Maria: Explaining football

Chapter one: Introductory level

Task one: Transcribe

Transcribe the clip, according to the published conventions (PDF, 158MB).

Response sheet - Maria (PDF, 137KB)

Use ‘A’ for utterances made by the adult, and ‘YP’ for utterances made by the young person.

Transcript conventions

The following conventions for transcribing speech are taken from ten Have, 2007, and are the conventions which we have used in our transcriptions.

Sequencing marks

[

A single left bracket indicates the point of overlap onset (where the second speaker begins speaking before the first has finished). For example:

A: did I tell you what happened yesterday when I went to the shop

B: [no what happened

=

Equal signs, one at the end of one line and one at the beginning of the next, indicate no 'gap' between the two lines: the second speaker begins speaking at the moment that the first speaker finishes.

Timed intervals

(0.0)

Numbers in brackets indicate elapsed time in silence by tenths of seconds. Thus, (5.6) is a silence of 5 seconds and 6-tenths of a second.

(.)

A dot in brackets indicates a tiny 'gap' within or between utterances.

Characteristics of speech production

word

Underlining indicates some form of stress, via the pitch or loudness of the utterance. An alternative method is to print the stressed part in italics.

::

Colons indicate prolongation of the sound immediately before. Multiple colons indicate a more prolonged sound.

-

A dash indicates that the speaker's speech is cut off abruptly. For example:

A: but then I-

.,?

Punctuation marks are used to indicate characteristics of speech production, especially intonation. They are NOT referring to grammatical units. See below.

.

A full stop indicates a stopping fall in tone: the speech sounds as if the speaker is indicating the end of their speech by lowering the pitch they are speaking at.

,

A comma indicates a continuing intonation, like when you are reading items from a list.

?

A question mark indicates a rising intonation, not a question. For example:

A: I'm reading a great book at the moment?

The absence of an utterance-final marker indicates that the speech did not end with a particular intonation or change in intonation: the speaker did not raise their pitch, or lower it, or sound particularly as if they intended to finish or continue speaking.

¯

Arrows indicate marked shifts into higher or lower pitch in the utterance-part immediately following the arrows. For example, the second part of this phrase would be uttered at a significantly higher pitch than the first:

A: then he said perhaps ­which he knows really annoys me

WORD

Upper-case letters indicate sounds which are particularly loud in relation to the surrounding talk (perhaps shouted).

°

Utterances or utterance-parts bracketed by degree sounds are relatively quieter than the surrounding talk. For example:

A: so I went in and °don't say anything but°I'm going to buy it there instead

< >

Right/left carets bracketing an utterance or utterance-part indicate speeding up

.hhh

A dot-prefix row of 'h's indicates an inbreath. Without the dot, the 'h's indicate an outbreath.

w(h)ord

A bracketed (h), or row of (hhh)s, within a word indicates breathiness as in laughter, crying etc.

Transcriber's doubts and comments

( )

Empty brackets indicate the transcriber's inability to hear what was said. The length of the bracketed space indicates the length of the untranscribed talk. In the 'speaker' designation column, empty brackets indicate inability to identify a speaker.

(word)

Bracketed words are especially dubious hearings or speaker identifications.

(())

Double brackets contain transcriber's descriptions rather than, or in addition to, transcribed speech.

ten Have, P. (1999). Doing conversation analysis: A practical guide. London, Sage.

Task one feedback: transcript

A: right (0.8) what’s your favourite game.

YP: ((yawns)) (2.5) I don’t know none

A: what games do you like to play

YP: football.

