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Nik Aloesnita Nik Mohd Alwi aloesnita@ump.my Universiti Malaysia Pahang, Malaysia

Task implementation features and language production in synchronous computer-mediated communication. Nik Aloesnita Nik Mohd Alwi aloesnita@ump.edu.my Universiti Malaysia Pahang, Malaysia Rebecca Adams r.adams@auckland.ac.nz Auckland University, New Zealand. E-communication and SLA.

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Nik Aloesnita Nik Mohd Alwi aloesnita@ump.my Universiti Malaysia Pahang, Malaysia

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  1. Task implementation features and language production in synchronous computer-mediated communication Nik Aloesnita Nik Mohd Alwi aloesnita@ump.edu.my Universiti Malaysia Pahang, Malaysia Rebecca Adams r.adams@auckland.ac.nz Auckland University, New Zealand

  2. E-communication and SLA Warchauer (1998) : A second language learner must have the ability “to read, write and communicate in an electronic environment”. Scopes of this presentation: - Computer-mediated communication (CMC) - Task complexity - Current study

  3. Computer-mediated communication Synchronous (SCMC) - Real-time communication e.g. internet-relay chat - Can be either written (text) or spoken (audio) language or visual (image) or any two (audio and image) or all three (text, audio and image)

  4. Text-SCMC • Previous studies on text-SCMC and TBLT • encourages meaning negotiation and interactional modifications (Kung, 2004; Lai & Zhao, 2004) • promotes noticing and focus on form (Fiori, 2005) • enhances accuracy (Blake & Zyzik, 2003) and complexity (Cheon, 2003) • fosters active learning and equal participation (Freiermuth & Jarell, 2006) • develops oral, interactive competence (Payne & Ross, 2005)

  5. Cognition Hypothesis • Increasing cognitive complexity of interactive tasks along: • 1) Resource-directing variables → • Accuracy ↑ Complexity ↑ • 2) Resource-dispersing variables → • Accuracy ↑ Complexity ↓

  6. Task implementation features in the current study Resource-dispersing variables Task structure: Low task structure (–TS) and high task structure (+TS) Language support: No language support (–LS) and with language support (+LS)

  7. Research hypotheses Hypothesis 1a: –TS → more accuracy than +TS Hypothesis 1b: –LS → more accuracy than +LS Hypothesis 2a: –TS → less complexity than+TS Hypothesis 2b: –LS → less complexity than +LS

  8. Research methodology • Subjects: • n = 96; 4 groups of Engineering learners • doing English for Professional Communication • Text-SCMC tool: • Microsoft internet relay chat (mIRC) • Procedures: • Learners- Engaged in 45 minutes chat session performing • a problem solving, authentic engineering task • 2) Researcher- Monitored and captured each learner’s screen • using the classroom management systems

  9. Research task Role-play engineers at a multinational company Technical description of the software to propose Tasks: Listen to each other’s proposals Compare and contrast Discuss until consensus based on: 1. practicality 2. utilization 3. cost Complete recommendation worksheet

  10. … continued High Task Structure (+TS) condition Instruction: Each of you has information on the software. As you discuss the software, fill in this table. This will help you compare and contrast the software to decide what is best for your company.

  11. Screenshot of language support

  12. Summary of research design

  13. Measures of language production • Accuracy • Error/AS-unit • TLU auxiliary verbs • TLU modal verbs • Complexity • Clause/AS-unit • Words beyond the first 1000 words • Guiraud Index

  14. Results: Accuracy Errors/As-unit 0.45 0.4 0.4 0.35 0.31 0.3 0.25 0.2 0.15 0.11 0.1 0.05 0.04 0 -LS +LS 1) Errors/AS-unit -TS +TS -LS +LS Task Structure (p ≤ 0.05) Language Support (p ≤ 0.05) Interaction effect (p ≥ 0.05)

  15. Results: Accuracy % of targetlike use of auxiliary verbs 100 92.83 90 80 73.94 70 60 52.34 50 52.83 40 30 20 10 0 -LS +LS 2) TLU auxiliary verbs +TS -TS -LS +LS Task Structure (p ≤ 0.05) Language Support (p ≤ 0.05) Interaction effect (p ≤ 0.05)

