Language Development

Please check your grammar, sentence structure, and thought process – as this assignment is language focused 😉

Please watch the video attached above – it deals with a classic case study known as Genie the Wild Child

It’s 55 minutes long and really interesting.

ALSO:-  Read the attached Article:    TheEarlyCatastrophe(1).pdf


  1. Discuss the case study (video) with reference to the key arguments on language development that are covered in your book, and the video, namely the critical period vs the sensitive period, and the behavioral approach vs the LAD approach (Noam Chomsky). How do these ideas clash and combine with this case.    
  2. Use the article to assist in discussing how language acquisition affects other aspects of development.
  3. What are your take away thoughts about language development – does this case answer the questions?  If not, why?  What else do we need etc. make sure to use peer reviewed journal research to support your arguments. Do not use direct quotes from the article, only paraphrase and cite accordingly.
  4. Each assignment is worth 25 points. Approx. 1000 words is  ~ 4 pages in length.
  • Follow basic APA formatting i.e. 12pt font (Times or Arial), double spaced, 1 inch margins. You do not need a cover page but you must cite references in APA style.
  • Be clear, and concise, but thorough in order to expect full points.
  • Use three (3) peer reviewed journal articles to support your arguments/claims. The book can be used as an extra resource (the book also provides several resources to look up).

The Early Catastrophe

The 30 Million Word Gap by Age 3

By Betty Hart and Todd R. Risley

D uring the 1960’s War on Poverty, we were among the many researchers, psychologists, and educators who brought our knowledge of child development to the front line in an optimistic effort to intervene early to forestall the terrible effects that poverty was having on some children’s academic growth. We were also among the many who saw that our results, however promising at the start, washed out fairly early and fairly completely as children aged.

In one planned intervention in Kansas City, Kans., we used our experience with clinical language in tervention to design a half-day program for the Turner House Preschool, located in the impoverished Juniper Gardens area of the city. Most interventions of the time used a variety of methods and then measured results with IQ tests, but ours focused on building the everyday language the children were using, then evaluating the growth of that language. In addition, our study included not juSt poor children from Turner House, but also a group of University of Kansas professors’ children against whom we could measure the Turner House children’s progress.

All the children in the program eagerly engaged with the wide variety of new materials and language-intensive activi­ ties introduced in the preschool. The spontaneous speech data we collected showed a spurr of new vocabulary words

Betty Hart is professor ofHuman Development at the Univer­ sity ofKansas and senior scientist at the Schiefelbusch Institute for Life Span Studies. Todd R. Risley is professor in the Depart­ ment ofPsychology at the University ofAlaska Anchorage and director ofAlaska’s Autism Intensive Early Intervention Project. The two have collaborated on research projects for more than 35 years. This article is excerpted with permission from Mean­ ingful Differences in the Everyday Experiences of Young American Children, © 1995, Brookes; www.brookespublish­; 1-800-638-3775; $29.00.

added to the dictionaries of all the children and an abrupt acceleration in their cumulative vocabulary growth curves. But just as in other early intervention programs, the in­ creases were temporary.

We found we could easily increase the size of the chil­ dren’s vocabularies by teaching them new words. But we could not accelerate the rate of vocabulary growth so that it would continue beyond direcr teaching; we could not change the developmental trajectory. However many new words we taught the children in the preschool, it was clear that a year later, when the children were in kindergarten, the effects of the boost in vocabulary resources would have washed our. The children’s developmental trajectories of vo­ cabulary growth would continue to point to vocabulary sizes in the future that were increasingly discrepant from those of the professors’ children. We saw increasing disparity between the extremes-the fast vocabulary growth of the professors’ children and the slow vocabulary growth of the Turner House children. The gap seemed to foreshadow the findings from other studies that in high school many children from families in poverty lack the vocabulary used in advanced textbooks.

Rather than concede to the unmalleable forces of hered­ ity, we decided that we would undertake research that would allow us to understand the disparate developmental trajecto­ ries we saw. We realized that if we were to understand how and when differences in developmental trajectories began, we needed to see what was happening to children at home at the very beginning of their vocabulary growth.

We undertook 2 1/2 years of observing 42 families for an hour each month to learn aboU[ what typi­cally went on in homes with 1- and 2-year-old children learning to talk. The data showed us that ordinary families differ immensely in the amount of experience with





language and interaction they regularly provide their chil­ dren and that differences in children’s experience are strongly linked to children’s language accomplishments at age 3. Our goal in the longitudinal study was to discover what was happening in children’s early experience that could account for the intractable difference in rates of vocabulary growth we saw among 4-year-olds.

