Manipulating Task Complexity: its impact on L2 production across task types and modes Roger Gilabert Mayya Levkina Universitat de Barcelona TBLT Conference Lancaster September 2009 Thanks to GRAL at the University of Barcelona, Ministerio de Ciencia e Innovación – HUM ) and Generalitat de Catalunya – 2009SGR137).

L2 Task –based research into performance and acquisition PLANNING TIME TASK COMPLEXITY TASK FAMILIARITY Intro: context INTERACTION Other Brennan, forthcoming

L2 Task –based research into performance and acquisition PLANNING TIME TASK COMPLEXITY TASK FAMILIARITY Intro: context INTERACTION Other

task complexity is the result of the attentional, memory, reasoning, and other information processing demands imposed by the structure of the task on the language learner. (Robinson, 2001:28 ) TASK COMPLEXITY

Pedagogic task 1 REAL- WORLD TASK Pedagogic task 2 Pedagogic task 3 Pedagogic task n What may be the role of task complexity in a task-based syllabus? Long, 2005 Balanced development of L2 production and acquisition GOAL SimpleComplex

The predictions of the Cognition Hypothesis More complex along resource- directing variables More complex along resource- dispersing variables Less fluent More lexically and structurally complex More accurate Higher interaction Less fluent Less lexically and structurally complex Less accurate Higher interaction (e.g. amount of preparation time, familiarity, or multi-tasking) (e.g. the number of elements or the amount of reasoning)

+/- here-and-now+/- elements +/- reasoning demands Fluency Lexical complexity Structural complexity Accuracy Findings of the impact of task complexity on production along resource directing dimensions Fluency decreases (Robinson, 1995; Rahimpour, 1997: Gilabert, 2005) Increased lexical complexity (Robinson, 1995; Rahimpour, 1997; Gilabert, 2005) No differences in structural complexity (Robinson, 1995; Rahimpour, 1997; Gilabert, 2005) Higher accuracy (Robinson, 1995; Rahimpour, 1997; Ishikawa, 2001; Iwashita et al.; Gilabert, 2005) +/- here-and-now+/- elements +/- reasoning demands Fluency decreases (Michel, Kuiken & Vedder, 2007; Robinson, 2001) Increased lexical complexity (Michel, Kuiken & Vedder, 2007; Révész, forthcoming) No differences in structural complexity (Michel, Kuiken & Vedder, 2007; Kuiken & Vedder, 2007; Kuiken, Vedder, & Mos, 2005) but Révész (forthcoming) Higher accuracy (Michel, Kuiken & Vedder, 2007; Kuiken & Vedder, 2007; Kuiken, Vedder, & Moss, 2005) but Révész (forthcoming) Fluency decreases (Niwa, 2001 ) Increased lexical complexity (Michel, Kuiken & Vedder, 2007; Révész, forthcoming) No differences in structural complexity (Robinson, 2007) but Révesz (forthcoming) Higher accuracy (Robinson, 2007; Gilabert, 2007) but Révész (forthcoming)

Goals and Questions Goal: to explore the impact of task cognitive complexity accross task types and modes. Questions: 1) Whats the relationship between general proficiency and performance? 2) Can differences in task cognitive complexity explain differences in performance in both monologic and dialogic tasks? 3) Are the effects of task cognitive complexity the same across task types?

DesignParticipantsStatistical analysis, transcription, coding 3 task types Repeated- measures design Latin square design 9-point Likert scale affective questionnaire 42 English-L2 volunteers in monologic study 50 in dialogic (25 dyads) 2 institutions (lower- /upper- intermediate) X-Lex / Y-Lex vocabulary size test Descriptive statistics Repeated-measures ANOVA Non-parametric tests CA mode of CHILDES for transcription of 252 tasks in study 1 + and 150 tasks in study 2 (302 tasks) Intrarater (97 %//97%) Interrater (91.5 %/90%) Experimental design

Advertising Journalism P.R. ( task-based program at Communication Studies Department at Ramon Llull University,Barcelona Spain) Typically they deal with storyboards for campaign presentations Task selection: Needs analysis Journaslists often have to find their ways in unknown cities In crisis management, scenario planning is an important aspect TV/Cinema

