert
observer and questioner (inquiry). Discover students prior knowledge to
link. Must create appropriate assessment. To improve prior knowledge,
design activities using senses.
VI. Predicting Forecast
of what a future observation might be - ability to construct allows us to
determine appropriate behavior - a reasoned statement. Based on careful
observation and inferences made about relationships. "If this happens, what
will follow?" "What will happen if I do this?"
How is Prediction
Different? - Information
gained through senses - Observation. Why the particular event happened -
Inference. What you expect to observe in the future - Prediction
Prediction Examples - I
see it raining and the sun comes out. There could be a rainbow. The weak
magnet picked up 5 paper clips. I predict the strong magnet will pick up more.
If I release both objects at the same time, they will hit the ground at the same
time.
Types
of Predictions - Interpolation
- predictions made between observed data. Extrapolation -
predictions made beyond observed data.
The Learning Process II: The
Integrated Steps
Contents
Identifying Variables
Constructing a Table/Graph
Variable Relationships
Processing Data
Analyzing
Hypothesis
Operational Definitions
Investigations
Experimenting
Empowers students to
answer own questions.
Students can interpret observations and design investigations.
Basic Skills provide foundation for process.
While reviewing this section, keep in mind:
How am I learning
this skill?
How will I teach this skill to students?
Identifying
Variables
A variable is
something that can vary or change.
Manipulated = Independent variables
Responding = Dependent variables.
Interpreting
Graphs
Variable
Relationships
Line of Best-Fit
Rules:
line should be
straight or smooth curve.
all points should lie either on the line or very near the line.
there should be about the same number of points on either side of the line.
Acquiring
and Processing Data
Conducting an
Investigation - observing and measuring.
Putting data in a table - classifying.
Graphing data - communicating.
Interpreting relationship between variables - communicating - inferring
explanations and predicting outcomes.
Beginning
an Investigation
An experiment begins
with a problem. Someone observes something and wonder, WHY?
For instance, what determines the time it takes water to heat and boil?
List
some of the variables that could affect the heating time of water?
Variables
for boiling water
Amount of water
Amount of dissolved material
Height above sea level
Shape and material of container
Type of heat source
Initial temperature of water
Analyzing
Investigations
Recognize parts of a
typical investigation.
What are the variables?
What hypothesis is being tested?
What are the expected outcomes?
How do your variables relate to these outcomes?
Is your approach feasible?
Control
What is a control?
Why and when should you use a control?
How do you use a control?
What is a constant?
Constructing
Hypothesis
An investigation
begins with a problem.
The science process skills are problem solving tools to gather information
(data) and test inferences (explanations).
Investigations are to determine if cause and effect relationships exist.
By deliberately changing one factor, another may change as a result.
To begin an investigation, a hypothesis, or prediction about the relationship
between variable is stated.
The hypothesis provides guidance to an investigation about what data to
collect.
This parameter begins the investigation and keeps the scientist on-track with
respect to goals, purpose and objectives.
Creating a
Hypothesis
To create a
hypothesis, begin by considering a problem:
What affects how
fast a person can run a 100 meter dash?
List all of the variables that could affect this problem:
Factors
that Affect Running
Lung Capacity
Muscle tone
Length of legs
Motivation
Wind direction
Track surface
Shoes
Operational
Definitions
By specifying a
procedure for measuring a variable, you are making an operational definition.
This means that YOU will decide how to measure it, thus it tells what is
observed and how it is measured.
Example:
Operationally define Constructivism on the Internet.
Designing
Investigations
KIS - Keep It Simple
The simpler the design, the more likely you will be able to collect useable
data.
Investigation is the setting up of a planned situation; the situation is
planned to yield data that will either support or not support your hypothesis.
If the manner in which a variable can be manipulated and the type of response
expected is clearly stated in the hypothesis, the much of the work is
complete.
There remains the task of specifying conditions under which the work will be
carried out.
Designing
Example
Suppose you want to
test the hypothesis:
"The Greater the
Surface Area of a Liquid Exposed to the Air, the Faster Evaporation will
Occur."
Discuss some of the
design parameters, starting with Materials, then Procedure, stating time
frame, Measurement tools, and Variables.
Design
Materials and
Procedure:
Pour 100 mL water at room temperature into 5 aluminum pans that are 5,6,7,8
and 9 cm square. Leave the pans sitting in an open room. After 2 hours have
passed, measure the volume of the water remaining in each pan.
The design consists of operationally defining both the manipulated and
responding variables:
MV is leaving the
liquid in different size open containers.
RV is measuring the volume of the liquid before and after a specific time.
The design also states which factors will be held constant.
Experimenting
Experimenting is the
culminating experience from the science process:
Posing a question,
identifying variables, formulating hypotheses, making operational
definitions, designing an investigation, conducting trials, collecting data,
and interpreting data.
Example
Problems
What affects the
amount of time it take a seed to sprout?
What affects the rate at which a person breathes?
What affects the amount of salt that can be dissolved in water?
What affects the time it takes to freeze when placed in the freezer?
Steps to
Addressing the Problems
Question
Hypothesis
Design with variables operationally defined
Data table
Graph
Relationship between variables
Findings
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