A: brilliant what I’m gonna ask you to do now then is, can you tell me,

YP: [you want me to name a football player

A: no I’ve got no idea about football players what I’d like you to do (.) is explain to me how you play football with as much detail as you can so I don’t I actually don’t know anything (.) about football .hhh so

YP: [you kick it into a goal, you just shoot it at people, er no you don’t you kick it at the person who you’re aiming at

A: mm

YP: er (1.8) don’t kick it through windows like I do, ((laughs))

A: [yeah

YP: ((coughs)) er (2) windows (1.5) °hang on a minute I’m trying to think (0.3) when did I play football I played it with my mates°

A: ok so describe to me, (.) everything you can about the game football so how you play it, what you need to do to win, what the rules are,

YP: wear a uni-wear a erm football t-shirt and football shorts. a kit I meant to say.

A: [mm

A: ok

YP: [er can’t remember..° it’s hard to think this° ((breathes in)) dududududu (4.2) the rules is not to kick each other (1.5) and swear at each other that’s not a good rule,

A: mm

YP: [.hhh erm (1.8) when somebody gets injured wait until the person comes and sorts them out.

A: right yeah

YP: that’s the goalkeep-no it’s not the goalkeeper it’s the referee.

A: mmhmm

YP: or manager

A: mhm

YP: and don’t start a fight after a game like some people do

A: no ( ) so what do you have to do to be really good at football.

YP: errr you have to have the energy for it.

A: mhm

YP: you have to do a lot of training to .hh (0.8) a lot of training to do football like Sheffield United does a right lot of training but then they turn round and say they’re crap afterwards

A: right (0.5) .hh and what do you do to win.

YP: erm score a goal ((laughs))

A: - yep is that all

YP: yeah and then you win a trophy afterwards if you get to the penalties, er get to the erm what’s it called,

A: (2.7) - I think it is penalties isn’t it?

YP: yeah and trophy awards I can’t remember what it’s called now.

A: - ( ) is that the word you’re thinking of

YP: yeah (1) think it’s called that? do you ever watch Match of the Day.

A: I don’t no I don’t know anything about football,

YP: I got to see the torch last night on the tv,

A: - ooh brilliant

YP: [it was on the tv (0.8) the torch was on the tv from Sheffield.

A: cool (.) did you see you on the tv were you on there too

YP: no an I seen this bloke carrying the torch from a different place.

A: mm

YP: [this one who’s doing the Olympic thing

A: right yeah

YP: the one who’s got no legs. he has got legs but it’s like them plastic ones.

A: yeah (1.8) ok (1.6) erm and can you tell me why why football’s your favourite game.

YP: [((yawns))

YP: cos I like to kick a ball around.

A: yeah

YP: (1.8) cos if I don’t kick a ball around I kick walls instead ((laughs))

A: [I don’t believe that

YP: .hh I kick the walls instead of kicking a ball and that’s how you injure your foot.

A: - but you look so - calm

YP: (2) not after I-no at home if we haven’t got a football at home I boot the wall

A: wow

YP: [and that’s why I’ve made a mess of the wall.

A: I bet you have I bet

Task two: Analyse

Using the analysis technique described by Marilyn Nippold analyse your transcription.

Speech sample analysis (based on Marilyn Nippold) (PDF, 132KB)
Online version available below.

Refer to the Glossary (PDF, 292KB) for an explanation of ‘subordinate clauses’. Note down the following information:

  • Total number of T-units (‘main clauses’)

  • Total number of fragments

  • Total number of words

  • Mean length of T-unit

  • Total number of subordinate clauses (relative (RC), adverbial (AVC), nominal (NC))

  • Clausal density (total clauses/total T-units)

Example of how to carry out this analysis below.

Chapter 1 Advanced level: sample analysis (PDF, 165MB)

Speech sample analysis, based on Marilyn Nippold (online version)

Analysis of a sample of a young person’s expository discourse can give information about the language structures used by the young person. Clausal density and T-units are types of complex language structures which are expected in expository discourse:

Clausal density refers to the number of subordinate clauses (see glossary) used within the sample.

T-units are defined as any independent clause (‘main clause’), including any dependent subordinate clauses. Thus, ‘you choose a colour’ and ‘you choose the colour you would like to be when you are playing this game against your friend who also has to choose a colour’ are both T-units. The first has no dependent clauses, whereas the second has many: ‘you choose the colour / you would like / to be /when you are playing this game / against your friend / who also has to choose a colour’.

