Margaret Shavlik Thesis

Running head: FURNISHING THE MIND 1

Furnishing the Mind: Understanding How Children Learn Adjectives
Margaret Shavlik
Faculty Advisor: Sandra Waxman
Second Reader: Steven Franconeri
Northwestern University
Department of Psychology – Honors Thesis

FURNISHING THE MIND 2
Abstract
An intuition-based theory of adjective learning is that it is a perceptually-based process.
However, it seems to be the case that children are not forming mere associations between a word
and a perceptual experience, but are in fact incorporating reference from their holistic knowledge
of the world. The current study put this to the test. We showed children books of ambiguous
shapes (e.g., a shape that could be interpreted either as spilled paint or a painting of a dragonfly),
introducing the books as full of “pictures of things” or “blobs of stuff.” On each page, we
described a target shape using a novel adjective (e.g., “blickish”), and as we showed two test
shapes (one of which matched the first in color) we asked the child if they could find “another
one that is blickish.” We found that this difference mattered: children who thought the shapes
were “blobs of stuff” were much more accurate at indicating a color match than those who
thought that the identical shapes were “pictures of things.” Put in context, the “blue” property a
child extracts from a dragonfly seems to be different—and less flexible—than the “blue”
property she extracts from a dragonfly-shaped puddle. Conceptual information, not just
perceptual information, seems to play a role in how children understand adjectives.
Acknowledgments
My sincere thanks to my advising professor, Sandra Waxman, and graduate student advisor,
Alexander Latourette. I would also like to thank Brooke Sprague, Jennie Woodring, and
everyone at the Project on Child Development for their help and support.

Furnishing the Mind: Understanding How Children Learn Adjectives
Literature Review
Childhood language skills are a strong predictor of overall success in school and work
(Biemiller, 2006; Biemiller, 2001; Song et al. 2015) and understanding what facilitates early
language learning could offer tools for addressing the “vocabulary gap” that exists between those
with high and low childhood vocabularies (Biemiller & Slonim, 2001; Chall, Jacobs, & Baldwin,
2009). Communication is the building block upon which much other learning relies, and as such,
understanding the mechanisms by which language learning occurs is vital.
Infants gain the skill to distinguish between different grammatical categories (nouns,
verbs, etc.) not long after speaking their first words – and long before they start using them in
sentences (Waxman & Booth, 2001). This ability to distinguish parts of speech is instrumental in
helping children learn to match the words they hear with the appropriate referents in the world
around them. Children's amazing word-learning capacity then serves as an important cornerstone
in their cognitive and linguistic development (Waxman & Markow, 1995; Biemiller, 2006).
Arguably, the hallmark social, conceptual, and linguistic abilities of the human mind share a
common lineage: word learning. Early in this process, children learn words for objects (e.g., dog)
and properties (e.g., white; Waxman & Booth, 2001).
An intuition-based theory of adjective acquisition is that it is a perceptually-based process.
A child hears a word, sees the property being described, and thus, is able to use the adjective to
describe other instances of that property. Philosopher John Locke articulates this approach,
famously describing the human mind as “white paper, void of all characters, without any ideas.”
According to Locke, the immense task of “furnishing” the mind relied simply on experience.

Thus, Locke argued:
The same colour being observed to-day in chalk or snow, which the mind
yesterday received from milk, it considers that appearance alone…and having
given it the name whiteness, it by that sound signifies the same quality
wheresoever to be imagined or met with. (Locke, 1690/1975)
One common instance of this furnishing, like in Locke’s example, involves the process by
which a child learns the names for colors. If Locke were right, then after hearing “Look at this
brown dog,” it should be easy for a young child to identify a house that is brown. However, this
process is in actuality much more complex for young language learners. First, they need to
identify which feature of the dog is described by “brown” (color? texture? other?). Next, children
have to learn how “brown” can be applied to other objects from the same category (e.g., from
one dog to another), and then, objects from new categories (e.g., from dogs to houses). This step
is surprisingly difficult for young learners (Sandhofer & Smith, 1999; Klibanoff & Waxman,
2000), which implies that children are not just assigning a perceptual quality a name. Instead, it
is likely that children are incorporating conceptual information into their understanding of a new
adjective’s referent. Just as is the case when learning names for object-nouns (see Waxman &
Gelman, 2009 for overview), children are not forming mere associations between a word and a
perceptual experience, but are in fact incorporating reference from their holistic knowledge of
the world.
Research on the role of intention and analogy in children’s naming of pictorial
representations supports this account as well (e.g., Gelman & Bloom, 2000; Christie, Gentner,
Vosniadou, & Kaiser, 2007). Sameness of shape has been found to be neither necessary nor
sufficient for two representations to share a name (for example, while an egg and a football are
quite similar in shape, most people would agree that they should not share an object name).

