Analyzing language complexity

of Chinese and African LearnersPresenters:

Agung Diah Wulandari // Ardiansyah // Eka Uliyanti // Paula Kristanti

• Most communicative tasks generally refer to what Cummins has called social language and academic language, the first referring to basic interpersonal communication. This kind of language generally typifies a relatively concrete and, observable utterance, e.g. the speech about things, people, and actions, and is generally supported by a considerable amount of contextual information (e.g., visual information about people and places). In this language, a lot of information can also be conveyed nonverbally to support and clarify our verbal communication (as cited in CARLA, 2015, para. 1).

• The latter, is typically a more complex called as Academic language, due to its differences and the possibility to develop its meaning independently (without being contextualized). Academic language proficiency is the ability to use cognitively demanding language (e.g. abstract nouns and complex syntax) as a tool for critical thinking, and it typically is used in situations where there may be comparatively little contextual support to aid in the sending and receiving of information (CARLA, 2015, para. 1)

Introduction

• Language complexity refers to how the students organizes and elaborates their speech. Language complexity generally varies based on the topic of discussion (CAL, 2015, para. 1-2).

• For example: the use of one word or phrase in a certain situation (e.g., What languages do you speak?), or the use of strings of sentences which are typically complex in different situation (e.g., Do you think it’s important to keep up with the news? Why/Why not?). (CAL, 2015, para. 1-2)

What is language complexity?

• Language Complexity / Cognitive complexity is related to complexity in language, both sentence structure and lexicon (CARLA, 2015, para. 1-2 ).

• In functional linguistics perspective, Schleppegrell states that certain utterance can be identified in terms of language forms that function to express a wide range of logical relationships in academic discourse. One such logical relationship occurs when one states an inference and the facts that support that inference (as cited in CARLA, 2015, para. 1-2 ).

Lackstorm says that typically the inference is framed using an abstract noun, such as ‘wealth’, while the facts may be realized as concrete nouns, such as car, nice house, or satellite dish. Linguistic forms are also needed to link inferences to supporting facts  (as cited in CARLA, 2015, para. 3).  

• Tarone & Swierzbin (2009) propose that native speakers of English could possibly show the above concept by way of producing evidence in support of their inferences using phrases like ‘just based on’, ‘from looking at these’, ‘because’(p.87).

• In short, Biber states that academic language typically includes an increased variety in the lexicon, such as the use of rare and/or abstract nouns; very complex noun phrases with multiple levels of embedding; and an increased occurrence of relative, adverbial and complement clauses (as cited in CARLA, 2015, para. 4).

The syntactic and lexical variety that is characteristic of academic language is more cognitively demanding. In addition, the lack of contextual support puts pressure on the speaker to be more precise, to make sure the listener understands.  Only at higher levels of proficiency do language learners appear to master the more complex registers and uses of the language (CARLA, 2015, para. 1-2).

Level SentencesLevel I Simple sentences, including

questions

Sentences with auxiliaries and semi-auxiliaries

Simple elliptical (incomplete) sentences

The dog barked.Did the dog bark?Where are you going?

This may have solved it.He is going to take the bus. The dog over there.He did.

Level 2 Infinitive or -ing complement with same subject as main clause

Try to brush her hair.Try brushing her hair.I felt like turning it.

Level 3 Relative (or appositional) clause modifying object of main verb Nominalization in object position Finite clause as object of main verb Subject extraposition

The man scolded the boy who stole thebicycle. Why can’t you understand his rejection ofthe offer?John knew that Mary was angry.Remember where it is?was surprising for John to have left Mary 

D-Level Scale by Covington et al (2006)

Level SentencesLevel 4 Non-finite Complement with its

own understood subject    Comparative with object of comparison

I expect him to go.I want it done today.I saw him walking the dog.I consider John a friend.I want these animals out of my house.John is older than Mary

Level 5 Sentences joined by a subordinating conjunctionNonfinite clauses in adjunct (not complement) positions

They will play today if it does not rain. Cookie Monster touches Grover after jumping over the fence.Having tried both, I prefer the second one.

Level SentencesLevel 6 Relative (or appositional) clause

modifying subject of main verb Embedded clause serving as subject of main verb

Nominalization serving as subject of main verb

The man who cleans the rooms left early.  For John to have left Mary was surprising. John’s refusal of the drink angered Mary.

Level 7 More than one level of embedding in a single sentence

John decided to leave Mary when heheard that she was seeing Mark

One way to measure lexical complexity is to count the number of different words that occur in a segment of written or spoken text: a type-token ratio (TTR).