When analysing expository discourse we also need to identify fragments. These are partial T-units, which lack a component such as the verb or the object (where required). For example, if the participant says ‘you play it with a… you choose a colour’, only the clause ‘you choose a colour’ is a T-unit. The phrase ‘you play it with a…’ is NOT a T-unit because it is missing the final object: it is a fragment.

In order to analyse your transcribed expository discourse sample:

1. Break the written sample into T-units. For the purposes of analysis, ignore any partial T-units (fragments). Ignore “and” and separate such sentences into separate T-units (eg “I did this and he did that” gives 2 T-units: “I did this” “he did that”). Also ignore “well”, “erm” and repetitions (eg “er when the um ba-when the um ball isn’t hit in the pocket” becomes “when the ball isn’t hit in the pocket”).

2. Identify all subordinate clauses. Classify them as: relative (RC), adverbial (AVC) or nominal (NC).

3. Calculate the clausal density by adding the number of all clauses (independent [=T-units], relative, adverbial and nominal) and dividing this by the number of Tunits. Thus, a sentence with higher clausal density will have a higher figure than a sentence with lower clausal density.

4. In addition, further information can be gathered as follows:

Once you have established the total number of T-units, add up the total number of complete words used in the T-units. Divide the total word number by the number of T-units to calculate the mean T-unit length.

5. Also, note down the number of fragments (incomplete T-units) in the speech sample.

When you have done this for a number of samples, you can begin to compare the samples to each other. We have included a sample transcription to show you how to carry out this analysis. We have also included data from five participants whose video clips are not shown in Teen Talk. You can use this data to compare the data that you will analyse from the video clips.

In addition, it may be useful for you to know that Nippold et al.’s findings from their 2005 study suggest that, for a typically-developing group of 17-year-olds (roughly akin to our sample participants), the normative figure for mean T-unit length is 10.59, and for clausal density is 1.56.

Based on: Nippold, M. A., Hesketh, L. J., Duthie, J. K., Mansfield, T. C. (2005) Conversational versus expository discourse: A study of syntactic development in children, adolescents, and adults. Journal of Speech, Language, and Hearing Research. 48, 1048-1064.

Chapter one: Advanced level - Sample analysis (online version)

(Natalie)

Transcription, as used for analysis:

A: so (.) what we’d like you to do now is think of a favourite game or sport.

YP: [yeah

YP: game

A: yep could be anything,

YP: uno?

A: >>oh that’s a good one ok (1.8) so can you tell me why Uno is your favourite game

YP: cos it’s numeracy and it’s funny cos you win and when somebody gets

A: [mm

YP: two cards and they have to pick it up and four cards (1.2) and they change the colour

A: [yeah

A: ok that’s interesting .hh can you tell us now, can you imagine that we don’t know anything about uno .hh and can you describe to us how you play it, (1) what the rules are. =

YP: =I >>don’t think I can remember them

A: just it doesn’t matter if you get them wrong but just have a go as much as you can

YP: err you play with two or four players, (1.8) the rules is not to cheat, (1.5) err (2.7) to start with the num-the whatever car-number card it is, (.) if it’s green you put down the green n (.) so on (.) err (2.5) so if there-if you’re down to the last ( ) card you shout uno (1.6) so it’s quite a good ?game

A: and (.) how do you win.

YP: when you get all rid of your cards

A: (1.5) and how do you do that.

YP: when you shout uno (.) but if you didn’t-but if you don’t shout uno before you pick up ?two cards.

A: (1.8) I remember that now .hh ok so what do you have to do (.) erm to be really good at uno.

YP: patience (.) practice sorry-practice.

A: mm?

YP: quite a lot of things actually I quite enjoy it.

A: mmhm? (1.6) so you have to have practice? anything else?=

YP: =I can’t remember now I’ve not played it for a while

A: mm.