Children make this distinction as well when viewing accidentally versus intentionally created
drawings: they much more likely to name the resulting shape if it was intentionally created than
if it were created on accident (Bloom & Markson, 1998).
To illustrate the role of conceptual information in adjective extension, Klibanoff &
Waxman (2000) taught children novel adjectives (e.g., “blickish”; see appendix) to describe
familiar objects. They found that adjective learning is not simply matching one hue to another.
Instead, children’s interpretation of property terms (adjectives) varies with the kind of object
being modified by the term (e.g., the “softness” of a kitten differs from the “softness” of a scarf).
If adjective learning was solely a perception-based process, children should find it equally easy
to extend a property name (e.g., “blickish”) for a quality (such as “being-bumpy’) from an apple
to another apple, or from an apple to a boat. It would not matter if two “blickish” objects were of
different or the same shape, as long as the salient perceptual feature (texture) was present in at
least one of the test items. However, this was not the case, as Klibanoff and Waxman found that
these property words were much easier to map from the trial object onto a test object of the same
basic-kind. This suggests that perceptual features may be initially constrained by item category
when children are first learning the meaning of the property.
In subsequent pilot testing, Waxman (2002) took this logic a step further. Would this
shape-bias still exist if children saw ambiguous shapes, instead of known objects? And could this
bias be manipulated solely based on conceptual information (how the stimuli were introduced)
while keeping all perceptual information constant? She reasoned that children would be more
successful at extending a novel adjective if it has been introduced as a property of a substance
(“a blickish blob of stuff”) than as a kind of object (“a blickish picture of a thing”), because all
blobs would fit under the same overarching category whereas each kind of object has its own

category membership and rules. She developed ambiguous stimuli which varied in color and
texture (see Appendix 0.2.1 for an example), introducing them to some children as “pictures of
things” and to others as “blobs of stuff.” This change in wording had a striking effect: children
successfully extended a novel adjective from one “blob of stuff” onto any other, but failed to do
so when the same ambiguous image was described as a “kind of thing.” This pilot is the
foundation for the current study. We updated (and validated) the stimuli through further pilot
testing and increased sample size. We predicted that her findings would hold: that children
would only be able to extend new adjectives onto objects of the same basic-kind, but to any kind
of non-object.
In the current experiment, we created books of stimuli that were either introduced as “a
book full of lots of pictures of things” or “a book full of lots of blobs of stuff.” We introduced a
target stimulus using a novel adjective (e.g., “blickish,” “zavish”), and asked the child if she or
he could find “another one that is “blickish,” showing two more stimuli (that matched each
others’ shape, but not that of the target) that varied along the parameter of color. We chose to
isolate color (instead of using both color and texture, as was the case in Waxman, 2002) because
it was easier to control and showed the effect of the conceptual manipulation more clearly in the
original study. In either condition, the stimuli were identical (the same perceptual information).
What varied was how the books were introduced (the conceptual information).
Predictions
We predicted that there would be a significant difference between the BLOBS condition
and the other conditions. This would support our hypothesis that there is an overall benefit from
being in the BLOBS condition as opposed to the other two.

Based on the findings of the previous study (Waxman 2002), we predicted no significant
difference between the OBJECTS and the CONTROL conditions. In absence of an explicit
contradiction, children may assume that stimuli are “objects” (i.e., exhibit an object-bias).
While we did not make an explicit prediction in this vein, an interesting question is
whether there would be a significant difference between the CONTROL condition and the other
conditions combined (i.e., “adjectives condition”)? A difference would support existing research
on effects of labeling as a bootstrapping tool. A lack of a difference would suggest that an
adjective-label does not provide a significant advantage in this task.
1. Piloting
Method
Participants
Participants were 30 typically developing monolingual children from the Chicagoland
area. There were 12 boys and 18 girls. Participants were recruited via the lab’s database of
interested families. Most participants were from the Evanston area, of higher socioeconomic
status, and white.
In Study 1a, 18 two and three year olds (25.6 – 37.8 months, mean age 32.0 months,
SD=4.3) participated. Six children from the original subject pool (24 children) were excluded for
never answering the questions (3), failing to complete the task due to distraction (2), and
experimenter error (1). In Study 1b, participants were 12 two and three year olds (28.6 – 36.2
months, mean age 32.2 months). One child was excluded from the original subject pool (14
children) for never answering the questions, and 1 was excluded due to experimenter error.