  16. Results: Accuracy 3) TLU modal verbs +TS -TS -LS +LS Task Structure (p ≤ 0.05) Language Support (p ≤ 0.05) Interaction effect (p ≥ 0.05)

  17. Summary: Accuracy Hypotheses: Hypothesis 1a: –TS → more accuracy than +TS Hypothesis 1b: –LS → more accuracy than +LS Results: +TS → more accuracy than –TS +LS → more accuracy than –LS

  18. Task structure: Discussion … continued “This means we did not have much trouble understanding the gist of the message, and I think that made us more attentive to the language our teammates used. I mean it allowed us to be more conscious of others’ language expressions” (Student A)

  19. Results: Complexity Clause/AS-unit 0.8 0.73 0.7 0.63 0.59 0.6 0.57 0.5 0.4 0.3 0.2 0.1 0 -LS +LS 1) Clause/AS-unit -TS +TS -LS +LS Task Structure (p ≥ 0.05) Language Support (p ≤ 0.05) Interaction effect (p ≤ 0.05)

  20. Results: Complexity % of words beyond the first 1,000 words 25 22.14 20.68 20 18.09 17.64 15 10 5 0 -LS +LS 2) Words beyond the first 1000 words +TS -TS -LS +LS Task Structure (p ≥ 0.05) Language Support (p ≤ 0.05) Interaction effect (p ≥ 0.05)

  21. Results: Complexity +TS -TS -LS +LS Task Structure (p ≥ 0.05) Language Support (p ≥ 0.05) Interaction effect (p ≤ 0.05)

  22. Summary: Complexity Hypotheses: Hypothesis 2a: –TS → less complexity than +TS Hypothesis 2b: –LS → less complexity than +LS Results: No significant effects of task structure on complexity +LS → less complexity than -LS

  23. Discussion +TS or +LS → accuracy ↑ -LS → complexity ↑

  24. Discussion “The language exercises and notes were very helpful when we had to do activities without the teacher’s help. Whenever I was uncertain of my grammar, I could refer to the notes. I could also compare what I have typed with the notes before I posted my message. It was convenient and I feel more confident to talk” (Student B)

  25. Discussion “We should be given more chance to practice English language using text chat. It encourages me to participate more because I can see what I want to say on the screen before posting my message. It reduces the probability of making errors. When we discuss language problems for example in a group of four or five, we can compare all opinions at the same time on one screen. It is very motivating” (Student C)

  26. Implications for Teaching • Increasing support (structure/language) to • promote attention to accuracy • -Avoid pre-task focus on specific forms to promote • complexity • -Task complexity: SCMC ≠ f2f

  27. References Blake, R. & Zyzik, E. (2003). Who’s helping whom?: Learner/Heritage-speakers’ networked discussions in Spanish. Applied Linguistics, 24(4), 519-544. Cheon, H. (2003). The viability of computer mediated communication in the Korean secondary EFL classroom. Asian EFL Journal, 5(1). Retrieved April 16, 2005, from www.asian-efl-journal.com/march03.sub2hc.pdf Fiori, M. L. (2005). The development of grammatical competence through synchronous computer-mediated communication. CALICO, 22(3), 567-602. Freiermuth, M. & Jarrell, D. (2006). Willingness to communicate: Can online chat help? International Journal of Applied Linguistics, 16(2), 189-212. Kung, S-C., (2004). Synchronous electronic discussions in an EFL reading class. ELT Journal, 58(2), 164-173. Lai, C. & Zhao, Y. (2006). Noticing and text-based chat. Language Learning & Technology, 10(3), 102-120. Retrieved January 9, 2007, from http://llt.msu.edu/vol10num3/laizhao/default.html Payne, J. S. & Ross, B. (2005). Synchronous CMC, working memory, and L2 oral proficiency development. Language Learning & Technology, 9(3), 35-54. Retrieved April 18, 2006, from http://llt.msu.edu/vol9num3/payne/default.html Warschauer, M. (1998). Researching technology in TESOL: Determinist, instrumental, and critical approaches. TESOL Quarterly, 32(4), 757-761.

  28. THANK YOU

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