Syntactic variables Syntactic variables in pupils' writings:in pupils' writings:

a comparison of hand-a comparison of hand-writtenwritten

and PC-written textsand PC-written textsBård Uri JensenBård Uri Jensen

University of Bergen / Hedmark University of Bergen / Hedmark University CollegeUniversity College

ContentsContents

PurposePurpose Background theoryBackground theory Presentation of text corpusPresentation of text corpus Research questionsResearch questions ResultsResults DiscussionDiscussion

Purpose / AimPurpose / Aim

Pupils’ writing in school by hand or Pupils’ writing in school by hand or on PCon PC

Does production mode affect Does production mode affect syntax ? syntax ?

Syntactic variablesSyntactic variables Lexical variablesLexical variables

Background theory / previous Background theory / previous researchresearch

Word processingWord processingRussell 1999Russell 1999

Harrington, Shermis & Rollins 2000 Harrington, Shermis & Rollins 2000 Kellogg & Mueller 1993Kellogg & Mueller 1993

Computer-mediated communicationComputer-mediated communicationBaron 1998Baron 1998

Crystal 2001Crystal 2001Hård av Segerstad 2002Hård av Segerstad 2002

Production speedProduction speedHorowitz & Berkowitz 1964Horowitz & Berkowitz 1964

Written and spoken languageWritten and spoken language differences resulting from production speeddifferences resulting from production speed

Allwood 1998Allwood 1998Biber 1988Biber 1988

Halliday 1989Halliday 1989

Research questionsResearch questions

How are the following variables How are the following variables affected by production mode in pupils’ affected by production mode in pupils’ writing?writing? Lexical densityLexical density Lexical diversityLexical diversity Rate of subordinationRate of subordination

Biber 1988, Halliday 1989Biber 1988, Halliday 1989

Rate of modal particlesRate of modal particles Rate of certain kinds of topic markersRate of certain kinds of topic markers

Faarlund, Lie & Vannebo 1997Faarlund, Lie & Vannebo 1997

Research questionsResearch questions

How are the following variables How are the following variables affected by production mode in pupils’ affected by production mode in pupils’ writing?writing? Lexical densityLexical density

Rate of subordinationRate of subordinationBiber 1988, Halliday 1989Biber 1988, Halliday 1989

Rate of modal particlesRate of modal particles

Faarlund, Lie & Vannebo 1997Faarlund, Lie & Vannebo 1997

Text collectionText collection 20 pupils in 11th year (16 years old)20 pupils in 11th year (16 years old) Three hours writing sessionThree hours writing session

little opportunity for revision / rewritinglittle opportunity for revision / rewriting No Internet connectionNo Internet connection

Text A Text A (Day 1)(Day 1)

Text B Text B (Day 2)(Day 2)

Pupil Pupil 1-101-10

HandHand PCPC

Pupil Pupil 11-2011-20

PCPC HandHand

Text lengthText length

Subordination Subordination (independent clauses)(independent clauses)

Subjunction countSubjunction count At, om, som, fordi, når, så, hvis, hvordanAt, om, som, fordi, når, så, hvis, hvordan, …, …

That, whether, which/that, because, when, so that, That, whether, which/that, because, when, so that, if, how, …if, how, …

ÅÅ (+ infinitive) (+ infinitive) ToTo (+ infinitive) (+ infinitive)

Traces of Traces of somsom and and atat..1)1) Han sa Han sa <<atat>> han skulle komme. han skulle komme.

He said He said <<thatthat>> he would come. he would come.2)2) Bilen Bilen <<somsom>> jeg kjører, er en Toyota. jeg kjører, er en Toyota.

The car The car <<thatthat>> I drive is a Toyota. I drive is a Toyota.

(Question-type(Question-type3)3) Hadde jeg ikke kommetHadde jeg ikke kommet,, ville det ikke ha skjedd. ville det ikke ha skjedd.

Had I not comeHad I not come,, it would not have happened it would not have happened..))

