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  4. Publikationen Angewandte Linguistik
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dc.contributor.authorRunte, Maren-
dc.contributor.authorMahlow, Cerstin-
dc.contributor.authorUlasik, Malgorzata Anna-
dc.contributor.authorCho, Sooyeon-
dc.date.accessioned2024-07-12T09:45:42Z-
dc.date.available2024-07-12T09:45:42Z-
dc.date.issued2024-06-26-
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/31099-
dc.description.abstractTo support students when writing their bachelor thesis, early and immediate feedback on structure and linguistic realization of required elements has been proven useful. Feedback should thus influence the writing process and help students produce appropriate products. Automatic feedback systems usually rely on models derived from scientific articles written by established researchers (e.g., Weder 2015) which also serve as examples shown to students. However, student writing is not on the same level as expert writing as students are still in the process to learn and master relevant competences. Automated services, intended to support students learning to write scientific introductions, should thus be based on authentic student writing to offer appropriate feedback. These services should offer feedback on drafts, let writers revise their texts and give feedback with respect to improvements, thus guiding the writing process.Within the project «Digital Literacy in University Contexts», we develop such a service, based on over 5000 student theses written in German from several study fields. So far, we manually annotated 1034 introductions using an adapted scheme (Runte et al. 2022) based on Weder (2015). The extracted 9032 step-annotated sentences served both as a resource for corpus-linguistic investigations and training material for machine learning algorithms. The corpus-linguistic findings were used as additional features both for training models and to define feedback categories to be shown to students. As a result of our corpus-linguistic exploration, we could classify two kinds of keywords: topic-specific and procedural keywords and keyword phrases. Additionally, we identified specific linguistic features associated with certain steps. These findings were used twofold: (1) to train recommender systems for semi-automatic annotation allowing us to annotate a larger amount of introductions needed to train the automatic step detection system, and (2) as input for the creation of 1268 synthetic sentences with the API of OpenAI’s GPT-3 to arrive at a decent amount of balanced training data for our models. Additionally, we use the phrases and features to provide students with real-world examples from fellow students.de_CH
dc.language.isoende_CH
dc.rightsNot specifiedde_CH
dc.subjectCorpus linguisticsde_CH
dc.subjectStudent writingde_CH
dc.subjectAnnotationde_CH
dc.subjectMovede_CH
dc.subjectStepde_CH
dc.subject.ddc410.285: Computerlinguistikde_CH
dc.subject.ddc808: Rhetorik und Schreibende_CH
dc.titleUsing synthetic sentences for developing a corpus-based feedback service for student writingde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementAngewandte Linguistikde_CH
zhaw.organisationalunitInstitute of Language Competence (ILC)de_CH
zhaw.conference.detailsSIG Writing, Paris Nanterre University, France, 26-28 June 2024de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.webfeedDigital Linguisticsde_CH
zhaw.webfeedDIZH Fellowshipde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.funding.zhawDigital Literacy im Hochschulkontext (DigLit)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
Appears in collections:Publikationen Angewandte Linguistik

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Runte, M., Mahlow, C., Ulasik, M. A., & Cho, S. (2024, June 26). Using synthetic sentences for developing a corpus-based feedback service for student writing. SIG Writing, Paris Nanterre University, France, 26-28 June 2024.
Runte, M. et al. (2024) ‘Using synthetic sentences for developing a corpus-based feedback service for student writing’, in SIG Writing, Paris Nanterre University, France, 26-28 June 2024.
M. Runte, C. Mahlow, M. A. Ulasik, and S. Cho, “Using synthetic sentences for developing a corpus-based feedback service for student writing,” in SIG Writing, Paris Nanterre University, France, 26-28 June 2024, Jun. 2024.
RUNTE, Maren, Cerstin MAHLOW, Malgorzata Anna ULASIK und Sooyeon CHO, 2024. Using synthetic sentences for developing a corpus-based feedback service for student writing. In: SIG Writing, Paris Nanterre University, France, 26-28 June 2024. Conference paper. 26 Juni 2024
Runte, Maren, Cerstin Mahlow, Malgorzata Anna Ulasik, and Sooyeon Cho. 2024. “Using Synthetic Sentences for Developing a Corpus-Based Feedback Service for Student Writing.” Conference paper. In SIG Writing, Paris Nanterre University, France, 26-28 June 2024.
Runte, Maren, et al. “Using Synthetic Sentences for Developing a Corpus-Based Feedback Service for Student Writing.” SIG Writing, Paris Nanterre University, France, 26-28 June 2024, 2024.


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