Light & Color Lesson Guide

Transcription

1
Teacher Guide
This lesson planning and implementation guide is specifically for the Light & Color investigation. For unit-level
planning, see the Teacher Product Guide in the Introduction section of the teacher materials.
At a Glance...
In this lesson, students will use the Light Sensor as the subject of study, examining the ways in which it
responds to different light and color stimuli. Learning goals are focused around inquiry, experimental design,
systems with multiple variables, and properties of color.
Students working in groups of 2-4 are expected to take approximately 3-5 days (45 minute period per day) to
complete this activity, depending on their level of comfort with the technology.
The Content Concept
In addition to the crucial Inquiry and Experimentation elements in this investigation, this lesson focuses on
light, color, and the behavior of light as it reflects off of colored objects.
The NXT Light Sensor consists of two parts: a light source and a light detector. The light source emits
primarily red light (around 650 nm). The light detector detects light in the same range. When red light enters
the Light Sensor’s clear detector bulb, it raises the sensor reading. The stronger the detectable light, the
higher the sensor value.
When the sensor is placed close to an object or surface such as the color strip – as it is in this lesson –
outside light tends to be blocked. This leaves only the light from the light source. The light source’s red light
shines outward, however, and can only reach the detector if it is reflected back into the detector by the object
Consequently, the better a surface is at reflecting red light, the higher a reading it will get.
Brightness of a color is a great indicator of how well it reflects light. The more light it reflects, the brighter it
appears (humans perceive “amount of light” as brightness). Brighter colors, therefore, will get higher readings
than darker colors.
Color of a surface in normal (white) lighting is also a good indicator of how well it reflects red light. If
something looks red, it is because it is reflecting red light into the viewer’s eyes. White surfaces also get high
readings, since white means all colors are reflected (including red).
In order to be more precise about whether we are referring to the “redness” of a color rather than the
“brightness” of the red, we use the term “hue” to distinguish the coloration, and talk about “lightness”
separately.
In the Light & Color investigation, students will analyze both of these qualities (lightness and hue) separately.
Comparing shades of black, white, and grey allows them to observe the effect of brightness on sensor
reading, but then introducing the varied readings from the equally-bright colors forces them to revise their
hypotheses based on new data. Students may or may not eventually conclude that the two factors are really
one. It is up to you whether you wish to push for the “single factor” explanation.
Science & Data Logging
© Copyright Carnegie Mellon Robotics Academy
2
Objectives and Outcomes
1. Students will conduct a scientific experiment to determine the light and color factors which affect the
numeric output of a Light Sensor
2. Given student-collected data and structured leading questions, students will be able to identify that
there are multiple factors affecting the Light Sensor value, and explain how the data supports their claim
3. Students will recognize a system where a single output depends on multiple input factors, and propose
test cases that isolate each factor as a variable to test experimentally
4. Students will recognize two different qualities of light relating to color – lightness and hue – and be able
to provide example-pairs of colors which exemplify a difference for each
Resources
• LEGO® MINDSTORMS® Education Base Set (9797) and PC/Mac with LEGO MINDSTORMS Edu NXT
2.0 Software installed.
• (Recommended) One setup as described above, per group. This activity can be completed as a wholeclass activity if only one set of materials is available, however.
• (Suggested) Volunteer group of students builds Light Sensor Platforms (Video Step 3) in advance to
save class time.
Prerequisites
• (Recommended) Science & Data Logging Tutorial activity completed in advance
Additional Teacher Notes
As written, this lesson touches but does not focus on the physical principles behind perception and reflectivity
of light. However, underlying the apparent two-factor behavior of the Light Sensor (i.e. the fact that it responds
to both brightness and color) is a single-factor explanation: the Light Sensor measures the amount of red light
it sees. Try using a diffraction grating or prism to examine the visible light present in the color bands in the
book – you will see that all of the colors that produce high readings actually contain red-reflecting dyes, even
though the presence of other dyes may cause the human eye to perceive them as perhaps yellow or orange.
The end-of-lesson Continue activity for Light & Color requires the use of the Programming portion of the NXT
software. Clicking the link will take you to a directory containing a program file. Double-click the file to open
it, and use the Programming window’s Play button in the lower-right corner to run it. Make sure your existing
NXT Data Logging or Programming material is saved first!
It can be very informative to use diffraction grating slides to separate the light in the color strips, and allow
students to see what colors are actually being reflected. You should procure these in advance. Optical prisms
do not work well for this because the strips are thin and close together; prisms work best when you shine a
beam of light directly through them.
3
Lesson Structure
Reminder: The structure below describes a suggested “flow” for the lesson. The “style” in which the lesson is
taught, including the degree to which the videos should “dictate” versus “guide”, is dependent on the maturity
and experience level of the students. See the Teacher Product Guide in the Introduction section of the teacher
material for details. “Days” below assume 45-minute periods.