Results: SubordinationResults: Subordination

Significant differences in subordinations Significant differences in subordinations by number of (graphic) sentences.by number of (graphic) sentences.

One-way ANOVAOne-way ANOVA

s<.05s<.05 HandHand PCPC

MeanMean 1.151.15 1.451.45

Modal particlesModal particles Jo, vel, nok,Jo, vel, nok, da, nå, visst da, nå, visst

Jo = Jo = Known to both sender and receiver.Known to both sender and receiver.1)1) Jeg kjører Jeg kjører jojo Toyota. Toyota.

I drive a Toyota, I drive a Toyota, youyou knowknow.. Vel = Vel = Uncertainty and appeals to Uncertainty and appeals to

receiver’s knowledge.receiver’s knowledge.2)2) Jenter leser Jenter leser velvel mer bøker. mer bøker.

Girls read books more, Girls read books more, don’t theydon’t they?? Nok = Nok = Expresses probability.Expresses probability.

3)3) Gutter driver Gutter driver noknok mer med data. mer med data.I thinkI think boys use their computer more. boys use their computer more.Boys Boys probablyprobably use their computer more. use their computer more.

Modal particles and text Modal particles and text typetype

Frequency per 1000 wordsFrequency per 1000 words No significant differences related to production No significant differences related to production

modemode Jo, nokJo, nok are slightly more frequent in PC-texts are slightly more frequent in PC-texts VelVel is slightly less frequent in PC-text is slightly less frequent in PC-text

Significant mean differences as function of question Significant mean differences as function of question

One-way One-way ANOVA, s<.05ANOVA, s<.05 Text AText A Text BText B

Mean / Mean / 10001000 8.38.3 3.03.0

Modal particles and text Modal particles and text lengthlength

Significant positive correlation:Significant positive correlation: Difference in rate of modal particles with Difference in rate of modal particles with

production modeproduction mode Total text length produced by pupilTotal text length produced by pupil Pearson’s correlation 0.57, s<.01Pearson’s correlation 0.57, s<.01

Pupils who generally write long texts use Pupils who generally write long texts use more modal particles in PC-textsmore modal particles in PC-texts

Pupils who write long texts:Pupils who write long texts: have good writing skills?have good writing skills? are motivated?are motivated? utilise speed to produce ”fluently”?utilise speed to produce ”fluently”? get carried away?get carried away?

Results: Lexical densityResults: Lexical density

Ratio of lexical words to total wordsRatio of lexical words to total words Nouns, adjectives and verbsNouns, adjectives and verbs Minus function verbs Minus function verbs å ha (to have), å være (to be)å ha (to have), å være (to be) Lexical adverbs not includedLexical adverbs not included

Production mode alone shows no influenceProduction mode alone shows no influence Significant negative correlation betweenSignificant negative correlation between

Difference in lexical density between production Difference in lexical density between production modesmodes

Difference in text length between production Difference in text length between production modesmodes

Pearson’s correlation -.61, s<.01Pearson’s correlation -.61, s<.01 No correlation with total text length!No correlation with total text length!

DiscussionDiscussion

Problem Problem ofof grammaticalgrammatical unitunit DifferentiatingDifferentiating betweenbetween differentdifferent

categoriescategories ofof pupilspupils text lengthtext length text length differencetext length difference

Corpus Corpus sizesize PupilsPupils’ ’ knowledgeknowledge ofof norms? norms?

ReferencesReferences Allwood, Jens (1998). Some Frequency based Differences between Spoken and Allwood, Jens (1998). Some Frequency based Differences between Spoken and

Written Swedish. In proceedings from Written Swedish. In proceedings from the XVI:th Scandinavian Conference of the XVI:th Scandinavian Conference of LinguisticsLinguistics,,

Department of Linguistics, University of TurkuDepartment of Linguistics, University of Turku Baron, N. S. (1998). Letters by phone Baron, N. S. (1998). Letters by phone or speech by other means: the linguistics of email. or speech by other means: the linguistics of email. Language & Communication, Language & Communication, 1818(2), 133-170.(2), 133-170.