ANALYSIS

  1. Break the written sample into T-units. For the purposes of analysis, ignore any partial T-units (fragments). Ignore ‘and’, and separate such sentences into separate T-units (eg ‘I did this and he did that’ gives 2 T-units: ‘I did this’; ‘he did that’). Also ignore ‘well’, ‘erm’ and repetitions (eg ‘er when the um ba-when the um ball isn’t hit in the pocket’ becomes ‘when the ball isn’t hit in the pocket’).

This gives Natalie's transcription as:

  1. cos it’s numeracy

  2. it's funny cos you win

  3. when somebody gets two cards and they have to pick it up and four cards and they change the colour

  4. I don't think I can remember them

  5. you play with two or four players

  6. the rules is not to cheat, to start with the whatever the number card it is

  7. if it's green you put down the green and so on

  8. so if you're down to the last (unclear) card you should uno

  9. so it's quite a good game

  10. when you get all rid of your cards

  11. when you shout uno

  12. if you don't shout uno before, you pick up two cards

  13. I quite enjoy it

  14. I can't remember now

  15. I've not played it for a while

Total T-units=15

Note: lines 1, 10 and 11 are not T-units because they don't feature a subject. However, they are functioning as T-units because they are uttered in response to a question: the 'subject' is implied by the question and so doesn't need to be repeated in the response.

2. Identify all subordinate clauses. Classify them as: relative (RC), adverbial (AVC) or nominal (NC).

Using the following colour scheme:

relative clause

adverbial clause

nominal clause

Natalie's transcription is:

  1. cos it’s numeracy

  2. it's funny cos you win

  3. when somebody gets two cards and they have to pick it up and four cards and they change the colour

  4. I don't think I can remember them

  5. you play with two or four players

  6. the rules is not to cheat, to start with the whatever the number card it is

  7. if it's green you put down the green and so on

  8. so if you're down to the last (unclear) card you should uno

  9. so it's quite a good game

  10. when you get all rid of your cards

  11. when you shout uno

  12. if you don't shout uno before, you pick up two cards

  13. I quite enjoy it

  14. I can't remember now

  15. I've not played it for a while

Total subordinate clauses: 8 (0 RC, 6 AVC, 2 NC)

3. Calculate the clausal density by adding the number of all clauses (independent [=T-units], relative, adverbial and nominal) and dividing this by the number of T-units.

Clausal density (total clauses/total T-units (=’main clauses’)): 23/15=1.53

4. Add up the total number of complete words used in the T-units. Divide the total word number by the number of T-units to calculate the mean T-unit length.

Total number of words: 128

Mean length of T-unit: 128/15=8.53 words

5. Note down the number of fragments (incomplete T-units) in the speech sample.

Number of fragments: 2 (' patience (.) practice sorry-practice'; ' quite a lot of things actually')

Thus, our analysis data for Natalie is as follows:

  • Total number of T-units: 15

  • Total number of fragments: 2

  • Total number of words: 128

  • Mean length of T-unit: 8.53 words

  • Total number of subordinate clauses: 8 (0 relative, 6 adverbial, 2 nominal)

  • Clausal density (total clauses/total T-units (=’main clauses’)): 23/15=1.53

Task two feedback

  • Total number of T-units: 41

  • Total number of fragments: 6

  • Total number of words: 326

  • Mean length of T-unit: 7.95 words

  • Total number of subordinate clauses: 17 (3 RC, 12 AVC, 2 NC)

  • Clausal density: 58/41=1.41

Fragments

-a right lot of training

-get to the

-and trophy awards

-think it’s called that

-this one who’s doing the Olympic thing

-the one who’s got no legs

Subordinate clauses: RC

6 who you’re aiming at

13 carrying the torch from a different place

15 not to kick each other and swear at each other

Subordinate clauses: AVC

7 like I do

17 when somebody gets injured

17 until the person comes and sorts them out

21 after a game

21 like some people do

23 to do football like Sheffield United does

26 if you get to the penalties

30 last night on the tv

32 from Sheffield

37 if I don’t kick a ball around

38 instead of kicking a ball

Subordinate clauses: NC

2 to name a football player

28 it’s called now

Task three: Comment

Comment on your analysis, with reference to the language structures you would expect to observe in the expressive language of older children and young adults at secondary school age, using our data for comparison.

