Common Core Standard For English Language Arts (Page 7 of 43) in pdf

Common Core State StandardS for engliSh language artS & literaCy in hiStory/SoCial StudieS, SCienCe, and teChniCal SubjeCtS

Quantitative Measures of Text Complexity

A number of quantitative tools exist to help educators assess aspects of text complexity that are better measured

by algorithm than by a human reader. The discussion is not exhaustive, nor is it intended as an endorsement of one

method or program over another. Indeed, because of the limits of each of the tools, new or improved ones are needed

quickly if text complexity is to be used effectively in the classroom and curriculum.

Numerous formulas exist for measuring the readability of various types of texts. Such formulas, including the widely

used Flesch-Kincaid Grade Level test, typically use word length and sentence length as proxies for semantic and

syntactic complexity, respectively (roughly, the complexity of the meaning and sentence structure). The assump-

tion behind these formulas is that longer words and longer sentences are more difficult to read than shorter ones; a

text with many long words and/or sentences is thus rated by these formulas as harder to read than a text with many

short words and/or sentences would be. Some formulas, such as the Dale-Chall Readability Formula, substitute word

frequency for word length as a factor, the assumption here being that less familiar words are harder to comprehend

than familiar words. The higher the proportion of less familiar words in a text, the theory goes, the harder that text is

to read. While these readability formulas are easy to use and readily available—some are even built into various word

processing applications—their chief weakness is that longer words, less familiar words, and longer sentences are not

inherently hard to read. In fact, series of short, choppy sentences can pose problems for readers precisely because

these sentences lack the cohesive devices, such as transition words and phrases, that help establish logical links

among ideas and thereby reduce the inference load on readers.

Like Dale-Chall, the Lexile Framework for Reading, developed by MetaMetrics, Inc., uses word frequency and sentence

length to produce a single measure, called a Lexile, of a text’s complexity. The most important difference between the

Lexile system and traditional readability formulas is that traditional formulas only assign a score to texts, whereas the

Lexile Framework can place both readers and texts on the same scale. Certain reading assessments yield Lexile scores

based on student performance on the instrument; some reading programs then use these scores to assign texts to

students. Because it too relies on word familiarity and sentence length as proxies for semantic and syntactic complex-

ity, the Lexile Framework, like traditional formulas, may underestimate the difficulty of texts that use simple, familiar

language to convey sophisticated ideas, as is true of much high-quality fiction written for adults and appropriate for

older students. For this reason and others, it is possible that factors other than word familiarity and sentence length

contribute to text difficulty. In response to such concerns, MetaMetrics has indicated that it will release the qualita-

tive ratings it assigns to some of the texts it rates and will actively seek to determine whether one or more additional

factors can and should be added to its quantitative measure. Other readability formulas also exist, such as the ATOS

formula associated with the Accelerated Reader program developed by Renaissance Learning. ATOS uses word dif-

ficulty (estimated grade level), word length, sentence length, and text length (measured in words) as its factors. Like

the Lexile Framework, ATOS puts students and texts on the same scale.

A nonprofit service operated at the University of Memphis, Coh-Metrix attempts to account for factors in addition to

those measured by readability formulas. The Coh-Metrix system focuses on the cohesiveness of a text—basically, how

tightly the text holds together. A high-cohesion text does a good deal of the work for the reader by signaling relation-

ships among words, sentences, and ideas using repetition, concrete language, and the like; a low-cohesion text, by

contrast, requires the reader him- or herself to make many of the connections needed to comprehend the text. High-

cohesion texts are not necessarily “better” than low-cohesion texts, but they are easier to read.

The standard Coh-Metrix report includes information on more than sixty indices related to text cohesion, so it can be

daunting to the layperson or even to a professional educator unfamiliar with the indices. Coh-Metrix staff have worked

to isolate the most revealing, informative factors from among the many they consider, but these “key factors” are not

yet widely available to the public, nor have the results they yield been calibrated to the Standards’ text complexity

grade bands. The greatest value of these factors may well be the promise they offer of more advanced and usable

tools yet to come.

Reader and Task Considerations

The use of qualitative and quantitative measures to assess text complexity is balanced in the Standards’ model by the

expectation that educators will employ professional judgment to match texts to particular students and tasks. Numer-

ous considerations go into such matching. For example, harder texts may be appropriate for highly knowledgeable or

skilled readers, and easier texts may be suitable as an expedient for building struggling readers’ knowledge or reading

skill up to the level required by the Standards. Highly motivated readers are often willing to put in the extra effort re-

quired to read harder texts that tell a story or contain information in which they are deeply interested. Complex tasks

may require the kind of information contained only in similarly complex texts.

Numerous factors associated with the individual reader are relevant when determining whether a given text is ap-

propriate for him or her. The RAND Reading Study Group identified many such factors in the 2002 report Reading for

Understanding:

The reader brings to the act of reading his or her cognitive capabilities (attention, memory, critical analytic

ability, inferencing, visualization); motivation (a purpose for reading, interest in the content, self-efficacy as

a reader); knowledge (vocabulary and topic knowledge, linguistic and discourse knowledge, knowledge of

Common Core Standard For English Language Arts Page 7

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