Measures
Study 1a: Ambiguous shapes that were deemed “blobs” by at least 50% of children were used
in Study 1b. Thirteen ambiguous shapes passed the 50% criterion. One was excluded for being
borderline and looking too similar to another shape.
Study 1b: Ambiguous shapes that were named by at least 50% of children were used in the
books for Experiment 1. All 13 blobs were named as specific objects by at least 55% of the
children (see appendix for names given).
Procedure
Piloting took place at the Project on Child Development at Northwestern University.
Children sat with a female experimenter and their parent in a private room. The task took
approximately 10 minutes.
In study 1a, children were shown a deck of “cards” with silhouettes on them. Half of the
silhouettes were those of clear objects (e.g., a dog), while the other half were ambiguous shapes
created by the experimenters (e.g., a shape that could be a blob, or could be a mitten; see
Appendix 1.1). Children were shown six example cards – three “blobs of stuff” and three
“pictures of things” and told that they were going to play a sorting game. Children were then
asked whether each card had “a blob of stuff” or “a picture of a thing” on it (see script in
Appendix 1.1).
In study 1b, children were shown silhouettes again, half of which were 13 objects from
the set in study 1a (e.g., a dog), while the other half were the 13 ambiguous shapes that met
inclusion criterion from study 1a. Children were told that all of the cards had “pictures of things
on them.” The experimenter explained that for some of the pictures, she knew what was on them,

but for some, she couldn’t tell what the picture was and needed help. Children were presented
one card at a time, and asked “What do you think this is a picture of?” (see script in Appendix
1.2).
Results
By the end of study 1a, thirteen of our ambiguous shapes had been sorted as “blobs” by at
least 50% of participating children. Because two of the shapes were perceptually similar (our
snail and whale) we eliminated one (the snail, which had a lower blob-rating). By the end of
study 1b, all 12 of the remaining shapes had been named as specific things (by new children) at
least 55% of the time.
Discussion
The above results suggest that our shapes truly were ambiguous: contingent upon the
framing of the task, the same shapes could be sorted as either “blobs of stuff” or “pictures of
things.” Thus, we found out stimuli sufficient to use in the experiment proper.
2. Experimental Manipulation
Method
Participants
Participants were 51 typically developing two- to three-year-olds (29.1 – 42.3 months,
mean age 36.0 months, SD=3.7) from the Chicagoland area. Most participants were from the
Evanston area, of higher socioeconomic status, and white. Three from the original subject pool
(53) were excluded for never answering the questions (1), or failing to complete the task due to
distraction (2). Participants were recruited via the lab’s database of interested families and via

letters sent home with parents at the preschool. There were 30 boys and 21 girls. Twelve
children had exposure to a second language at home (defined as >25% non-English heard).
Measures
Performance was measured in terms of test-object choice. Each of the 12 trials were
forced choice responses between two test items. For each participant, “percent-correct choice”
variable was created by tallying their correct responses and dividing by the total number of
responses they gave (which was almost always 12). We submitted the data to a one-way analysis
of variance (ANOVA) with condition (3) as a between subjects condition and percent-correct
choice as our dependent variable.
Procedure
The current experiment followed the logic and procedures of Waxman (2002). The
experiment took place at the Project on Child Development at Northwestern University or in a
private room in a local preschool. In both locations, participants were with the same female
experimenter. At the Project on Child Development, but not at the preschool, the child was
accompanied by his or her parent as well. The task took approximately 10 minutes. Children
looked through a book with the experimenter. Inside the book were the “blob” stimuli validated
during the pilot part of this study (Study 1a and 1b). There were two different versions of the
book, counterbalanced and showing “across basic-kind” triads (test shapes differed from the
target, e.g., two keys and a baseball cap; see appendix for full details). Twenty-six children were
shown Book 3, and 25 were shown Book 4.
In the OBJECTS condition, the experimenter explained to the child that she had a book
“full of pictures of things” and showed an example thing (a dog) and explained that there would