DAY 1
• Students are introduced to the pipeline repair problem by watching the Step 1 video
• Students discuss the nature of the light sensor and list what they know about light and what it has to do
with color (identify preconceptions)
• If time remains, discuss the perception of the color of objects, with special attention given to the fact
that perceived color is based on the color of light that is reflected, not absorbed
DAY 2
• Students follow video steps 2-5, pausing to answer the questions at the end of each video (written,
verbally, or independently at instructor’s discretion; note that answers to “Check Your Answer” questions
are directly accessible to students by hovering the mouse cursor over the “Check Your Answer” icon
next to those questions)
• Students should complete Step 6 then stop and check in with the instructor. This is a good checkpoint
to make sure that student data is being collected correctly, and to remind students that they need to
make their predictions before measuring the other colors.
CHECKPOINT: Students must report to the instructor and receive approval before continuing
DAYS 3-4
• Students continue with the experiment, following video 7 after making their predictions. Optionally,
check their predictions before allowing them to take actual measurements.
• Students take measurements in Step 8, and examine them in Step 9.
• Question 9-1 is recommended as a discussion question, since students may notice many different
things and come up with many different explanations.
• Students perform two parallel series of analyses in Steps 10 and 11. Have students check in with their
conclusions after Step 11.
• Students continue with Continue Steps 12-14 to simulate the Pipeline Explorer using cardboard
model ducting. This section will require some construction and will also involve the use of the NXT
Programming software (the NXT software). You do not need a new cardboard “pipe” setup for each
group; one or two should be sufficient for the whole class.
DAY 5
• When all student groups have finished Step 11, debrief about lightness and hue, then optionally
continue on with the Pipeline Explorer activity at your own discretion.
• Conclude measurements and analyses for the model Pipeline Explorer
• Administer Quiz
4
Sample Graph
This is a sample graph of completed student data at the end of this lesson (color viewing recommended).
• Red is so high that it actually exceeds white on this graph. It will generally be either near white or above
it, because the sensor is most sensitive to red light... as shiny and bright as the white part of the page
is, the red strip actually manages to reflect more red light than white!
• Blue and green are close together in the middle. Since both are of similar lightness, but neither is red,
they are usually in this region.
• Black remains at the bottom, but does not have a 0 reading because the glossy paper reflects some
light even though the ink makes is black.
• The student in this case predicted that all 3 colors would be the same brightness – the red, green,
and blue dotted lines are all on top of each other. This is a reasonable expectation if he or she made
predictions based on the (reasonable, at the time) hypothesis that brightness was the only factor that
mattered.
• There are a lot of lines on this graph! Clicking the small “eye” icon next to each line will toggle its
visibility.
5
Light & Color Worksheet Answer Key
Worksheet
Answer the Worksheet Questions for each Step after you have followed along with the video.
Check Your Answer
This type of question appears
only after videos, and never
on worksheets.
Place your mouse cursor over
the “Check Your Answer” icon
on the question screen to
check your answer!
Worksheet question
These appear in both the
videos and worksheets.
Answer these based on
your data and experience,
and record your answers
here on the worksheet.
Step 5
5-1. Sketch the relative positions for the black and white lines on the graph below. Label each line
clearly.
Light Sensor Reading
White
Red
Grey
Blue & Green
Black
Time
5-2. Based on the Black and White sensor values, what kinds of colors do you think will produce
high Light Sensor readings, in general? Write your answer in the form of a rule:
Example: Hotter temperatures produce higher Temperature Sensor readings.
Fill in: ____________er colors produce higher Light Sensor readings.
Students can make any answer they feel they can justify at this point, but a typical answer would be “Lighter”.
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Step 6
6-1. Add lines to the graph you drew in Question 5-1 (on the previous page), showing what you
think the lines for the colors grey, red, blue and green will look like.
Some potential student answers are shown on the graph on the previous page. Encourage students to complete
this step before adding the lines to their graphs in the Data Logging software, and to make sure the two match.
6-2. How did you decide where to put each of the four prediction lines?
Students should have at least a slightly organized rationale for these predictions based on available data about
the black and white measurements – therefore, predictions should typically focus on the lightness of the colors.
Grey, for example, should be straightforward to place in between black and white. For the others, however, some
students may perceive a difference in brightness or lightness, or others might predict that they’re all the same
lightness, so they should all give the same value.
6-3. For each statement below, fill in the middle blank with one of the following:
“... a significantly higher reading than ...”
“... about the same reading as ...”
“... a significantly lower reading than ...”
I think that the Grey bar will give...
I think that the Grey bar will give...
I think that the Red bar will give...
I think that the Red bar will give...
I think that the Blue bar will give...
higher
lower
(based on student answer in 6-2)
...the Black bar.
...the White bar.
...the Blue bar.
