E-text in EFL - Four flavours


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Dr. Przemysław Kaszubski : IFAConc - web-concordancing with EAP writing students
Mgr Joanna Jendryczka-Wierszycka : E-text annotation - why bother?
Dr. Michał Remiszewski : Towards competence mapping in language teaching/learning
Prof. Włodzimierz Sobkowiak : E-text in Second Life: reification of text?
[ http://ifa.amu.edu.pl/fa/node/1144 ]
[ http://ifa.amu.edu.pl/fa/node/1123 ]

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  • E-text in EFL - Four flavours

    1. 1. E-TEXT in E-FL: Four flavours <ul><li>Przemek Kaszubski </li></ul><ul><li>Joanna Jendryczka-Wierszycka </li></ul><ul><li>Michał Remiszewski </li></ul><ul><li>Włodzimierz Sobkowiak </li></ul>
    2. 2. <ul><li>flexibility: fonts, formats, attributes </li></ul><ul><li>correctibility, accuracy, up-to-dateness </li></ul><ul><li>searchability: local and global </li></ul><ul><li>portability: PDA, Kindle, smartphone, etc. </li></ul><ul><li>manipulability: types, media, channels </li></ul><ul><li>annotability: tagging, parsing, semantic web </li></ul><ul><li>immediacy: speed of transmission and processing </li></ul><ul><li>(hyper-)linkability, nonlinearity </li></ul><ul><li>sharability, openness, low cost </li></ul><ul><li>popularity among 'digital natives' </li></ul><ul><li>(See The Machine is Using Us by Michael Wesch for a good video treatment of these issues) </li></ul>The advantages of e-text:
    3. 3. <ul><li>PK : IFAConc - web-concordancing with EAP writing students </li></ul><ul><li>JJW : e-text annotation - why bother? </li></ul><ul><li>MR : Towards competence mapping in language teaching / learning </li></ul><ul><li>WS : e-text in Second Life: reification of text? </li></ul>Presentation plan:
    4. 4. Przemysław Kaszubski IFAConc – web-concordancing with EAP writing students
    5. 5. <ul><li>Developers: </li></ul><ul><ul><li>Paweł Nowak </li></ul></ul><ul><ul><li>Dominique Stranz </li></ul></ul><ul><li>Over 200 Student Participants : </li></ul><ul><ul><li>12 : MA and BA seminars 2005-6 </li></ul></ul><ul><ul><li>16 : 1MA and 2MA seminars 2007-8 </li></ul></ul><ul><ul><li>18 : 1BA Writing 2007-8 </li></ul></ul><ul><ul><li>32 : 1MA Academic Writing 2008-9 </li></ul></ul><ul><ul><li>140 : 3MA Acad. Discourse Part-Time Lecture 2008-9 </li></ul></ul>Acknowledgements
    6. 6. <ul><li>a form of e-text processing for a linguistic purpose: descriptive or pedagogical </li></ul><ul><ul><li>paper concordance < computer ised concordanc ing </li></ul></ul><ul><ul><li>data-driven learning (DDL): operationalisation of gap-noticing (also: form-focused instruction ; awareness-raising) </li></ul></ul><ul><li>‘ shunting’ (Halliday): </li></ul><ul><ul><li>vertical / paradigmatic reading – KWiC </li></ul></ul><ul><ul><li>horizontal / syntagmatic reading – KWiC + context </li></ul></ul><ul><li>pedagogic concordancing for EAP/ESP learning: </li></ul><ul><ul><li>repetitions / patterns (light theory: ‘extended units of meaning’ – Sinclair; ‘lexical primings’ – Hoey) </li></ul></ul><ul><ul><li>dispersion within corpus </li></ul></ul><ul><ul><li>variation across corpora </li></ul></ul>Concordancing
    7. 7. Corpora Search (click on picture to go to IFAConc; log in for best effect)
    8. 8. <ul><li>DDL under-practised and under-researched – few dedicated, student-friendly tools. Some needs: </li></ul><ul><ul><li>facilitate training and current practice (time factors: what to search for and how ; inductive analysis) </li></ul></ul><ul><ul><li>facilitate (but not replace) noticing and deeper-processing </li></ul></ul><ul><ul><li>manage results </li></ul></ul><ul><ul><li>facilitate teacher control and teacher-student interaction </li></ul></ul><ul><ul><li>integrate with syllabus etc. (also ‘non-e-text’) </li></ul></ul><ul><li>IFAConc and EAP writing – some assumptions: </li></ul><ul><ul><li>trace relevant academic primings (interesting patterns are many) </li></ul></ul><ul><ul><li>students (meta)linguistically conscious = co-research possible </li></ul></ul><ul><ul><li>enable more complex search patterns and subtle observations </li></ul></ul><ul><ul><li>encourage autonomy and individualisation (personal ‘primings’) </li></ul></ul>DDL issues and IFAConc