Data for comparison (PDF, 130KB)

Data for comparison (online version)

In order for you to make sense of the information which you have just analysed, we will provide data from five further participants to enable you to make meaningful comparisons. We will also include information on what you would expect from a ‘typically developing’ group of participants for you to refer to; this data is taken from Nippold et al.’s 2005 study.

To compare your data to other data from our sample of young people with language disorder, use the information below.

Participant 1
Total T-units: 29
Mean length of T-unit (wds): 9.2
Clausal density: 1.55

Participant 2
Total T-units: 18
Mean length of T-unit (wds): 6.67
Clausal density: 1.56

Participant 3
Total T-units: 41
Mean length of T-unit (wds): 9.96
Clausal density: 1.39

Participant 4
Total T-units: 15
Mean length of T-unit (wds): 6.00
Clausal density: 1.20

Participant 5
Total T-units: 15
Mean length of T-unit (wds): 8.53
Clausal density: 1.53

To analyse our participants’ language samples in relation to what you would expect from a typically developing young person, use the information below, taken from Nippold et al.’s 2005 study. Nippold’s study used participants who were considered typical language users (that is, they showed no evidence of any speech, language or communication need and had not been identified as having language disorder at any point in their education) from a number of age groups.

They used the expository discourse task to analyse the participants’ language use. Their findings are summarised below. Please note, only the mean (average) result is shown here, for the purposes of comparison and analysis within this Teen Talk task.

Measure: Age 8
Total T-units: 33.05
Mean length of T-unit: 8.59
Clausal density: 1.42

Measure: Age 11
Total T-units: 33.30
Mean length of T-unit: 9.29
Clausal density: 1.45

Measure: Age 13
Total T-units: 36.15
Mean length of T-unit: 8.68
Clausal density: 1.42

Measure: Age 17
Total T-units: 44.00
Mean length of T-unit: 10.59
Clausal density: 1.56

Measure: Age 25
Total T-units: 51.55
Mean length of T-unit: 11.04
Clausal density: 1.54

Measure: Age 44
Total T-units: 60.55
Mean length of T-unit: 11.46
Clausal density: 1.59

Based on: Nippold, M. A., Hesketh, L. J., Duthie, J. K., Mansfield, T. C. (2005) Conversational versus expository discourse: A study of syntactic development in children, adolescents, and adults. Journal of Speech, Language, and Hearing Research. 48, 1048-1064.

Task three feedback

Maria's mean T-unit length (at 7.95) is somewhat lower than some of the other participants. Her clausal density (at 1.41) is only slightly below the group’s mean (at 1.45). Two of Maria’s fragments (“this one who’s doing the Olympic thing” and “the one who’s got no legs”) also contain relative clauses.

Using normative data from Nippold et al.’s 2005 study, we see that Marias mean T-unit length (at 7.95) is significantly lower than the mean for her typically-developing age-matched peers (at 10.59). Her clausal density is also lower than for her typically-developing age-matched peers (at 1.56), but less so. This, along with the data from the transcription regarding the types of subordinate clauses which Maria uses, suggests that she is capable of producing complex language, although this may be seen less in Marias language than in others.

Summary task

  • What have you learned from completing this task?

  • What questions do you have following this set of tasks?

  • How do you plan to address these questions? What are your next steps?

  • How can you apply your learning in your practice?

  • How could you use expository discourse, and analysis of expository discourse, in your setting?

  • How can your learning in this task help you in working with young people with language disorder?

No feedback.