Methodology Our ambition was to record “everything” that went on in children’s homes-everything that was done by the children, to them, and atound them. Because we were committed to undertaking the labor involved in observing, tape recording, and transcribing, and because we did not know exactly which aspects of children’s cumulative experience were con­ tributing to establishing rates of vocabulary growth, the more information we could get each time we were in the home the more we could potentially learn.

We decided to start when the children were 7-9 months old so we would have time for the families to adapt to obser­ vation before the children actually began talking. We fol­ lowed the children until they turned three years old.

The first families we recruited to participate in the study came from personal contacts: friends who had babies and families who had had children in the Turner House Preschool. We then used birth announcements to send de­ scriptions of the study to families with children of the de­ sired age. In recruiting from birth announcements, we had [wo priorities. The first priority was to obtain a range in de­ mographics, and the second was stability-we needed fami­ lies likely to remain in the longitudinal study for several years. Recruiting from birth announcements allowed us to preselect families . We looked up each potential family in the city directory and listed those with such signs of permanence as owning their home and having a telephone. We listed families by sex of child and address because demographic status could be reliably associated with area of residence in this city at that time. Then we sent recruiting letters selec­ tively in order to maintain the gender balance and the repre­ sentation of socioeconomic strata.

Our final sample consisted of 42 families who remained in the study from beginning ro end. From each of these fam­ ilies, we have almost 2 1/ 2 years or more of sequential monthly hour-long observations. On the basis of occupa­ tion, 13 of the families were upper socioeconomic status (5E5), 10 were middle 5E5 , 13 were lower 5E5, and six were on welfare. There were African-American families in each 5E5 category, in numbers roughly reflecting local job alloca­ tions. One African-American family was upper 5E5, three were middle, seven were lower, and six families were on wel­ fare. Of the 42 children, 17 were African American and 23 were girls. Eleven children were the first born to the family, 18 were second children, and 13 were third or later-born children.

What We Found Before children can take charge of their own experience and begin to spend time with peers in social groups outside the home, almost everything they learn comes from their fami­


Eighty-six percent to 98 percent

of the words recorded in each

child’s vocabulary consisted

ofwords also recorded

in their parents’ vocabularies.





lies, to whom society has assigned the task of soc ializing children. We were not surprised to see the 42 children turn out to be like their parents; we had no t fully realized, how­ ever, the implications of those similari ties for the children’s futures.

We observed the 42 children grow more like their par­ ents in stature and activity levels, in vocabulary resources, and in language and interaction styles . Despite the consid­ erable range in vocabulary size among the children, 86 per­ cent to 98 percent of the words recorded in each child’s vo­ cabulary consisted of words also recorded in their parents’ vocabularies. By the age of 34-36 months , the children were also talking and using numbers of differen t words very similar to the averages of their parents (see the table below).

By the time the children were 3 years old, trends in amount of talk, vocabulary growth, and style of interaction were well established and clearly suggested widening gaps to come. Even patterns of parenting were already observable among the children . When we listened to the children, we seemed to hear their parents speaking; when we watched the children play at parenting their dolls, we seemed to see the futures of their own children.

Families’ Language and Use Differ Across Income Groups


12 Professional 23 Working.class 6 Welfare

Measures and scores Paren! Child Pateur Child Paten! Child

Pretest score’ 41 31 14 Recorded vocabulary

Size 2,176 1,116 1,498 749 974 525 Average utterances

per hour” 487 310 301 223 176 168 Average d ifFerem

words per hour 382 297 25 1 216 167 149 ‘When we began the longitudinal study, we asked rhe parents to complete a vocabu· lary ptetest. At the first observa tion each paren t was asked to complete a fotm abo stracted from the Peabody Picture Vocabu lary Test (PPVT ). We gave each parent a list of 46 vocabulary words and a seties of pictures (fou r options per vocabulary word) and asked the paten t to write beside each word the number of the picture rhar corresponded ro the wrirren word . Parenr performance on [he resr was highly correlated with years of ed ucation (r = .57).

‘Parent u[(erances and different words were averaged over 13-36 months of child age. Child utterances and different wotds were ave raged for the four observarions when the child ren were 33·36 months old .

We now had answers to our 20-year-old questions . We had observed, recorded , and analyzed more than 1,300 hours of casual interactions berween parents and their lan­ guage-learning children. We had dissembled these interac­ tions into several dozen molecular features that could be reli­ ably coded and counted. We had examined the correlations berween the quantities of each of those features and several outcome measures relating to children’s languageaccom­ plishments. .