only be pictures of things in her book, and no blobs of stuff (showing an example blob). She then
opened to a page in the book, and pointed to the target shape, saying “Look at this picture! This
is a BLICKISH one. Can you find another one that is BLICKISH?” and then showed the two test
objects. Test objects were on a half-sheet of paper that was lifted up so that the whole triad of
shapes could be seen at once (see photo in Appendix 2.1). The test objects were different shapes
than the target shape, but the same shape as each other. The two shapes only differed in color;
one was the same color as the target (thus, embodying the BLICKISH quality) while the other was
a different color. This continued for 12 triads in each book, with a different novel adjective for
each triad. Participants were randomly assigned to one of the two versions of the book.
In the BLOBS condition, the experimenter explained to the child that she had a book “full
of “blobs of stuff” (and showed an example blob). She explained that there would only be blobs
of stuff in her book, and no pictures of things (showing the dog silhouette). She then opened to a
page in the book, and pointed to the target shape saying “Look at this blob! This is a BLICKISH
one. Can you find another one that is BLICKISH?” and then showed the two test objects. The test
objects were different shapes than the standard, but the same shape as each other. The two shapes
only differed in color; one was the same color as the target (thus, embodying the “blickish”
quality) while the other was a different color. This continued for 12 triads in each book, with a
different novel adjective for each triad. Participants were randomly assigned to one of the two
versions of the book.
In the CONTROL condition, the experimenter introduced her book as “full of pages,”
showing the example dog (“some pages are like this one”) and blob (“and some pages are like
this one”). She then opened to a page in the book, and pointed to the target shape saying “Look
at this page! Look at this one here. Can you find another one like it?” and then showed the two

test objects. This continued for 12 triads in each book. Participants were randomly assigned to
one of the two versions of the book.
Results
As expected, only the condition variable significantly predicted performance. One-way
analyses of variance indicated no effect of stimulus order, second-language exposure, or gender
on choice accuracy (all ps >.25). Additionally, a correlation analysis indicated no effect of age
(r=-.06, p=.69). A regression analysis considering all four of these factors also confirmed
condition as the only significant predictor (ß=.30, p=.047).
For the effect of condition, we hypothesized that children in the BLOBS condition would
be more likely to select the property-match than would those in either the OBJECTS or CONTROL
conditions, and that there would be no difference in the latter two conditions. To test for this
effect, we used a one-way analysis of variance (ANOVA) on participants’ choice accuracy
(likelihood of selecting the property-matched test image). The assumption of homogeneity of
variance was not met, as indicated by Levene’s test (F(2,48)=5.35 p=.008). Thus, we obtained
the Welch’s adjusted F ratio, which indicated a reliable effect of condition, F(2, 30.52)=3.811,
p=.033. Choice accuracy was near ceiling for the BLOBS condition (M=.90, SD=.17) while the
CONTROL (M=.71, SD=.25) and OBJECTS (M=.76, SD=.29) conditions showed somewhat lower
accuracy. Planned orthogonal contrasts demonstrated that, indeed, the BLOBS condition
significantly differed from the other two conditions (t(44.66)=2.65, p=.011, d=.74) while the
OBJECTS and CONTROL conditions did not significantly differ from each other (t(31.65)= -.68,
p=.50, d=.18). These findings support our prediction that perceiving a given shape as a blob,
without an object identity, facilitates adjective learning (see Figure 1).

Individual planned comparisons also supported this conclusion, with the BLOBS condition
outperforming both the OBJECTS (t(26.67)=1.67, p=.11, d=.59) and CONTROL conditions,
(t(28.36)=2.63, p=.014, d=.89). Additional nonparametric (chi-squared) comparisons were
calculated in order to determine whether each condition differed from a chance-distribution of
scores landing either above or below 50% accuracy (the accuracy rate yielded by guessing). Only
performance in the BLOBS condition significantly differed from such a chance distribution
(χ2
=8.088, P=.004, other ps>.23). Finally, a chi-square analysis comparing the OBJECTS and
BLOBS distributions on the same measure revealed a marginal difference between the OBJECTS
and BLOBS condition (χ2
=3.238, p=.072), providing converging support for the marginal
difference in group means in overall accuracy.
Taken together, these results suggest that encouraging children to view the shapes as
BLOBS, not objects, substantially increases the likelihood that they will extend novel adjectives to
shapes that differ enough to be considered, by children in the OBJECTS condition, as coming from
different basic level kinds.
----------------------------------------------------------------------
Insert Figure 1 Here
----------------------------------------------------------------------