Biber, D. (1988). Biber, D. (1988). Variation across speech and writingVariation across speech and writing. New York: Cambridge . New York: Cambridge University Press.University Press.

Crystal, D. (2001). Crystal, D. (2001). Language and the InternetLanguage and the Internet. Cambridge: Cambridge University . Cambridge: Cambridge University Press.Press.

Faarlund, J. T., Lie, S., og Vannebo, K. I. (1997). Faarlund, J. T., Lie, S., og Vannebo, K. I. (1997). Norsk referansegrammatikkNorsk referansegrammatikk. Oslo: . Oslo: Universitetsforlaget.Universitetsforlaget.

Halliday, M. A. K. (1989). Halliday, M. A. K. (1989). Spoken and written languageSpoken and written language (2nd ed.). (2nd ed.). Oxford: Oxford Oxford: Oxford University Press.University Press.

Harrington, S., Shermis, M. D., og Rollins, A. L. (2000). The influence of word Harrington, S., Shermis, M. D., og Rollins, A. L. (2000). The influence of word processing on English placement test results. processing on English placement test results. Computers and Composition, 17Computers and Composition, 17(2), (2), 197-210.197-210.

Horowitz, M. W., og Berkowitz, A. (1964). Horowitz, M. W., og Berkowitz, A. (1964). Structural advantage of the mechanism of Structural advantage of the mechanism of spoken expression as a factor in differences in spoken and written expression. spoken expression as a factor in differences in spoken and written expression. Perceptual and motor skills, 19Perceptual and motor skills, 19, 619-625., 619-625.

Hård af Segerstad, Y. (2002). Hård af Segerstad, Y. (2002). Use and Adaptation of Written Language to the Use and Adaptation of Written Language to the Conditions of Computer-mediated Communication.Conditions of Computer-mediated Communication. Göteborg University, Göteborg. Göteborg University, Göteborg.

Kellogg, R. T., og Mueller, S. (1993). Kellogg, R. T., og Mueller, S. (1993). Performance amplification and process Performance amplification and process restructuring in computer-based writing. restructuring in computer-based writing. International Journal of Man-Machine International Journal of Man-Machine Studies, 39Studies, 39(1), 33-49.(1), 33-49.

Russell, M. (1999). Testing on computers: A follow-up study comparing performance Russell, M. (1999). Testing on computers: A follow-up study comparing performance on computer and on paper. on computer and on paper. Education Policy Analysis Archives, 7Education Policy Analysis Archives, 7(20).(20).

Corpus sizeCorpus size

Difficult to obtain significanceDifficult to obtain significance Some substantial differences / Some substantial differences /

correlationscorrelations Less substantial differences may be Less substantial differences may be

significant in a larger corpus.significant in a larger corpus.

Unit of measurementUnit of measurement Basic principle:Basic principle:

Number of occurances per possible places of Number of occurances per possible places of useuse

SubordinationSubordination Per graphic sentence (i.e. between <. ! ?>)Per graphic sentence (i.e. between <. ! ?>) Should be per independent clause.Should be per independent clause.

Requires time-consuming manual analysis.Requires time-consuming manual analysis. Modal particlesModal particles

Per 1000 wordsPer 1000 words Should be per indpendent clauseShould be per indpendent clause

Lexical densityLexical density Per total number of wordsPer total number of words

Knowledge of normsKnowledge of norms

Long sentences,Long sentences, Independent clauses often piled onto Independent clauses often piled onto

each othereach other Without conjunctionsWithout conjunctions Without full stopsWithout full stops Without commas, sometimesWithout commas, sometimes

Often seem quite oral in natureOften seem quite oral in nature If pupils don’t know the norms, can’t If pupils don’t know the norms, can’t

be expected to strive towards thembe expected to strive towards them Maybe differences will only show in Maybe differences will only show in

pupils with good writing skills?pupils with good writing skills?