•Exploring the working definitions of language complexity. •Exploring the impact of language complexity to second language learners’ communication.•Analyzing learners’ language complexity, in terms of abstract and concrete words.

Objective of Analysis

Library researchSource of Data The data will be taken from transcript

of the interview from two learners (Retell and Narrative task).

Method of Analysis

Highlighting the data &

Listing them Into a table

Analyzing the data using

Simple Concordance

Program

Identifying the data

Reading the transcript

Watching the videos

Data collection technique will be conducted by way of:

Kormos & Trebits (2012)

Method: investigating the relationship between components of aptitude and the fluency, accuracy, syntactic complexity and lexical variety of performance in two types of written and spoken narrative tasks by administering oral and written narrative test to 44 students age 15-18 in Hungarian-English bilingual secondary schoolResults: participants used more varied vocabulary in writing than in speech, but their performance was similar in terms of syntactic complexity.

Sadeghi & Mosalli (2012)

Method: exploring the effect of task complexity on the fluency and lexical complexity of 60 university EFL students’ argumentative writing in IranResults: increasing task complexity (1) produced significantly less fluency, and (2) did not lead to differences in lexical complexity (measured by the ratio of lexical words to function words and lexical density), but it did lead to significant differences when mean segmental type-token ratio was used to measure lexical complexity.

Masrom, Alwi, & Daud (2015)

Method: Employing multivariate analysis of variance (MANOVA) toward 88 undergraduate ESL students in a public Malaysian university, to measure the effects of task complexity and the complexity of language productionResults: the manipulation of task complexity has a significant effect on certain measures of syntactic and lexical complexity of the language production

Summary of Previous Studies

Data Analysis

*fillers are NOT included

Retell Task

Chun

81 word vocabularies-5=76261 words-19=242Type Token Ratio= 76/242x100= 31% Line   Complexity 

5 ...he want to uh take a ride? 17 ..uh yeah take a ride but and he just do this.. 21 to 2 when he got up and he found he's [lake], uh, he's late... 29 ...the driver want to take him to school so he geti in the car. 112 he just want to clean the windshield uh and then but but he think... 116 he was surprise to find the boy in his car 1  TOTAL 8

Concrete Words Abstract WordsBus catchMoney WinterSchool AgreeWindshield CleanStudent MissedCar Gesture

Late

Data Analysis

*fillers are NOT included

Narrative Task

Jeanne

71 word vocabularies-9=62207 words-28=179Type Token Ratio= 62/179x100= 34% Line   Complexity 

2 to 3 um, something in her bag that she took from 310 to 11 I don't know who put it there 311 to 12 She's not going to know that it was the, baby who put it in her bag  614 to 15 She won't know who put it there.. 315 They're going to ask her to pay, for it. 1  TOTAL 16

Concrete Words Abstract WordsBag MetGrocery StoleStore Name

 KnowGoingSomethingCall

Findings and Discussion

Conclusion

•Chun has 31% of Type Token Ratio in Retell Task•Chun gets 8 points of lexical complexity•Chun uses more concrete words than Jeanne

•Jeanne has 34% of Type Token Ratio in Narrative Task•Jeanne gets 16 points of lexical complexity•Jeanne uses less concrete words than Chun

Jeanne has more lexical complexity than Chun based on the Type Token Ratio and Lexical Complexity. Furthermore, Jeanne uses less concrete words than Chun.

Although the use of abstract words between Chun & Jeanne are equal, Jeanne uses less concrete words than Chun

CAL (2015). Components of language complexity. Retrieved from: http://www.cal.org/adultspeak/assessment/complexity.html CARLA (2015). Overview of complexity of learner language. University of Minnesota.

Retrieved from: http://www.carla.umn.edu/learnerlanguage/complexity.html Covington, M. A., He, C., Brown, C., Naci, L., & Brown, J. (2006). How complex is that sentence? A proposed revision of the

Rosenberg and Abbeduto D-Level Scale.Kormos, J. & Trebits, A. (2012). The role of task complexity, modality and aptitude in narrative task performance. A journal of

research in language studies 62(2), 1-34.Masrom, U. K., Alwi, N. A. N. M., & Daud, N. S. M. (2015). The effects of task complexity on the complexity of the second language

written production. Journal of second language teaching and research 4(1), 38-66.Sadeghi, K. & Mosalli, Z. (2012). The effect of task complexity on fluency and lexical complexity of EFL Learners’ argumentative

writing. International journal of applied linguistics & English literature 1(4), 53-65.Tarone, E. & Swierzbin, B. (2009). Exploring learner language. Oxford: Oxford University Press.www.sltinfo.com/type-token-ratio/

References