Challenges Presented by Diversity

1. Challenges Presented by Diversity --Topics in Technology Integration into the Second Language Classroom

2. Computer Mediated Communication • Corpus Analysis and Foreign Language Teaching • Machine Translation Tools

3. Computer Mediated Communication • Asynchronous CMC: Emails; discussion board. • Synchronous CMC: Chatrooms; Internet Relay Chat such as MSN or ICQ

4. Compared to f-2-f Interaction • CMC enhances students’ motivation. (Kern, 1995). • CMC reduces anxiety and produces more talk. • CMC improves linguistics proficiency and increases self-confidence (Beauvois & Eledge, 1996). • Less vocal students participate more. (Warschauer, 1996; Sullivan & Pratt, 1996).

5. Recent Studies in Internet Relay Chat • Coniam, D. & Wong, R. (2004). 26 EFL students used ICQ to chat at least 5 hours a week for a month long period. (Chat partners and topic were not controlled.) –Lower the “affective filter”. • Results: Those students made as many errors as they did in pre-test. But they tended to use far more auxiliaries and more complex sentences. • Students found the activity interesting and motivating.

6. Recent Studies in Internet Relay Chat • Sotillo (2005) : Analyzing Learner Errors in Communicative Activities via Yahoo! Instant Messenger. • The ten students, including NS and NNS, were asked to “help each other”. • D: Aren’t you from Guadalajara? • T: Yes, we’re all from Guadalajara, but my father got a good job opportunity in Sacatecas which is four hours far away. • D: Four hours away.<recast> • T: Four hours away.<noticing and uptake> You see, those are my problems. Four hours away • D: Just repeat and you’ll remember.

7. Conclusions (Sotillo, 2005) • Instant messaging is an attractive option for young adults. • IM offers L2 learners opportunities to acquire sociolinguistic competence as they take risks requesting favors/information, complimenting each other, apologizing, or negotiating misunderstandings.

8. Problems of Using Synchronous CMC in Foreign Language Teaching • The following is part of the chat logs for a electronic peer review activity (Liu & Sadler, 2003). • Christian says, “oh oh” • Michael arrives. • Vayomi says, “What paragraphs” • Christian says, “hi michael” • Michael says, “HEY” • Christian says, ‘u wrote about Jack”. • Michael says, “hey christine” • Michael says, “err your paper sucked” • Vayomi says, “Hi Michael” • Michael says, “hehehe”

9. Problems of Synchronous CMC • The following is part of the chat logs from Sotillo (2005). • 70R<NNS>: sure I’m realy <spelling> sorry • 71K<ANNS>: stop saying sorry… • 74K<ANNS>: In unite state people don’t say sorry all the time like in Brazil. • Later on… • 129K<ANNS>: Yes, I know. But here in US I have never heard about it. […] • 130K<ANNS>: I ‘m going to type some sentences and we can go over them. • 131R<NNS>: ok • 132R<NNS>: I have never been in <syntax-missing article ‘the’> united states. • --R. mimics her structure immediately following the second instance.

10. Problems of Synchronous CMC • Instead of focusing on the tasks for language learning, students chat for “fun”. Liu & Sadler (2003): Students liked using the chatroom, but the student’s conversation in chatroom proved ineffective for the peer review purposes. • Chat partners whose knowledge of the TL is incomplete may not detect learner errors; they may even introduce additional errors. • The very nature of “chatting” precludes thoughtful writing in the target language. • Teachers’ responses towards chatroom activities are somewhat controversial. (Kern, 1995). • Teacher would want to have control over the students’ chatting activity; they also want to lower the students’ “affective filter”. It is difficult to achieve both. • Synchronous CMC should complement more structured and formal methods of foreign language teaching. (Sotillo, 2005).

