Claudia Kunschak Marcia Peterson Shantou University Training in error identification -Paving the way toward learner autonomy Claudia Kunschak Marcia Peterson Shantou University

Motivation for research English teaching reform Communicative Language Teaching “They know their grammar” “We don’t want/need grammar, we’ve had it for the past 8/10/12 years” Test focus Perceived gap competence-performance Grammar in context/text grammar in CLT

Previous studies and theoretical underpinnings James, C. (1998) Error vs. mistake Grammaticality-acceptability-correctness-strangeness or infelicity Detection-location-description-classification of errors => profiling Substance, text, lexical, grammar, discourse error Noticing error Chu, C. (1998): Chinese grammar has to be understood on the discourse level Huang, X. (2005): Grammar, use of words and textual cohesion are main difficulties for Chinese learners Ferris, D. (2003): Students can attend to macro- and micro-level feedback at the same time Wong, H. & Storey, P. (2006): Awareness of writing process improves production Little, D. (2002): Learner autonomy provides effective and efficient, motivational and social environment

Research questions Why is there such a wide gap between competence and performance in selected grammatical features? How can this gap be narrowed? How do Chinese learners self-evaluate their grammatical competence/performance? What importance do they attribute to grammar in the various skills and in general? How are they analyzing text when revising? What difference does language awareness training in the form of error identification make?

Study design 9 groups of 30+ students 3 levels Experimental and control groups Pre-test, post-test, exercises, interviews Text with 6 verb-tense errors, 3 subject-verb agreement, 3 articles, 3 pronouns Comparison with MC placement test

Findings from the placement test compared to error identification 86.76 % correct answers in MC 30.16 % correct identifications in pretest OVERALL PG Pre-test Tier 1 79.52 27.29 Tier 2 87.02 29.12 Tier 3 93.84 34.08

Placement test vs. error identification in verb tense 79.84% correct answers in verb tenses 26.27% correct identifications in pretest VERB TENSE PG Pre-test Tier 1 71.81 24.81 Tier 2 78.71 24 Tier 3 89 30

Error identification pre-test vs post-test Tier 1 27.33 35.33 Tier 2 28.66 37.33 Tier 3 34 41.33

Error identification per tier total identified correctly incorrectly not Tier 1 pre 78.66 27.33 51.33 72.66 Tier 1 post 80.66 35.33 45.33 65.33 Tier 2 pre 71.33 28.66 42.66 Tier 2 post 77.33 37.33 40.66 62.33 Tier 3 pre 74.66 34 66 Tier 3 post 86 41.33 58.66

Error identification experimental-control CORRECT Class 1 Class 2 Class 3 Class 4 Tier 1 pre 25 30 26.88 Tier 1 post 31.33 26 36.66 Tier 2 pre 27.92 29.89 29.19 29.49 Tier 2 post 32.66 43.33 34.66 26.66 Tier 3 pre 33.79 34.37 Tier 3 post 38.66

Baseline data 7 native speaking teachers total correct incorrect not IDd average 102.8 75.2 27.61 24.56

Breakdown by majors MAJORS Tier 1 Tier 2 Tier 3 Liberal Arts 36.66 34.66 44 Mathematics 35.33 45.33 43.33 Science 38 Engineering 33.33 35.55 38.66 Education 46.66 42.66 Admin. Mgmt 39.13 Business Art&Design 26 26.66

Interviews Students declared they understood the meaning of the text but not the grammar Students admitted that they chose the errors mainly based on their gut feeling Students picked errors for the wrong reason (verb tense, verb/adj., sg./pl.) – Corrections were not always ascertained Students were able explain their choices based on rules but sometimes overapplied them When prompted, students were able to explain items they had not chosen Students expressed a preference for listening/speaking over writing

Examples of errors chosen for the wrong reason As hospital personnel working in maternity are aware for a long time now… personnel as singular, aware as verb When the calm infant hear the sound of other infants crying, they… “the” must be singular, hear follows infant …they too begin to sob. too in the end=>also, too+adj+to+verb

Suggestions from students More feedback on writing Error identification exercises Grammar self-study Correct input by teacher Some sentences written on the board Translation Chinese-English Few are willing to exchange journals

Discussion Obvious gap between rule-based knowledge and applied grammar SVA –– Verb tense - Pronoun – Article Visible difference according to level Clear difference pre- post No consistent difference experimental-control Additional gap between identification and correction

Implications Continued integrated skills approach New approach to grammar review Involvement of students Support of teachers Based on language awareness Focused on typical problem areas Emphasis on writing Potential expansion to include listening/speaking

References Krashen, S. (1981) Second language learning and second language acquisition. Oxford: Pergamon Press. Pienemann, M. (1998) Language processing and second language development: Processability theory. Amsterdam: John Benjamins. James, C. (1998) Errors in language learning and use: Exploring Error Analysis. London: Longman. Connor, U. (1996). Contrastive Rhetoric: Cross-cultural aspects of second language writing. Cambridge: Cambridge University Press. Ferris, D. (2003). Response to student writing: Implications for second language students. Mahwah, NJ: Lawrence Erlbaum. Huang, X. (2005). Multilevel analysis of Chinese EFL learners’ errors in their writing. Celea Journal 28(5), 24-32. Chu, C. (1998). A discourse grammar of Mandarin Chinese. New York: Peter Lang. Hengeveld, K. & Mackenzie, J L. (2006). Functional discourse grammar. In Keith Brown (Ed.), Encyclopedia of language and linguistics (2nd ed.), pp. 668-676. Amsterdam: Elsevier. Little, D. (2002). Learner autonomy and second/foreign language learning. In The guide to good practice for learning and teaching in languages, linguistics and area studies. LTSN Subject Center for Languages, Linguistics and Area Studies. University of Southampton. Wong, H. & Storey, P. (2006). Knowing and doing in the ESL writing class. Language Awareness 15(4), 283-300.