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| ELL3077 | Introduction to Corpus Linguistics | 2+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | WESTERN LANGUAGES and LITERATURE (%100 English) | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Doç. Dr. Ali Şükrü ÖZBAY | | Co-Lecturer | Assoc.Prof. Dr. Ali Şükrü ÖZBAY | | Language of instruction | | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to enable students to develop a solid understanding of the theoretical foundations of corpus linguistics and to apply corpus-based methods using tools such as AntConc and Sketch Engine to analyze authentic language data. By the end of the course, students are expected to identify and examine word groups, collocational patterns, multi-word units, and statistical measures, interpret corpus findings both quantitatively and qualitatively, and present their analyses in accordance with academic writing conventions and ethical principles. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | analyze and interpret word groups, collocational patterns, p-frames, and academic keywords using corpus-based methods through the Holmes and ICLE corpora and answer the questions to be asked. | 9 - 12 | 1, | | LO - 2 : | identify thematic patterns, semantic proximity, and synonymy relations based on corpus data and demonstrate quantitative and qualitative differences in academic discourse. and answer the questions to be asked. | 9 - 12 | 1, | | LO - 3 : | formulate data-driven research questions using corpus analysis tools and report their findings in accordance with academic writing conventions | 9 - 12 | 3, | | LO - 4 : | explain or answer the theoretical foundations of corpus linguistics (e.g., data-driven learning, reference corpora, corpus-informed teaching, and ethical considerations) and answe the questions to be asked . | 9 | 3, | | LO - 5 : | apply corpus analysis tools such as AntConc and Sketch Engine to conduct wordlist, concordance (KWIC), collocation, cluster, keyword, and CQL analyses, and answer the technical questions to be asked about these topics. | 9 - 12 - 14 - 15 | 3, | | LO - 6 : | distinguish different types of multi-word units (e.g., collocations, lexical bundles, idioms, p-frames, formulaic sequences, and n-grams) and demonstrate their functions in academic and natural language use through corpus evidence and answer the questions to be asked about these topics. | 12 | 3, | | LO - 7 : | employ statistical measures (e.g., MI score, t-score, cut-off frequency, normalization, and stopword removal) to quantitatively analyze corpus findings and report the results in line with academic writing standards and answer the questions to be asked about these topics. | 12 | 3, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| This course introduces the theoretical and practical foundations of corpus linguistics, focusing on the analysis of authentic language data for linguistic research and language teaching. The course content covers key concepts such as data-driven learning, reference and learner corpora, corpus-informed pedagogy, and ethical considerations in corpus use. Students gain hands-on experience with corpus analysis tools including AntConc and Sketch Engine, learning to conduct wordlist, concordance (KWIC), collocation, cluster, keyword, and CQL analyses. The course also addresses multi-word units (e.g., collocations, lexical bundles, idioms, p-frames, and n-grams), statistical measures (e.g., MI score, t-score, normalization, and cut-off frequency), and the interpretation and reporting of corpus findings in academic contexts. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction to corpus linguistics: the concept of corpus, aims of corpus linguistics, and its applications in linguistics and language teaching. | | | Week 2 | Types of corpora: reference corpora, learner corpora, and specialized corpora; overview of the Holmes and ICLE corpora. | | | Week 3 | Data-Driven Learning (DDL): theoretical background, learner-centered approaches, and pedagogical implications. | | | Week 4 | Corpus-based vs. corpus-informed teaching; ethical issues and copyright considerations in corpus use. | | | Week 5 | Corpus compilation and preprocessing: text selection, cleaning, formatting; stopword removal and normalization. | | | Week 6 | Introduction to AntConc: interface overview, basic settings, and corpus loading. | | | Week 7 | Wordlist and Keyword List analyses in AntConc: frequency analysis and reference corpus comparison. | | | Week 8 | Concordance (KWIC) and Collocates analyses in AntConc: contextual analysis and collocational patterns. | | | Week 9 | Word cluster and n-gram analyses: recurring sequences, cut-off frequency, and interpretation | | | Week 10 | Multi-word units: collocations, lexical bundles, formulaic sequences, and idioms | | | Week 11 | Corpus analysis: Ngram patterns (2-3) Sketch Engine | | | Week 12 | Introduction to Sketch Engine: interface, built-in corpora, and basic search functions | | | Week 13 | Sketch Engine tools: Word Sketch, Sketch Diff, Thesaurus, and Corpus Query Language (CQL). | | | Week 14 | Statistical measures: MI score and t-score; quantitative analysis and qualitative interpretation of corpus findings. | | | Week 15 | Course review and evaluation: student presentations, discussion of corpus-based mini research projects, and overall course reflection. | | | Week 16 | Course review and evaluation: student presentations, discussion of corpus-based mini research projects, and overall course reflection. | | | |
| 1 | Sinclair, John and Renouf, Antoinette (1988),?A lexical syllabus for language learning?, in Carter and M. McCarthy R. (eds), Vocabulary and Language Teaching, (140?160), London and New York: Longman. | | | 2 | Sinclair, John (2005), ?Corpus and text - basic principles?, in M. Wynne (Ed.), Developing Linguistic Corpora: A Guide to Good Practice (1-16). Oxford: Oxbow Books. Retrieved from from: http://ahds.ac.uk/linguistic-corpora/. | | | |
| 1 | Schmitt, Norbert (ed.) (2004), Formulaic Sequences, Amsterdam: Benjamins. | | | 2 | O'Keeffe, Anne et et al. (2007), From Corpus to Classroom, Cambridge, Cambridge University Press. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 8 | | 2 | 25 | | Project | 11 | | 100 | 25 | | Homework/Assignment/Term-paper | 15 | | | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 2 | 14 | 28 | | Arasınav için hazırlık | 6 | 2 | 12 | | Arasınav | 2 | 1 | 2 | | Uygulama | 4 | 8 | 32 | | Proje | 8 | 4 | 32 | | Dönem sonu sınavı için hazırlık | 6 | 2 | 12 | | Dönem sonu sınavı | 2 | 1 | 2 | | Total work load | | | 120 |
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