Task 1: narrative Monologic and dialogic Operationalization

Begin the story like this: TODAY Mr. and Mrs. Ropper are in bed. Theyre trying to get to sleep but they can hear music coming from the apartment above theirs. Begin the story like this: YESTERDAY Mr. Festenkroud was shopping at the supermarket. He was checking his shopping list and looking at prices. An employee was putting price tags on the products. SIMPLE here-and-now Visual presence (here) Present tense (now) COMPLEX there-and-then No visual presence (there) Past tense (then) Tasks and operationalization of variables

Interactive, two-way, closed, convergent, split information narrative task SIMPLE Here-and-now Visual presence (here) Present tense (now) COMPLEX There-and-then No visual presence (there) Past tense (then) Tasks and operationalization of variables

Results: Affective perception questionnaire I thought this task I thought this task was easy was difficult I felt frustrated I felt relaxed doing this task I did not do this I did this task well task well This task was This task was not interesting interesting I dont want to I want to do more do more tasks tasks like this like this (Based on Robinson, 2001) Dependent VariableNarrativeMapFire chief Difficulty,372,013*,006* Stress,765,513,079 Confidence,552,067,005** Interest,371,262,912 Motivation,775,842,530

Task 2: map task Monologic and dialogic Operationalization

Simple Few landmarks Clearly distinguishable landmarks One axis (lateral= right, left, straight)

Complex Many landmarks Similar landmarks More axes (lateral – right, left, straight– vertical – up, down – sagittal – front, back).

Simple Few landmarks Clearly distinguishable landmarks One axis (lateral= right, left, straight) Interactive, one-way, closed, convergent, split information map task Tasks and operationalization of variables Route marked Route unmarked

Complex Many landmarks Similar landmarks More axes (lateral – right, left, straight– vertical – up, down – sagittal – front, back). Interactive, one- way, closed, convergent, split information map task Route marked Route unmarked Tasks and operationalization of variables

Wayfinding is an important and complex task. Landmark identification Path selection Direction selection Abstract environmental overviews Chown, E., Kaplan, S., & Kortenkamp, D. (1995)

Task 3: firechief task Monologic and dialogic Operationalization

SIMPLE Many resources No particular roles Few unconnected factors COMPLEX Few resources Particular roles of characters Intricately connected factors

SIMPLE Many resources No particular roles Few unconnected factors Interactive, two-way, open, convergent, shared information decision-making task

COMPLEX Few resources Particular roles of characters Intricately connected factors Interactive, two-way, open, convergent, shared information decision-making task

Complex problem-solving tasks are situations that are: (1)dynamic, because early actions determine the environment in which subsequent decisions must be made (2)time-dependent, because decisions must be made at the correct moment in relation to environmental demands; and (3)complex, in the sense that most variables are not related to each other in a one-to-one manner. In these situations, the problem requires not one decision, but a long series, in which early decisions condition later ones. Quesada et al. (2005)

Experimental design: production measures Transcriptions were coded for: -Fluency: Unpruned speech rate A Pruned speech rate B Pauses x minute -Structural Complexity: Sentence Nodes x AS-Unit. -Lexical Complexity: Guiraud Index of Lexical Density -Accuracy: No. Of errors x 100 words Repaired to unrepaired errors

Results: Question 1 1)Whats the relationship between general proficiency and performance? Moderately strong correlation between PROFICIENCY and PERFORMANCE Proficiency x Performance in MONOLOGIC Simple Story Complex Story Simple Map Complex Map Simple Firechief Complex Firechief Rate A,792**,613**,590**,613**,557**,586** Rate B,839**,758**,643**,669**,667**,695** Pauses,271,085,336*,261,372*,197 S-Nodes x AS Unit,208,035,479*,336*,130,269 Guiraud Index,718**,650**,618**,562**,760**,716** Errors x 100 words -,725**-,680**-,816**-,768**-,719**-,738** Rep to unrep,216,158,031-,024-,104,119