After all 1,318 observations had been entered into the computer and checked for accuracy against the raw data, after every word had been checked for speJling and coded and checked for its part of speech, after every utterance had been coded for syntax and discourse function and every code checked for accuracy, after random samples had been re-


~ ~ ~ “‘ ~

coded to check the reliability of the coding, after each file had been checked one more time and the accuracy of each aspect verified, and after the data analys is programs had fi­ nally been run to produce frequency counts and dictionary lists for each observation, we had an immense numeric database that required 23 million bytes of computer file space. We were flllally ready to begin asking what it all meant.

It took six years of painstaking effort before we saw the first results of the longitudinal research. And then we were astonished at the differences the data revealed (see the graph below).

Children’S Vocabulary Differs Greatly



‘E'” 0 3

800 ‘5 ‘” ~


~ 0 > Ql > 600 ~ ‘5

~ 0



10 12 14 16 18 20 22 24 26 28 30 32 34 36

Age of child in monlhs

Like the children in the Turner House Preschool, the three year old children from families on welfare not only had smaller vocabularies than did children of the same age in professional families, but they were also add ing words more slowly. Projecting the developmental trajectory of the welfare children’s vocabulary growth curves, we could

. see an ever-widening gap similar to the one we saw berween the Turner House children and the professors’ children in 1967.

While we were immersed in collecting and processing the data, our thoughts were concerned only with the next utterance to be transcribed or coded. While we were ob­ serving in the homes, though we were aware that the fami­ lies were very different in lifestyles, they were all similarly engaged in the fundamental task of raising a child. All the families nurtured their children and played and talked with them . They all disciplined their children and taught them good manners and how to dress and toilet themselves. They provided their children with much the same toys and talked to them about much the same things. Though dif­ ferent in personality and skill levels, the children all learned to talk and to be socially appropriate members of the family with all the basic skills needed for preschool entry.


Across Income Groups 13 higher SES children

” (profeSSional)

23 middle/lower· SES children (working·class)

6 children from families on welfare

, ,



Test Performance in Third Grade Follows Accomplishments at Age 3 We wondered whether the differences we saw at age 3 would be washed out, like the effects of a preschool intervention, as the children’s experience broadened to a wider community of competent speakers. Like the parents we observed, we wondered how much difference children’s early experiences would actually make. Could we, or parents, predict how a child would do in school from what the parent was doing when the child was 2 years old?

Fortune provided us with Dale Walker, who recruited 29 of the 42 families to participate in a study of their children’s school performance in the third grade, when the children were nine to 10 years old.

We were awestruck at how well our measures of accom­ plishments at age 3 predicted measures of language skill at age 9-10. From our preschool data we had been confident that the rate of vocabulary growth would predict later per­ formance in school; we saw that it did . For the 29 children observed when they were 1-2 years old, the rate of vocabu­ lary growth at age 3 was strongly associated with scores at age 9-10 on both the Peabody Picture Vocabulary Test-Re­ vised (PPVT-R) of receptive vocabulary (r = .58) and the Test of Language Development-2: Intermediate (TOLD) (r = .74) and its subtests (listening, speaking, semantics, syntax).

Vocabulary use at age 3 was equally predictive of measures of language skill at age 9-10. Vocabulary use at age 3 was strongly associated with scores on both the PPVT-R (r = .57) and the TOLD (r = .72). Vocabulary use at age 3 was also strongly associated with reading comprehension scores on the Comprehensive Test of Basic Skills (CTBS/U) (r= .56).

The 30 Million Word Gap By Age 3 All parent-child research is based on the assumption that the data (laboratory or field) reflect what people typically do. In most studies, there are as many reasons that the averages would be higher than reponed as there are that they would be lower. But all researchers caution against extrapolating their findings to people and circumstances they did not in­ clude. Our data provide us, however, a first approximation to the absolute magnitude of children’s early experience, a basis sufficient for estimating the actual size of the interven­ tion task needed to provide equal experience and, thus, equal opportunities to children living in poverty. We depend on future studies to refIne this estimate.

Because the goal of an intervention would be to equalize children’s early experience, we need to estimate the amount of experience childten of different SES groups might bring to an intervention that began in preschool at age 4. We base our estimate on the remarkable differences our data showed in the relative amounts of children’s early experience: Simply in words heard, the average child on welfare was having half as much experience per hour (616 words per hour) as the av­ erage working-class child (1,251 words per hour) and less than one-third that of the average child in a professional family (2,153 words per hour). These relative differences in


amount of experience were so durable over the more than two years of observations that they provide the best basis we currently have for estimating children’s actual life experience.