    9. 9. <ul><li>e-text sample </li></ul><ul><li>collection of e-text samples (= corpus; cline of spec. corpora) </li></ul><ul><li>selective structural markup (XML) </li></ul><ul><li>linguistic annotation (POS tagging) </li></ul><ul><li>conc. searchability (syntax language + options) </li></ul><ul><li>conc. manipulability: sampling, re-sorting, corpus switching </li></ul><ul><li>automatic conc. summary: stats table, collocate counting </li></ul><ul><li>unique URL search address – hyperlinking </li></ul><ul><li>note-taking ( annotation ) – personal and/or T-S collaborative </li></ul><ul><li>search logging (personal and global History database – browsable / searchable / hyper-linkable </li></ul><ul><li>towards dynamic conc-illustrated EAP textbook ( Resources ) </li></ul>E-text integration in IFAConc
    10. 10. History (click on picture to go to IFAConc History , log in when prompted)
    11. 11. Resources (click on picture to go to IFAConc Resources – reg’d IFA users only)
    12. 12. <ul><li>hyperlink-assisted concordancing </li></ul><ul><ul><li>Corpora Search hyperlinks </li></ul></ul><ul><ul><li>History search hyperlinks </li></ul></ul><ul><ul><ul><li>also Corpora Search ID and History Search ID options </li></ul></ul></ul><ul><ul><li>integrated with other materials </li></ul></ul><ul><ul><ul><li>e.g. feedback links; resources for self-exploration </li></ul></ul></ul><ul><li>T-S interactive annotation </li></ul><ul><li>= less time-costly, more meaningful concordancing: </li></ul><ul><ul><li>more students conduct more searches that are more in-depth ... </li></ul></ul><ul><ul><li>teacher learns about students ’ linguistic and cognitive abilities ... </li></ul></ul><ul><ul><li>... while the database of relevant lg observations continues to grow (and to gradually feed ‘Shared’ History and Resources) </li></ul></ul>Beyond bottom-up concordancing
    13. 13. <ul><li>IFAConc (09.2006 – 02.2009 ) : </li></ul><ul><ul><li>206 participants </li></ul></ul><ul><ul><li>All searches > 37,000 </li></ul></ul><ul><ul><li>Students' A ll searches: > 17,000 </li></ul></ul><ul><ul><li>All a nnotated: > 2 ,200 </li></ul></ul><ul><ul><li>Students’ a nnotated – c. 1,000 </li></ul></ul><ul><li>PICLE Conc (04.2004 – 08.2005) </li></ul><ul><ul><li>125 ... IP numbers (15-20 active users...) </li></ul></ul><ul><ul><li>All (?)students’ searches < 3,700 </li></ul></ul><ul><ul><li>Students’ annotated (non-interactive) – about 40 </li></ul></ul>Concordancing with EAP students – basic stats
    14. 14. <ul><ul><li>“ I found this research valuable as I used a few examples from Concordance database in my MA dissertation. I value the research as it provides me with proper examples of native uses. Whenever I look for a word usage I Google it, yet it never gives me 100% certainty that the internet source is a reliable one. Conc on the other hand is a reliable tool which a student can trust. ” ( agooska , H - 37145) </li></ul></ul><ul><ul><li>“ I regret I didn’t search these Conc pages before I wrote the majority of my dissertation…It is really a vital source - very helpful!” ( Aleksandra, Resources Textbook comment ) </li></ul></ul><ul><li>Some more practical applications will be shown at ELT training on 27th March </li></ul>Testimonials
    15. 15. Joanna Jendryczka-Wierszycka e-text annotation - why bother?
