Search for Magical Solutions

Loading...

From the course by University of California, Santa Cruz

Children Acquiring Literacy Naturally

25 ratings

Explore Related Videos

At Coursera, you will find the best lectures in the world. Here are some of our personalized recommendations for you

University of California, Santa Cruz

Children Acquiring Literacy Naturally

25 ratings

In this short course you will explore the possibility that children might acquire written language in a way that is similar to how they acquire spoken language—without instruction. You will encounter various aspects of behavioral science and technology that are relevant to this proposition. You will have the opportunity to learn the the perceptual, cognitive, and neurological capacities of children during their first years of life. You will advance your understanding of children and how they learn language. You will also be more attuned to current advances in the technology of human machine interactions, and what these phenomena imply for learning to read at an early age.

From the lesson

Week 3 Reading, Early Reading, and Technological Innovations

The nature of reading, reading myths, current approaches to teaching reading, demographics of literacy and illiteracy, and technological innovations.

Measuring Reading Skill6:24

How We Perceive Letters and Words9:22

Reading Words5:24

Search for Magical Solutions6:51

Testing Top-Down Influences6:59

Meet the Instructors

Dr. Dominic William Massaro
Research Professor
Psychology

[MUSIC]

In the spirit of finding a magical solution,

one could ask whether whole word shape, word length, and the first and

last letters provides sufficient information for reading words.

Only 9% of the thousand most frequent words in American English

are uniquely defined by their first and last letters.

Adding the number of letters in a word, increased this percentage to 40%.

It should be noted, however,

that word length isn't such an easy property to pick up

given the difference in length of the letters and proportional spacing.

Compare the words ill and wow, or lilly and women.

Note that the five letter word,

lilly, is not longer than the three letter word wow.

When exterior letters, interior word shape, and word length are considered

as features, 75% of the thousand most frequent words are uniquely described.

At first glance, you might believe that three out of four times is not bad.

Succeeding at this strategy,

however, requires the reader to accurately recognize all three variables.

This is not a trivial amount of processing to bypass a strategy,

simply of recognizing the letters of the word.

We have pursued a misguided endeavor, and conclude that readers must

necessarily recognize words, based on the letters that make them up.

In fact, there's evidence that the probability of identifying a word

is a function of the probability of identifying each

of it's individual letters.

Although, there are no readily apparent shortcuts to successfully reading words,

we have not yet accounted for the ease of word recognition.

What is it about words that make them so easy to recognize by the expert reader?

The primary reason is that we use multiple sources of information

in domains of pattern recognition, such as reading.

Many sources of non-visual information supplement the information

from the letters.

In our infamous paragraph, syntactic and

semantic constraints facilitated its reading.

We would have expected less skilled readers to have much more

trouble with the paragraph,

ostensibly because they have less of this top down knowledge.

Another important source of information in word recognition

is knowledge about the spelling orthography of the language.

We call this information orthographic structure.

Claude E. Shannon gave a formal description of orthographic structure.

He was an American mathematician, electronic engineer, and

cryptographer who founded information theory.

It should be noted that orthographic structure refers to the constraints

within the written language,

independently of how the orthography predicts the pronunciation.

This later metric is usually called spelling to sound correspondence.

And languages can differ in the degree to which the orthography

predicts pronunciation.

As it's well known, English is notorious for its unpredictability.

And spelling reform has more or less been continuously advocated,

without success since written English began.

The controversy and research on this topic

are another story that must be postponed until another time.

We saw earlier

that neighboring letters can interfere with each other because of crowding.

This occurs because fundamental visual processes.

However, neighboring letters can also inform one another

in the hands, or should I say eyes, of a knowledgeable reader.

Consider the puzzle of guessing a word.

This demonstration shows that leaders are capable of recognizing words

based on partial information from the letters that make the words up.

Where do readers get this information?

They have read many, many words, and

have learned about their statistical occurrences.

It is possible to analyze large databases of text

to determine these statistical regularities, and

then ask, to what extent they are used by readers.

Peter Norvik analyzed all of the words occurring in all of the books

scanned by Google.

Given this huge database,

we now have a good measure of how letters occur in written English.

One must feel relieved, that only slightly less than 100,000 words,

were found in over 743 trillion words.

The graph shows the frequency of occurrence of single letters.

As expert scrabble players can attest,

it is instructive that there is such a disparity in the occurrence of letters,

with the letter E occurring about 139 times more often than the letter Z.

In reading, however, this base rate frequency may not be important.

Most likely, we can expect that a good statistical measure of the orthography

will include both letter patterns, and their position in words.

In addition, we can expect the statistical predictability of letter patterns

to be greater at the beginning, and at the end of words, rather than in the middle.

The graphic shows frequent letter patterns in initial and final position of words.

Many of these patterns are frequent in initial position,

but not in final position, and vice versa.

[MUSIC]

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.

Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.

© 2019 Coursera Inc. All rights reserved.

Download on the App Store

Get it on Google Play