11. Corpora; Corpus • Loose Definition: A large database with written and/or oral texts (i.e. “authentic” languages). • Leech and Fligelstone (1992) : "bodies of natural language material (whole texts, samples from texts, or sometimes just unconnected sentences), which are stored in machine-readable form". • Teaching and Language Corpora (1996): “……they are now being used increasingly for teaching purposes. This includes the use of corpus data to inform and create teaching materials; it also includes the direct exploration of corpora by students, both in the study of linguistics and of foreign languages”

12. The Use of Corpora in Foreign Language Teaching • Because materials in corpus is “authentic” , teachers and materials designers can better describe the language to be acquired, and decide what learners should learn. • Corpora can consist of materials produced by learners, so that teachers can know the students’ weaknesses. • Students can use the corpora to learn themselves.

13. An EFL textbook example: MR SNOW: Hello, Wendy. MRS SNOW: Hello, Ron. MRS SNOW: Where are the girls?Are they packing? MRS SNOW: Yes, they are. MR SNOW: Or are they playing? MRS SNOW: No, they aren’t, Ron. They are packing. Corpus analysis: “Packing” and “playing” are not at all frequent in the pattern “are they VERB-ing”. Sinclair (2002): “We cannot trust our ability to make up examples”. Corpus Example 1 (BNC): What’s happening now, does anybody know? What are we talking about, what’s the subject? Are you listening to me? Are you staying at your mum’s tonight? No. I’m staying at Christopher’s. Corpus Example 2 PSOM4> Alia and Aden are coming around to play with you this afternoon. PSOM5> Are they coming now? PSOM4> In a minute. Corpus Example 3 PSOM5>: Who who bought this? PSOM4>: Mummy and daddy bought it. PSOM5>: Where did it came from? PSOM4>: It comes from the Gap. “Authenticity”( Römer, 2004)

14. A Combination of Computer Learner Corpus based error analysis and CALL (Lee, Choo, Kim, 2005) • Firstly, they used the students’ writing to create a 260,000-word corpus; they used a concordance program to identify four highly persistent grammatical errors. • Errors were incorporated in a CALL program: ESL Tutor • 22 ESL students received CALL instruction for one hour a week over four weeks. • The students were asked to use ESL Tutor to detect and correct ungrammatical examples of the four targeted categories embedded in their own writings. • Students’ performance in post-test showed significant improvement.

15. Machine Translation Tools • Machine translation tools, when used appropriately, can be a valuable learning and productivity aid. • Students can explore new words and phrases. • The translation tools help ESL/EFL students make sense of the topic. • Website: • http://world.altavista.com • http://www.free-translator.com • http://www.freetranslation.com • http://www.worldlingo.com

16. Machine translation tools, when used appropriately, can be a valuable learning and productivity aid. Students can explore new words and phrases. The translation tools help ESL/EFL students make sense of the topic. The tools of the automatic translation, when they are used appropriately, can be to learn and an aid valuable of the productivity. The students can explore new words and phrases. The students of aid ESL/EFL of the translation tools have sense of the subject. How effective are machine translation tools? ---http://world.altavista.comEnglish  Spanish; Spanish  English

17. Machine translation tools, when used appropriately, can be a valuable learning and productivity aid. Students can explore new words and phrases. The translation tools help ESL/EFL students make sense of the topic. When being used appropriately, when valuable study and it is which of help of productivity, there is machine translation equipment. The student can explore new word and phrase. The help ESL/EFL student of the translation equipment has formed the meaning of the topic. How effective are machine translation tools?--English  Japanese; Japanese English

18. How effective are machine translation tools? • They might work better for simple sentences than for complex/compound sentences. • They might work better for languages which are “closer” to each other (i.e. English and Spanish) than for “distant” languages (i.e. English and Japanese). • They probably work well for specific words, but they are less efficient in dealing with contexts.

19. Google Language Tools--Try translating your website ……

20. Technology can be used for speech recognition, translation, and synthesis. Students can use this technology to practice their foreign language skills. Problems: Students might take advantage of such technologies to complete their L2 class assignment. Do we need to learn foreign languages if machine can translate effectively for us? Dr. Patrick Dixon: http://streams.netscalibur.co.uk:8080/ramgen/~dhs-0022/language.rm Implications