    16. 16. annotation (tagging)
    17. 17. <ul><li>Facebook, Picasa, Gmail, Etc. </li></ul><ul><li>Linguistic (e-text) annotation </li></ul>annotation (tagging)
    18. 18. <ul><li>definition </li></ul><ul><li>different levels of annotation: explanations, examples and utility </li></ul><ul><li>limitations of annotation </li></ul><ul><li>answer to “Why bother?” </li></ul>e-Text annotation - contents
    19. 19. <ul><li>corpus annotation is „the practice of adding interpretative, linguistic information to an electronic corpus of spoken and/or written language data” (Leech, 1997: 2) </li></ul><ul><li>It „is widely accepted as a crucial contribution to the benefit a corpus brings, since it enriches the corpus as a source of linguistic information for future research and development” (ibid.) </li></ul>e-Text annotation defined
    20. 20. <ul><li>Part-of-Speech </li></ul><ul><li>Parsing </li></ul><ul><li>S emantic </li></ul><ul><li>Discourse/ pragmatic </li></ul><ul><li>Stylistic </li></ul><ul><li>Prosodic </li></ul><ul><li>Lemmatization </li></ul><ul><li>M arkup </li></ul>e-Text annotation exemplified
    21. 21. <ul><li>adding information about word classes </li></ul><ul><li>er 93 FU she 93 PPHS1 was 93 VBDZ terrific 93 JJ in 97 [II/1] CS21%/ that 97 [DD1/1] CS22@/ film 93 [NN1/1] VV%/ </li></ul><ul><li>er_FU she_PPHS1 was_VBDZ terrific_JJ in_II that_DD1 film_NN1 </li></ul>e-Text annotation - POS
    22. 22. <ul><li>by far most frequent annotation </li></ul><ul><li>useful in: frequency lists or frequency dictionaries with grammatical classification, MT, Translation studies, contrastive linguistics, lg teaching, TTS synthesis </li></ul>POS-tagging ctd
    23. 23. <ul><li>syntactic analysis into such units as phrases and clauses (sentence structure) </li></ul><ul><li>[S[N Nemo_NP1 ,_, [N the_AT killer_NN1 whale_NN1 N] ,_, [Fr[N who_PNQS N][V 'd_VHD grown_VVN [J too_RG big_JJ [P for_IF [N his_APP$ pool_NN1 [P on_II [N Clacton_NP1 Pier_NNL1 N]P]N]P]J]V]Fr]N] ,_, [V has_VHZ arrived_VVN safely_RR [P at_II [N his_APP$ new_JJ home_NN1 [P in_II [N Windsor_NP1 [ safari_NN1 park_NNL1 ]N]P]N]P]V] ._. S] </li></ul>e-Text annotation - parsing
    24. 24. <ul><li>adding information about the semantic category of words, e.g. “bark” </li></ul><ul><li>for translation and lexicography </li></ul><ul><li>PPIS1 I Z8 VV0 like E2+ AT1 a Z5 JJ particular A4.2+ NN1 shade O4.3 IO of Z5 NN1 lipstick B4 </li></ul>e-Text annotation - semantics
    25. 25. <ul><li>adding information about anaphoric links, e.g. for MT </li></ul><ul><li>S.1 (0) The state Supreme Court has refused to release{1 [2 Rahway State Prison 2] inmate 1}} (1 James Scott 1) onbail . S.2 (1 The fighter 1) is serving 30-40 years for a 1975 armed robbery conviction . S.3 (1 Scott 1) had asked for freedom while <1 he waits for an appeal decision . </li></ul>e-Text annotation - discourse anaphora
    26. 26. <ul><li>adding information about the modalization, phraseological units, metaphor, kinds of speech act , etc. that occur in a spoken dialog </li></ul><ul><li><IP MOD=interactive>ok?<IP> </li></ul><ul><li><IP PU=proverb MET=true Source=nature Target=prudence>a bird in the hand is worth two in the bush</IP> </li></ul><ul><li><IP SA=request> May I open the window, please?</IP> </li></ul>e-Text annotation - pragmatics
    27. 27. <ul><li>it's about “stylistic features in literary texts” usually S&TP (McEnery et al. 2006:41) </li></ul><ul><li>S&TP = direct speech, indirect speech, free indirect thought, etc (Leech 2004) </li></ul><ul><li><sptag cat=FDS who=K next=FDS whonext=J s=1 w=6> 'Where've you got in mind, sir?' </li></ul>e-Text annotation - stylistics
    28. 28. <ul><li>segmental pronunciation </li></ul><ul><li>prosodic boundaries, prominent syllables and abnormal sound lengthening </li></ul><ul><li>Both highly valuable in accent studies </li></ul><ul><li>ik heb he%m% | n^e^gen maal ontvangen denk ik </li></ul><ul><li>speaker A : jan | en ook piet waren hier al eerder twee jaar geleden </li></ul><ul><li>speaker B : ja| dat weet ik || maar wanneer </li></ul>e-Text annotation - prosody