Categorization of pupilsCategorization of pupils

Results: Lexical diversityResults: Lexical diversityDistribution of word Distribution of word

frequencyfrequency WrittenWritten

10 words = 19%10 words = 19% 50 words = 38%50 words = 38%10.000 words = 87%10.000 words = 87%

HandHand 10 words = 10 words = 24%24% 50 words = 50 words = 53%53%700 words = 700 words = 91%91%

SpokenSpoken 10 words = 23%10 words = 23%

50 words = 52%50 words = 52%

10.000 words = 97%10.000 words = 97%Allwood Allwood

19981998

PCPC 10 words = 10 words = 24%24% 50 words = 50 words = 53%53%700 words = 700 words = 90%90%

Hand Hand PCPC11 detdet itit 4,004,00 4,04,0 detdet itit 4,014,01 4,04,0

22 erer isis 3,813,81 7,87,8 erer isis 3,623,62 7,67,6

33 ogog andand 3,173,17 11,011,0 ogog andand 3,363,36 11,011,0

44 somsom that (adj)that (adj) 2,302,30 13,313,3 somsom that (adj)that (adj) 2,292,29 13,313,3

55 ikkeikke notnot 2,192,19 15,515,5 åå to (inf.)to (inf.) 2,242,24 15,515,5

66 ii inin 1,911,91 17,417,4 påpå onon 1,891,89 17,417,4

77 påpå onon 1,841,84 19,219,2 atat that (subs)that (subs) 1,831,83 19,219,2

88 atat that (subs)that (subs) 1,711,71 21,021,0 ikkeikke notnot 1,761,76 21,021,0

99 åå to (inf.)to (inf.) 1,701,70 22,722,7 dede theythey 1,741,74 22,722,7

1010 dede theythey 1,651,65 24,324,3 forfor forfor 1,631,63 24,424,4

1111 jegjeg II 1,581,58 25,925,9 enen a/ana/an 1,481,48 25,825,8

1212 medmed withwith 1,411,41 27,327,3 jegjeg II 1,451,45 27,327,3

1313 enen a/ana/an 1,331,33 28,628,6 ii inin 1,421,42 28,728,7

Hand Hand PCPC11 detdet itit 4,004,00 4,04,0 detdet itit 4,014,01 4,04,0

22 erer isis 3,813,81 7,87,8 erer isis 3,623,62 7,67,6

33 ogog andand 3,173,17 11,011,0 ogog andand 3,363,36 11,011,0

44 somsom that (adj)that (adj) 2,302,30 13,313,3 somsom that (adj)that (adj) 2,292,29 13,313,3

55 ikkeikke notnot 2,192,19 15,515,5 åå to (inf.)to (inf.) 2,242,24 15,515,5

66 ii inin 1,911,91 17,417,4 påpå onon 1,891,89 17,417,4

77 påpå onon 1,841,84 19,219,2 atat that (subs)that (subs) 1,831,83 19,219,2

88 atat that (subs)that (subs) 1,711,71 21,021,0 ikkeikke notnot 1,761,76 21,021,0

99 åå to (inf.)to (inf.) 1,701,70 22,722,7 dede theythey 1,741,74 22,722,7

10 de they 1,65 24,3 for for 1,63 24,4

1111 jegjeg II 1,581,58 25,925,9 enen a/ana/an 1,481,48 25,825,8

1212 medmed withwith 1,411,41 27,327,3 jegjeg II 1,451,45 27,327,3

1313 enen a/ana/an 1,331,33 28,628,6 ii inin 1,421,42 28,728,7

Hand Hand PCPC11 detdet itit 4,004,00 4,04,0 detdet itit 4,014,01 4,04,0

22 erer isis 3,813,81 7,87,8 erer isis 3,623,62 7,67,6

33 ogog andand 3,173,17 11,011,0 ogog andand 3,363,36 11,011,0

44 somsom that (adj.)that (adj.) 2,302,30 13,313,3 somsom that (adj.)that (adj.) 2,292,29 13,313,3