...the Green bar.
...the Green bar.
Step 9
9-1. Choose one pair of colors from Question 6-3 that did not behave as you expected – perhaps
two values you thought would be the same didn’t turn out to be? Come up with at least one
possible explanation for this unexpected behavior.
This question is a good candidate for class discussion. The most common mismatch is one where students predict
that two of the colored bands (red, blue, green) will match because they are the same brightness, but don’t.
Another interesting pair to examine is red + white (how can red be lighter than white??).
The eventual conclusion to reach in discussion is that the current explanation for the behavior of the light sensor –
that lightness of the color is the determining factor – is insufficient to explain the new evidence. This can also take
the form of an answer such as “Color also has an effect on the light sensor value.”
It will be natural for students to want to find things wrong with the experimental procedure or execution rather
than change their beliefs about the Light Sensor. If you have time, students can try these modified versions of the
experiment, but ultimately, the data should support the same conclusion. If you do not have time, then Occam’s
Razor (the “simplest solution principle”) may help to catalyze the discussion – there could be lots of complex
explanations, but what if our initial thoughts on the Light Sensor were just incomplete?
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Step 10
10-1.Examine the actual Black and Grey color strips in the book (not the data lines yet). What
primary characteristic would you say is different between the two colors?
Black and grey are essentially the same color, but with different “Lightness” or “Brightness”. Black is darker than
Grey. Grey is lighter than Black. However, neither is a different “hue” on the color wheel like red, blue, or green.
10-2.Refer back to the rule you proposed in Question 5-2. According to that rule, which of the two
colors you just chose (in 10-1) should have produced the higher Light Sensor reading?
Students should refer back to their rule. Most commonly, students say that the “lighter” color will produce the higher
reading, and thus predicts Grey will be higher than Black (whichever pair students choose).
10-3.Compare the actual Light Sensor readings. Did the rule correctly predict which color had the
higher value? If not, how could the rule be revised to account for this new data?
The prediction of Grey > Black is correct and supported by the Light Sensor values.
If students had an “incorrect” prediction, they should revise their prediction now to take into account the data along
this axis of comparison. Since the items being compared explicitly vary only in their “lightness” (the choice made in
10-1), lightness should be the logical conclusion.
10-4.Why is it important to choose shades of the same color for this comparison?
Because in order to make a “fair comparison”, you needed to eliminate as many other possible factors as possible.
This is directly related to the “fair test” concept, where external factors which bias the comparison need to be
eliminated or controlled as much as possible. If you did not do so, the real reason for the difference would be
unclear – is it the thing you’re examining, or the other unintended difference?
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Step 11
11-1.Examine the actual Blue and Red color strips in the book (not the data lines yet). What
primary characteristic would you say is different between the two colors?
This is the “hue” or “color” parallel to Step 10. Blue and Red have similar lightness, but are totally different
directions on the color wheel. Pairs of matched “lightness” sometimes vary under student perception, so students
may also note that one is slightly (but not greatly) lighter. Students should NOT use the Light Sensor values to
conclude that their brightnesses are different; this would be backward reasoning.
11-2.Refer back to the rule you proposed in Question 5-2 (or the revised version, if you revised it
in 10-3). According to that rule, which of the two colors – Red or Blue – should have produced
the higher Light Senor reading? Or should they have been the same?
A prediction rule using lightness as its only factor should predict that any two of these colors will produce very
similar readings.
11-3.Compare the actual Light Sensor readings. Did the rule correctly predict which color had the
higher value? If not, how could it be revised to account for this new data? A rule can have
more than one statement as long as they don’t conflict with each other!
Red is much higher than Blue when measured.
The rule either can’t make a prediction, or predicts that they will be very similar readings, since their lightnesses are
similar. Both are incorrect predictions.
The rule should be revised to include color as an ADDITIONAL factor. Lightness should not be removed as a rule,
but rather the two should coexist. It is also possible to have a “hybrid” rule involving both factors in a single metric,
like “the amount of red light”.
An example of a “before” rule might be: “The Light Sensor gives higher readings for brighter colors.” This could be
revised to be: “The Light Sensor gives higher readings for brighter colors, and for more reddish hues.”
11-4.Why is it important to choose shades of approximately the same “lightness” for this
comparison?
Again, the fairness of the comparison – and your ability to conclude that color is a factor – depends on eliminating
other possible sources of interference.
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Step 12
12-1.The Pipeline Explorer robot shown below is designed to travel through natural gas pipes,
searching for leaks with a camera.
a.
Why is a robot helpful for this task?
Manual inspection is costly, time-consuming, and disruptive. Additional student research can also reveal that there
are already tethered systems that perform similar work, but their range is very limited (by the length of the tether
cable) compared to an autonomous robotic solution.
b.
How is a video camera similar to a Light Sensor? How is it different?