Results: Question 1 1)Whats the relationship between general proficiency and performance? Moderately strong correlation between PROFICIENCY and PERFORMANCE Proficiency x Performance in DIALOGIC Simple Story Complex Story Simple Map Complex Map Simple Firechief Complex Firechief Rate A,417*,329*-,021,233,226,143 Rate B,391*,362*,375,335,334*,121 Pauses-,177-,143,084-,093-,007-,074 S-Nodes x AS Unit,216,179-,071,038,162,094 Guiraud Index,346*,478**,415*,404,269,356* Errors x 100 words -,099-,029,009-,231-,115-,086 Rep to unrep -,023,228-,035,140-,036,066

Results: Question 2 2) Is there an impact of Task Complexity on performance in both the monologic and dialogic tasks? Proficiency x Performance in MONOLOGIC Simple Story Complex Story Simple Map Complex Map Simple Firechief Complex Firechief Rate A,448,072,196 Rate B,069,227,404 Pauses,308,827,460 S-Nodes x AS Unit,261,095,638 Guiraud Index,286,002,087 Errors x 100 words,001,000,777 Rep to unrep,009,000,149

Results: Question 2 2) Is there an impact of Task Complexity on performance in both the monologic and dialogic tasks? Proficiency x Performance in DIALOGIC Simple Story Complex Story Simple Map Complex Map Simple Firechief Complex Firechief Rate A,167,372,164 Rate B,256,309,229 Pauses,336,972,177 S-Nodes x AS Unit,830,277,116 Guiraud Index,025,287,008 Errors x 100 words,707,231,325 Rep to unrep,162,353,468

Results: tasks compared by dimension Sig. difference

Results: tasks compared by dimension Sig. difference

As expected, in the MONOLOGIC task, general proficiency correlated strongly with performance, and particularly with lexical complexity and accuracy. The picture is not so clear for the DIALOGIC task, where interaction seems to mitigate the effects of proficiency on performance, especially with regard to accuracy Discussion: Question 1

In the MONOLOGIC tasks, task complexity shows an impact on accuracy in the narrative task, while it has an impact on both lexical complexity and accuracy in the case of the map task. Higher tasks demands seem to draw attention to form. Task complexity has no impact on the decision-making task. General measures may not be able to capture such impact. In the DIALOGIC tasks, task complexity seems to only affect lexical complexity, and just for the narrative and the decision-making task. Discussion: Question 2

In the MONOLOGIC tasks: the map task generated less structurally and lexically complex speech. In the DIALOGIC tasks, task complexity seems to only affect lexical complexity, and just for the narrative and the decision-making task. Discussion: Question 3

1)As in other task-based research areas (e.g. planning time studies, task repetition, or interaction), SPECIFIC PREDICTIONS need to be made for each TASK TYPE. 2)In the same way, predictions need to be adjusted to EACH MODE, since behavior on monologic and dialogic tasks differs considerably. Conclusions

1)Small sample sizes 2)Use of general measures only 3)Binary operationalizations of complexity (simple/complex, not a continuum) 4)Not factoring in individual differences (e.g. differences in WM capacity) 5)Not using complementary information from native speaker performance Limitations

1)Use of more specific measures (task-related, developmentally sound) (Pownall, forthcoming) use of conjoined clauses as in Révész (forthcoming) and NPs has found that specific, task-related measures capture the impact of task complexity Ways to go from here and, because, so The car The little boy The funny little boy If, before, after The girl that was reading little boy

1)Use of more specific measures (Pownall, forthcoming) use of conjoined clauses as in Révész (forthcoming) and NPs has found that specific, task-related measures capture the impact of task complexity 2) Integration of Task Complexity into SEQUENCING studies. Ways to go from here

Thank you Gràcies Gracias Members of the GRAL group: Carme.Muñoz, M. Luz Celaya, Elsa Tragant, Teresa Navés, Joan Carles Mora, Imma Miralpeix, Raquel Serrano, Júlia Barón, Natalia Fullana, Laura Sánchez Interns: Mayya Levkina, Mireia, Anna Marsol Catherine Daughty Our students Roger Gilabert Universitat de Barcelona