The Distribution and Features of Semantic Clusters Within Reading Selections of Core Reading...

The Distribution and Features of Semantic

Clusters Within Reading

Selections of Core Reading Programs

Elfrieda H. HiebertTextProject & University of

California, Santa Cruz

Typical Vocabulary of Core Reading Programs: Narrative

Text

Houghton Mifflin Harcourt (HMH)

Scott Foresman (SF)

creptdullgloriousheritagemasterpiecememoryruinedstreaktowersyanked

cardboardfeastfierceflightspitcherruinedstoopstreasure

Me and Uncle Romie (Hartfield, 2002)

*Rare*Words are not in the target text

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Establishing Number of Untaught, Rare Words within Core Reading Programs

(Gr. 3, “Big 3)(Hiebert, AERA, 2014)

Narrative Informational

Total rare words

1,832 1551

Taught, rare words

195 106

Untaught, rare words

1,637 1,4453

Possible Semantic Relationships

towertowers—hightowers—9-11towers—watertowers—climbtowers—LegosEiffel Tower

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Another direction: Semantic Clusters

“Semantic clusters are categories that contextualize terms according to their meaning, use, and relation to other words. Semantic clusters allow teachers to give direct instruction for groups of words clustered around a specific topic, rather than trying to address each word individually.”

(Marzano, 2004)

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Marzano & Marzano’s

Semantic Clusters (1988)

7,230 words commonly found in elementary school texts, drawing on lists compiled by Carroll et al., 1971; Dahl, 1979; Harris & Jacobsen, 1972

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Example of a Marzano & Marzano Supercluster/Cluster/Mini-Cluster

(target word: tower)

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Substantial Changes since Marzano & Marzano’s (1988)

effortsDigital Thesaurus

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Visual Thesaurus

9

The Megacluster Project

10


11


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And 3 additional clusters:

Proper nounsAbbreviations/contractionsNon-English words

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In the current studyFor the rare vocabulary of the texts from three core, grade-three reading programs: How similar/different are the megaclusters in narrative and informational texts?

How well do the megaclusters for specific texts connect to the themes/content of the texts?

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Data Source: Gr 3 Anthology Selections from 3 Core Reading

ProgramsTexttype

Tokens Types

Rare Types*

Rare Tokens

Houghton Mifflin Harcourt (2011)

Nar 19,412 2,825

641 1,710

Info 11,533 2035 342 657McGraw-Hill (2012) Nar 18,168 3,53

3616 1,264

Info 9,529 2,099

402 816

Scott Foresman (2013)

Nar 21,113 3,312

913 1,866

Info 12,782 2,676

603 1,032

*Rare Words are designated as those with fewer than 10 predicted appearances per 1,000,000 words of text (as defined by Brysbaert & New, 2009). 16

Data Source: Gr 3 Anthology Selections from 3 Core Reading

ProgramsTexttype

Tokens Types

Rare Types*

Rare Tokens

Houghton Mifflin Harcourt (2011)

Nar 19,412 2,825

641 1,710

Info 11,533 2035 342 657McGraw-Hill (2012) Nar 18,168 3,53

3616 1,264

Info 9,529 2,099

402 816

Scott Foresman (2013)

Nar 21,113 3,312

913 1,866

Info 12,782 2,676

603 1,032

*Rare Words are designated as those with fewer than 10 predicted appearances per 1,000,000 words of text (as defined by Brysbaert & New, 2009). 17

Distribution of Three Primary Clusters (Social, Physical,

Other): Programs

Social Physical Other0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

HMH MH SF 18

Distribution of Three Primary Clusters (Social, Physical,

Other): Text Types

Social Physical Other0

10

20

30

40

50

60

Narrative Informational 19

How similar/different are the megaclusters

in narrative and informational texts?

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Megaclusters: Social ConstructsText

Attitudes

Communi-cation

Social Values

Roles/Jobs

Actions

Physical Fea-

tures

TOTAL

Nar .06 .13 .03 .05 .09 .06 .41

Info .03 .07 .04 .07 .08 .08 .35

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Megaclusters: Social ConstructsText

Attitudes

Communi-cation

Social Values

Roles/Jobs

Actions

Physical Fea-

tures

TOTAL

Nar .06 .13 .03 .05 .09 .06 .41

Info .03 .07 .04 .07 .08 .08 .35

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Megaclusters of Physical Environment Huma

n Bo

dy

Dwel

ling

s

Wate

r/We

ather

Land

/Veg

etatio

n

Phys

ical

Scie

nce

Food

Anim

als

Mach

ines

Soci

alCons

truc

tions

Tota

l

Nar .04 .04 .03 .04 .02 .09 .03 .07 .05 .42

Info .03 .05 .03 .04 .05 .04 .13 .08 .05 .49

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Megaclusters of Physical Environment Huma

n Bo

dy

Dwel

ling

s

Wate

r/We

ather

Land

/Veg

etatio

n

Phys

ical

Scie

nce

Food

Anim

als

Mach

ines

Soci

alCons

truc

tions

Tota

l

Nar .04 0.04 0.03 .04 .02 .09 0.03 .07 .05 .42

Info .03 .05 .03 .04 .05 .04 .13 .08 .05 .49

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How similar/different are the megaclusters in narrative and

informational texts?Conclusion:

At least with trade books, certain megaclusters are represented similarly in the rare words in narrative and informational texts. Shared megaclusters are more frequent for megaclusters in the social domain than for those in the physical domain.