A linear extrapolation from the averages in the observa­ tional data to a 100-hour week (given a 14-hour waking day) shows the average child in the professional families with 215,000 words of language experience, the average child in a working-class family provided with 125,000 words, and the average child in a welfare family with 62,000 words of language experience. In a 5,200-hour year, the amount would be 11 .2 million words for a child in a profes­ sional family, 6.5 million words for a child in a working­ class family, and 3.2 million words for a child in a welfare family. In four years of such experience, an average child in a professional family would have accumulated experience with almost 45 million words, an average child in a working-class family would have accumulated experience with 26 million words, and an average child in a welfare family would have accumulated experience with 13 million words. By age 4, the average child in a welfare family might have 13 million fewer words of cumulative experience than the average child in a working-class family. This linear extrapolation is shown in the graph below.

The Number of Words Addressed to Children Differs Across Income Groups

50 million Professional

~ 40 million

i’! “0 “0

‘”<n 1:’ o ~


. ~ ;;; :; E ::J

“”0 OJ ;;;


~ w

o 12 24 36 48 Age of child in months


But the children’s language experience did not differ just in terms of the number and quality of words heard. We can extrapolate similarly the relative differences the data showed in children’s hourly experience with parent affirmatives (en­ couraging words) and prohibitions. The average child in a professional family was accumulating 32 affirmatives and five prohibitions per hour, a ratio of 6 encouragements to 1 discouragement. The average child in a working-class fam­ ily was accumulating 12 affirmatives and seven prohibitions per hour, a ratio of 2 encouragements to 1 discouragement. The average child in a welfare family, though, was accumu­ lating five affirmatives and 11 prohibitions per hour, a ratio of 1 encouragement to 2 discouragements. In a 5,200-hour year, that would be 166,000 encouragements to 26,000 dis­ couragements in a professional family, 62,000 encourage­ ments to 36,000 discouragements in a working-class family, and 26,000 encouragements to 57,000 discouragements in a welfare family.




In four years, an average child in a

professional family would

accumulate experience with almost

45 million words, an average child in

a working-class family 26 million

words, and an average child in a

welfare family 13 million words,


Extrapolated [Q the first four years of life, the average child in a professional family would have accumulated 560,000 more instances of encouraging feedback than dis­ couraging feedback, and an average child in a working-class family would have accumulated 100,000 more encourage­ menrs than discouragemenrs. But an average child in a wel­ fare family would have accumulated 125,000 more instances of prohibitions than encouragemenrs. By the age of 4, the average child in a welfare family might have had 144,000 fewer encouragemenrs and 84,000 more discouragemenrs of his or her behavior than the average child in a working-class family.

Extrapolating the relative differences in children’s hourly experience allows us [Q estimate children’s cumulative experi­ ence in the first four years of life and so glimpse the size of the problem facing inrervenrion. Whatever the inaccuracy of our estimates, it is not by an order of magnitude such that 60,000 words becomes 6,000 or 600,000. Even if our esti­ mates of children’s experience are [00 high by half, the dif­ ferences between children by age 4 in amounrs of cumula­ tive experience are so great that even the best of intervention programs could only hope [0 keep the children in families on welfare from falling still further behind the children In the working-class families.

The Importance of Early Years Experience We learned from the longitudinal data that the problem of skill differences among children at the time of school entry is bigger, more inrractable, and more important than we had thought. So much is happening to children during their first three years at home, at a time when they are especially mal­ leable and uniquely dependent on the family for virtually all their experience, that by age 3, an intervention must address not just a lack of knowledge or skill, but an entire general approach [0 experience.

Cognitively, experience is sequential: Experiences in in­ fancy establish habits of seeking, noticing, and incorporating new and more complex experiences, as well as schemas for categorizing and thinking about experiences. Neurologically, infancy is a critical period because cortical developmenr is influenced by the amounr of central nervous system activity stimulated by experience. Behaviorally, infancy is a unique time of helplessness when nearly all of children’s experience is mediated by adults in one-to-one interactions permeated with affect. Once children become independent and can speak for themselves, they gain access to more opportunities for experience. But the amount and diversity of children’s past experience influences which new opportunities for ex­ perience they notice and choose.

Estimating, as we did, the magnitude of the differences in children’s cumulative experience before the age of 3 gives an indication of how big the problem is . Estimating the hours of inrervenrion needed [0 equalize children’s early experience makes clear the enormity of the effort that would be re­ quired to change children’s lives. And the longer the effort is put off, the less possible the change becomes. We see why our brief, intense efforts during the War on Poverty did not succeed. But we also see the risk to our nation and its chil­ dren that makes intervenrion more urgenr than ever. 0