Figure 1 | Performance differences between experimental groups. Toddlers in the
BLOBS condition successfully identified the property match more frequently than those
in the CONTROL and OBJECTS conditions.
Discussion
In this experiment, we documented an effect of conceptual knowledge on early word
learning. We had predicted that the BLOBS condition would perform better than the other
conditions, which was generally confirmed by both parametric and nonparametric analyses.
These findings suggest that when trying to extend a given shape’s properties to others differing
in shape, there is a benefit to conceiving of that shape as a blob. When shapes are described as
blobs, they do not fall victim to an object-bias, and children are better able to identify
commonalities across basic kinds. When the same shapes are described as objects, children
struggle to identify these commonalities. Furthermore, we had predicted there to be no difference
between the OBJECTS and the CONTROL conditions. Our findings supported this notion,
suggesting that the default assumption for children may be that new stimuli are “objects” (i.e., an
object-bias).

Interestingly, many more children in the THINGS and CONTROL conditions performed
above chance than did so in the original 2002 study. Indeed, this difference represents the most
substantial difference between the original and present findings. There are multiple possibilities
for this elevated overall performance. First and foremost, our stimuli were different than in the
2002 study. In the original study, the shapes varied in either color or texture on each trial,
whereas ours always varied in color only. This may have made the meaning of the adjectives
more obvious to the children in the current study: children may have learned that color was
always the property being mapped. Furthermore, due to the inclusion of texture, children were
encouraged to touch the shapes in the 2002 study, which may have been distracting. Lastly, our
shapes were computer generated and thus more standardized than those in the 2002 study, which
were cut out by hand and thus subject to more variation between each pair of “matching” shapes.
This may have increased the salience of the color dimension, as it was truly the sole
distinguishing feature.
This heightened performance in the present study may also be due to environmental
differences. In the 2002 study, all children were tested in a preschool. In our study, nearly half
were tested at the preschool and half at our research laboratory. As more variables can be
controlled in a lab, and these children were in the comforting presence of their parent, this may
have led to an advantage for these children. Other potential factors include the relative
engagement of children with the 2002 and 2016 experimenters and possible changes in
children’s home experiences in the intervening 14 years (e.g., increased emphasis on color
learning). However, it is important to note that all conditions experienced a similar increase in
accuracy across experiments, resulting in a consistent advantage for the BLOBS condition.
Limitations and Next Steps

There remains a gap in this line of reasoning: how do these “blobs of stuff” or “pictures of
things” arise in children’s everyday experience? (Children are rarely explicitly told “this is an
object” or “this is just a substance”). Without this crucial step, it is difficult to see the importance
of these findings for everyday language learning. Future studies will examine the conditions
under which children interpret images as objects (“kinds of things”) versus non-objects (“blobs
of stuff”). Rather than explicitly telling children that the picture being shown is an object or a
“blob of stuff,” the researcher could show children how it is created—a much more naturalistic
source of information about a shape’s identity
For instance, research on “artifact intention” (the intended use of a created entity) has
indicated that young children have different expectations about intentional versus accidental
events. For example, children are more likely to name a shape if it is created intentionally, as
opposed to accidentally (Gelman & Ebeling, 1998; Gelman & Bloom, 2000). Thus, one could
test whether 3-year-olds can use the intentions of a creator to identify whether an image is an
object (e.g., an ink blot that was purposely created) or a blob (e.g., the same ink blot, created as a
result of an accidental spill). Extending the findings of our current study, I would predict that this
difference will influence infants’ adjective extension in the same manner. In other words, if
children believe that the stimulus was created on purpose (and thus, was an object), they should
restrict their extension of adjectives to other objects of the same kind. However, when the
stimulus is created by accident (e.g., when someone accidentally spills the substance), they
should extend adjectives across many entities (i.e., all shapes that share the same property, such
as color).
Conclusion

Our findings suggest that there is, in fact, an effect of our conceptual manipulation on
adjective extension. Thus, contrary to John Locke’s theory, when learning adjectives, children
are not merely relying on perceptual information. Indeed, it seems that our ability to identify the
properties of a shape depends on the way in which we conceptualize it. The “blue” property we
extract from a dragonfly is different—and less flexible—than the “blue” property we extract
from a dragonfly-shaped puddle. Even if the perceptual information is one and the same. Broadly
speaking, then, conceptual information plays a key role in early word-learning.