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How well do the megaclusters relate to

critical themes of passages?

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Typical Vocabulary of Core Reading Programs: Narrative

Text

Houghton Mifflin Harcourt (HMH)

Scott Foresman (SF)

creptdullgloriousheritagemasterpiecememoryruinedstreaktowersyanked

cardboardfeastfierceflightspitcherruinedstoopstreasure

Me and Uncle Romie (Hartfield, 2002)

*Rare*Words are not in the target text

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Content of Megacluster

# Words in Megacluster

Average Age of Acquisition

Concreteness

Proper Nouns, slang, abbreviations, onomatopoeia

13 N/A N/A

Motion 12 6.1 3.5Art, music, & sports 10 7.6 4.5

Food & Flowers 11 6.01 4.8

Places & parts of Places

9 7.7 4.6

Features of Physical Things

5 8.1 3.4

Misc 3 6.6 3.2Total Rare Words 63

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Concreteness

Proper Nouns, slang, abbreviations, onomatopoeia

13 N/A N/A

Motion 12 6.1 3.5Art, music, & sports 10 7.6 4.5

Food & Flowers 11 6.01 4.8

Places & parts of Places

9 7.7 4.6


5 8.1 3.4

Misc 3 6.6 3.2Total Rare Words 63

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Synopsis of Me and Uncle Romie James travels from south to stay with his uncle and aunt in New York City for summer. Uncle Romie is absent, working on his art behind closed doors. Aunt Nanette gives James a tour of New York City. On James’s birthday, Aunt Nanette goes to a funeral and James feels sorry for himself. But that morning he finally gets to see Uncle Romie’s art—which has captured everything that James has loved about New York City.

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Typical Vocabulary of Core Reading Programs: Informational

TextPenguin Chick, Tatham, 2001

MG SFechoes frozendown preenhuddle cuddlesshuffles snugglesfierce flipperswhips hatchjunior pecks•Rare

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Concreteness

Motion 13 7.5 4.0Animals & Their Features 8 7.6 4.5


6 7.0 3.2

Communication 3 5.9 4.9Places & parts of Places 2 13.5 N/A

Proper Nouns, slang, abbrev., onomatopoeia

1 N/A N/A

Total Rare Words 33

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Concreteness

Motion 13 7.5 4.0Animals & Their Features 8 7.6 4.5


6 7.0 3.2

Communication 3 5.9 4.9Places & parts of Places 2 13.5 N/A

Proper Nouns, slang, abbrev., onomatopoeia

1 N/A N/A

Total Rare Words 33

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Synopsis of Penguin Chick

This title focuses on one emperor penguin family's survival. The parents' care of their young is central, shown by deft yet perfunctory watercolors depicting a harsh, challenging habitat. The danger of the baby's starvation is emphasized; one adult must keep it protected from the elements and the other must fish for food and return in time to feed it before it dies. Trading places, the caregivers share these duties until the chick is old enough for both adult birds to hunt for food together.

School Library Journal, 2002 36

How well do the megaclusters relate to critical themes of

passages?Conclusion:

The megaclusters with substantial members of rare words and with appropriate levels of age of acquisition appear to connect to the themes in both a narrative and an informational example.

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Questions/LimitationsHow can multiple-meaning words be captured in the megacluster approach? Examples: stoops in Me and Uncle Romie; trumpets in Penguin Chick

To what degree can highly frequent and moderately frequent words within a megacluster assist in learning the rare words?

For how many of the words within a taught cluster are meanings of words recognized subsequently?

Does instruction of words in clusters aid in closing the vocabulary gap? [At the same time, students’ performances would suggest that teaching 6-8 relatively unconnected words from a text does not close the vocabulary gap.] 38

Conclusion: In conclusion, any program of direct vocabulary instruction ought to be conceived in full recognition that it can cover only a small fraction of the words that children need to know. Trying to expand children's vocabularies by teaching them words one by one, ten by ten, or even hundred by hundred would appear to be an exercise in futility. Vocabulary instruction ought, instead, to teach skills and strategies that would help children become independent word learners.

Nagy and Anderson (1984), p. 328

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