    29. 29. <ul><li>lem m atization = adding the identity of the lemma (base form) of each word form in a text </li></ul><ul><li>markup = originally text division into paragraphs, font characteristics (all noninterpretative, text -inherent qualities) </li></ul><ul><li>also: markup for speaker/writer identification, useful in sociolinguistics </li></ul>e-Text annotation - lemmatization & markup
    30. 30. <ul><li>accuracy </li></ul><ul><li>annotation= always interpretation. It's never theory free (MWUs, -ing) </li></ul><ul><li>ambiguity tags nothing bad! (better than wrong tags) – e.g. CLAWS ditto tags, portmonteau tags – if consistent! </li></ul><ul><li>the importance to keep “pure” text separately (Sinclair) </li></ul><ul><li>which one, how, where, when applied and by whom ? </li></ul>Limitations of annotation
    31. 31. <ul><li>“ it enriches the corpus a source of linguistic information for future research and development” (Leech 1997) </li></ul><ul><li>fields possibly profiting from it: lexicography, MT, translation studies, discourse studies, pragmatics, literary studies, contrastive linguistics, lg teaching, grammatical lg analysis, TTS synthesis, accent studies, sociolinguistics </li></ul><ul><li>“ no one in their right mind would offer to predict the future uses of a corpus ” Leech, 2004 </li></ul><ul><li>References </li></ul>Why bother?
    32. 32. Michał Remiszewski Towards competence mapping in language teaching/learning
    33. 33. <ul><li>Technology-driven </li></ul><ul><li>Practice-driven </li></ul>Reasons for e-learning
    34. 34. <ul><li>Structured syllabus </li></ul><ul><li>No access to the structure of competence </li></ul>Problem
    35. 35. <ul><li>Synchronic view </li></ul><ul><li>Dynamic view </li></ul>Solution: competence mapping
    36. 36. CLIP ; AMBER ONE
    37. 37. <ul><li>It will allow the creation and administration of interactive language tasks for learners. </li></ul><ul><li>It will automatically check the accuracy of learners’ answers, and not just the obvious multiple choice, but also gap input going way beyond one or two words. </li></ul><ul><li>It will provide exhaustive student performance reports both as stats for large groups as well as individuals. Reports will be delivered to the learner and to the teacher. </li></ul><ul><li>It will help identify problem areas and dynamics in learners’ linguistic competence. </li></ul>AMBER ONE
    38. 38. Włodzimierz Sobkowiak e-text in Second Life: reification of text?
    39. 39. <ul><li>public text-chat , </li></ul><ul><li>Instant Messaging (IM), </li></ul><ul><li>notecards , </li></ul><ul><li>whiteboards , </li></ul><ul><li>object info fields , </li></ul><ul><li>avatar profile info fields , </li></ul><ul><li>inventory contents , </li></ul><ul><li>menu system </li></ul>Types of &quot;ordinary&quot; e-text in SL:
    40. 40. <ul><li>Linguistic symbols, from phonemes/letters to whole texts can be reified into 'rezzed' (created) three-dimensional objects, thus creating innovative manipulative affordances, impossible in First Life and appealing especially to kinaesthetic learners. For example, phonetic dominoes : words reified as moveable and audio-enhanced blocks which attract or repel each other, according to e-FL-relevant phonetic criteria, such as segmental makeup, syllable number, stress pattern, etc. </li></ul>Unique e-text affordances in SL:
    41. 41. Phonetic dominoes ( view from above ) Arrange the nine coloured cubes domino-style to match sounds at the edges of words. Cubes say their name when left-clicked. Here's the list (in alphabet order): apricot, cereal, cream, ketchup, lettuce, milk, pork chops , spoon, T-bone steak .
    42. 42. Phonetic dominoes : close-up view of pork chops ; click to hear You'll find my dominoes in my Virtlantis class room in Second Life.
    43. 43. Other examples of e-text reification: David Merrill's (MIT) 'siftables' (click to watch on YouTube)