55 ikkeikke notnot 2,192,19 15,515,5 åå to (inf.)to (inf.) 2,242,24 15,515,5

66 ii inin 1,911,91 17,417,4 påpå onon 1,891,89 17,417,4

77 påpå onon 1,841,84 19,219,2 atat that (subs)that (subs) 1,831,83 19,219,2

88 atat that (subs)that (subs) 1,711,71 21,021,0 ikkeikke notnot 1,761,76 21,021,0

99 åå to (inf.)to (inf.) 1,701,70 22,722,7 dede theythey 1,741,74 22,722,7

1010 dede theythey 1,651,65 24,324,3 forfor forfor 1,631,63 24,424,4

1111 jegjeg II 1,581,58 25,925,9 enen a/ana/an 1,481,48 25,825,8

1212 medmed withwith 1,411,41 27,327,3 jegjeg II 1,451,45 27,327,3

1313 enen a/ana/an 1,331,33 28,628,6 ii inin 1,421,42 28,728,7

Hand Hand PCPC11 detdet itit 4,004,00 4,04,0 detdet itit 4,014,01 4,04,0

22 erer isis 3,813,81 7,87,8 erer isis 3,623,62 7,67,6

33 ogog andand 3,173,17 11,011,0 ogog andand 3,363,36 11,011,0

44 somsom that (adj.)that (adj.) 2,302,30 13,313,3 somsom that (adj.)that (adj.) 2,292,29 13,313,3

55 ikkeikke notnot 2,192,19 15,515,5 åå to (inf.)to (inf.) 2,242,24 15,515,5

66 ii inin 1,911,91 17,417,4 påpå onon 1,891,89 17,417,4

77 påpå onon 1,841,84 19,219,2 atat that (subs)that (subs) 1,831,83 19,219,2

88 atat that (subs)that (subs) 1,711,71 21,021,0 ikkeikke notnot 1,761,76 21,021,0

99 åå to (inf.)to (inf.) 1,701,70 22,722,7 dede theythey 1,741,74 22,722,7

1010 dede theythey 1,651,65 24,324,3 forfor forfor 1,631,63 24,424,4

1111 jegjeg II 1,581,58 25,925,9 enen a/ana/an 1,481,48 25,825,8

1212 medmed withwith 1,411,41 27,327,3 jegjeg II 1,451,45 27,327,3

1313 enen a/ana/an 1,331,33 28,628,6 ii inin 1,421,42 28,728,7

Hand Hand PCPC11 detdet itit 4,004,00 4,04,0 detdet itit 4,014,01 4,04,0

22 erer isis 3,813,81 7,87,8 erer isis 3,623,62 7,67,6

33 ogog andand 3,173,17 11,011,0 ogog andand 3,363,36 11,011,0

44 somsom that (adj.)that (adj.) 2,302,30 13,313,3 somsom that (adj.)that (adj.) 2,292,29 13,313,3

55 ikkeikke notnot 2,192,19 15,515,5 åå to (inf.)to (inf.) 2,242,24 15,515,5

66 ii inin 1,911,91 17,417,4 påpå onon 1,891,89 17,417,4

77 påpå onon 1,841,84 19,219,2 atat that (subs)that (subs) 1,831,83 19,219,2

88 atat that (subs)that (subs) 1,711,71 21,021,0 ikkeikke notnot 1,761,76 21,021,0

99 åå to (inf.)to (inf.) 1,701,70 22,722,7 dede theythey 1,741,74 22,722,7

1010 dede theythey 1,651,65 24,324,3 forfor forfor 1,631,63 24,424,4

1111 jegjeg II 1,581,58 25,925,9 enen a/ana/an 1,481,48 25,825,8

1212 medmed withwith 1,411,41 27,327,3 jegjeg II 1,451,45 27,327,3

1313 enen a/ana/an 1,331,33 28,628,6 ii inin 1,421,42 28,728,7