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APPENDIX 0 : LITERATURE REVIEW
0.1 Logic of Klibanoff & Waxman (2000)
(Note: these diagrams were created by me to explain the logic of this study, and are not
actual stimuli used in the study itself)

0.2 Logic of Waxman (2002)
(Note: these diagrams were created by me to explain the logic of this study, and are not
actual stimuli used in the study itself)
0.2.1 Examples of actual stimuli used in Waxman (2002).
From left to right: a bird, a tree, a snake.

APPENDIX 1: PILOTING
1.0 Stimulus Validation Scripts
1.1 Blob/Thing Sorting
Hey (NAME), look! This book is full of pictures of things (used Tana Hoban’s Of Colors and
Things book). Like this one (choose an example in the book). Is that a picture of a thing? Yeah!
And what about this one, is this a picture of a thing? Yeah it is! These are all pictures of things.
Okay great. So, I have a bunch of different cards. On some of them, they have pictures of things,
like this one! (show dog). That’s a picture of a dog, right?
And on some of my cards, there aren’t pictures of things. They are just blobs of stuff. Like this
one! (show blob). That’s just a blob of stuff, right?
Work through 4 more guided examples (2 things, 2 blobs).
You’re good at this! Okay, let’s look at more of my cards! I need you to help me decide if each
card has a picture of a thing on it, or just a blob of stuff. Are you ready? Great!
Do you think this one is a blob of stuff? What about this one? (etc.)
Great! Thank you for all of your help!
1.2 Thing Naming
Okay (NAME), I have to tell you something. I have a problem. Do you think you can help me?
Great! Thank you! So, I have a problem. I have all of these cards. See? Well, all of these cards
have pictures on them. Right?
Well, some of them I know what the picture is of – like this one. That’s a (show dog) right?
Good job.
But here’s my problem. Some of the cards, I can’t tell what the picture is! Like this one…. can
you help me? What do you think this is a picture of?
Thank you! You are such a good helper. I’m going to write that down. Do you think you could
help me with some more?
[REPEAT]
Great! Thank you for all of your help!

1.1 Ambiguous Shapes
“key” “mitten” “whale” “spoon”
“hammer” “flashlight” “baseball hat” “ice cream cone”
“car” “flag” “dragonfly” “key”

1.2 “Thing” Names
How children named the shapes when presented as “pictures of things.” We made sure
that shapes that were given the same name were not put in a triad together for the
experiment.

APPENDIX 2: Experimental Manipulation
2.0 Experiment Script
Pictures of Things:
Introduction:
Hey [NAME]! Look, I have a book. Wanna see?
Okay but first, let me show you what's gonna be inside my book! (*use two cards - blob
and dog). My book is full of pictures of things. Like this one (point at dog). This is a
picture of a dog! Right? My book DOESN'T have any blobs of stuff like this one, nope
(point to blob, shake head). My book ONLY has pictures of things like this one (point at
dog again, smile and nod).
Wanna look at my book now?
Task:
Look at this picture! (point at target). This is a [BLICKISH] one. Can you find another
one that is [BLICKISH]? (lift up test items page)
Thank you for helping!
(etc)
No Word:
Introduction:
and dog). My book is full of pages. Like this one (point at dog - switch between using
blob first vs thing first). See? My book has some pages like this one (point at blob,
nod). And my book has some pages like this one (point at dog again, nod).
Wanna look at my book now?
Task:
Look at this page! Look at this one here. (point at target) Can you find another one like
it? (lift up test items page).
(etc)
Blobs of Stuff:
Introduction:
and dog). My book is full of blobs of stuff. Like this one (point at blob). This is just a
blob of stuff. Right? My book DOESN'T have any pictures of things like this one, nope
(point at dog, shake head). My book ONLY has blobs of stuff like this one (point at blob
again, nod).
Wanna look at my book now?  
Task:
Look at this blob! This is a [BLICKISH] one. Can you find another one that is
[BLICKISH]?
(etc)

2.0.1 Adjectives Used
From Klibanoff & Waxman,
2000
Adapted from Yoshida &
Hanania, 2013
Adapted from Mintz &
Gleitman, 2002
Blickish (KEY) Toop(ish) (DRAGONFLY) rup(ish) (MITTEN)
dakish (HAMMER) Vap(ish) (BASEBALL HAT) drin(ish) (FLASHLIGHT)
zavish (ICE CREAM CONE) Stoof(ish) (FLAG) prall(ish) (WHALE)
wuggish (SPOON)
feppish (CAR)
talish (COMB)
2.1 Example Triad

2.2 Book Organization

Margaret Shavlik Thesis

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