A digital video camera can be thought of as being made of millions of tiny light sensors, sensitive to different colors
of light (red, green, and blue). However, the actual technology used is much more advanced and compact, and the
system displays its information in a very different way (pictures rather than lines).
Step 14
14-2.Suppose the robot runs through a 10m stretch of pipe and gives the following data...
a.
What point in the run does the leftmost arrow represent?
The point at which the robot started, typically the beginning of the pipe, or at least the beginning of the 10m
segment.
b.
What point in the run does the rightmost arrow represent?
The point at which data recording ended, typically the end of the pipe. We know from the problem description that
this is also 10m from the beginning.
c.
d.
What might the middle arrow represent?
An area of something anomalous, producing a low sensor reading, perhaps a dark spot. A hole, perhaps? You
can enrich this question by using red tape to indicate rust, and black tape to indicate holes, which would show as
upward and downward “bumps” in the line respectively.
Where in the pipe is the sensor value “dip” marked by the middle arrow? Describe the location
as a distance from the entrance.
Students can estimate the position of the dip by noting that it begins perhaps 30% of the way through the robot’s
run. Since this segment of data corresponds to 10m of pipe, then it is 30% of that 10m segment, or about 3-4
meters in.
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14-3.Examine your own robot’s results!
a.
Were there any points of interest in your data like the “dip” marked by the middle arrow in the
example on the previous page?
The construction of the model pipe calls for there to be an alternate-colored strip of tape, so there should be at
least one such anomaly. However, if the model pipe is constructed using dark materials and a light-colored “break”,
the anomaly could appear as a “bump” instead of a “dip”!
b.
Where did these points occur? Describe their positions using distances if possible.
Students should approximate the position of the anomaly by referring to parts of their graph. They can measure the
robot’s total running distance to find out how far apart the start and end of the graph are, and calculate the position
of the anomaly by finding the fraction of the total distance.
c.
What might those “points of interest” be? Use data from your color strip experiment as
evidence for your answer.
On a basic level, the Light Sensor is not detailed enough in its data to tell what the anomaly is. However, by
referring to the Sensor measurements from the color strip, students can make some reasoned guesses about what
color the anomalous material is.
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Light & Color Quiz Answer Key
Quiz
Complete these questions after you have completed the Light & Color Investigation.
Question 1
1a. Rearrange the following 5 colors so that they are listed in order from highest expected Light
Sensor value, to lowest:
Black, White, Red, Grey, Blue
These colors are measured during the investigation, but there are occasionally acceptable discrepancies in data
that will put them in a slightly different order.
• Student identifies the order: White, Red, Grey, Blue, Black
• ALSO ACCEPTABLE: White and Red are sometimes reversed
• ALSO ACCEPTABLE: Blue and Black are sometimes reversed
1b. What is one pair of colors that human eyes can usually distinguish, that the Light Sensor can
not?
There are several pairs that are typically ambiguous to the Light Sensor, producing very similar readings:
• Student chooses a pair that gets similar Light Sensor readings, such as Blue and Green, White and Red,
Blue and Black, Yellow and Red
• ALSO ACCEPTABLE: Any pair for which students can show data
Question 2
There are two different factors at work in determining what value the Light Sensor shows for a color.
2a. One of the factors is the “lightness” of the color. Give an example of two colors that are
identical except for “lightness”.
• Student identifies any two colors that are lighter or darker shades of the same hue, such as Black vs. White,
or Light Blue vs. Dark Blue.
• Do not accept colors that have different base colors, like yellow vs. dark green.
• Neither Yellow nor Orange is a “lighter” version of red. They are also different from each other.
2b. The other factor is the “hue” of the color. Give an example of two colors that are identical
except for “hue”.
• Student identifies any two colors that have approximately the same brightness, such as Blue vs. Green, or
Red vs. Blue.
• Do not accept any colors that are significantly different brightness shades, like Pink vs. Red.
• Orange and Yellow are difficult to work with, because even a “pure” yellow tends to be bright.
2c. Using the concepts of Hue and Lightness, explain what kind of reading one might expect for a
Dark Red color band, read using the NXT Light Sensor. Write your answer on the back of this
sheet.
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12
Light & Color Quiz Answer Key
(Question 2c continued)
• Student identifies that the there are two conflicting (or interacting) factors at work in determining the Light
Sensor value, and that those two are lightness and hue.
• Student argues that for the NXT Light Sensor, darker colors – those with lower lightness – tend to have low
readings. Dark red is dark, and should therefore give a low reading.
• Student argues that for the NXT Light Sensor, red colors – those with hues nearest red – tend to have high
readings. Dark red is red, and should therefore give a high reading.
• Student concludes that because of the conflicting nature of the two factors, the resulting reading would be
somewhere in the middle.
NAME
DATE

Light & Color Lesson Guide

Transcription

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