| Publication type: | Conference paper |
| Type of review: | Peer review (abstract) |
| Title: | EFL placement testing for engineering students with automated essay scoring : natural language processing in R |
| Authors: | Gautschi, Curtis |
| et. al: | No |
| Proceedings: | Technische Bildung im Kontext von 'Digitalisierung' / 'Automatisierung' : Tendenzen, Möglichkeiten, Perspektiven - Wege zu technischer Bildung |
| Editors of the parent work: | Petersen, Maren Kammasch, Gudrun |
| Page(s): | 65 |
| Pages to: | 70 |
| Conference details: | 14. Ingenieurpädagogische Regionaltagung 2019, Universität Bremen, 23.-25. Mai 2019 |
| Issue Date: | 2020 |
| Publisher / Ed. Institution: | IPW |
| Publisher / Ed. Institution: | Berlin |
| ISBN: | 978-3-9818728-3-5 |
| Language: | English |
| Subjects: | Automated essay scoring; Placement testing for writing; Computerized assessment; EFL writing assessment |
| Subject (DDC): | 410.285: Computational linguistics 808: Rhetoric and writing |
| Abstract: | This paper describes the design and first results of an Automated Essay Scoring tool and CEFR-level prediction algorithm created and experimentally implemented in an online English placement test in a higher-education setting. The algorithm was developed employing a prediction-accuracy pseudo-black box approach using a small training corpus of texts with known CEFR levels (N=48). Written and run entirely in R, the tool can be integrated with other advanced text analyses possible in R. Efficiently calculating the CEFR levels of large numbers of student essays, the tool is ideal for quick assessment of writing skills for placement purposes. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/21340 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | Applied Linguistics |
| Organisational Unit: | Institute of Language Competence (ILC) |
| Appears in collections: | Publikationen Angewandte Linguistik |
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Gautschi, C. (2020). EFL placement testing for engineering students with automated essay scoring : natural language processing in R [Conference paper]. In M. Petersen & G. Kammasch (Eds.), Technische Bildung im Kontext von ‘Digitalisierung’ / ‘Automatisierung’ : Tendenzen, Möglichkeiten, Perspektiven - Wege zu technischer Bildung (pp. 65–70). IPW.
Gautschi, C. (2020) ‘EFL placement testing for engineering students with automated essay scoring : natural language processing in R’, in M. Petersen and G. Kammasch (eds) Technische Bildung im Kontext von “Digitalisierung” / “Automatisierung” : Tendenzen, Möglichkeiten, Perspektiven - Wege zu technischer Bildung. Berlin: IPW, pp. 65–70.
C. Gautschi, “EFL placement testing for engineering students with automated essay scoring : natural language processing in R,” in Technische Bildung im Kontext von ‘Digitalisierung’ / ‘Automatisierung’ : Tendenzen, Möglichkeiten, Perspektiven - Wege zu technischer Bildung, 2020, pp. 65–70.
GAUTSCHI, Curtis, 2020. EFL placement testing for engineering students with automated essay scoring : natural language processing in R. In: Maren PETERSEN und Gudrun KAMMASCH (Hrsg.), Technische Bildung im Kontext von ‚Digitalisierung‘ / ‚Automatisierung‘ : Tendenzen, Möglichkeiten, Perspektiven - Wege zu technischer Bildung. Conference paper. Berlin: IPW. 2020. S. 65–70. ISBN 978-3-9818728-3-5
Gautschi, Curtis. 2020. “EFL Placement Testing for Engineering Students with Automated Essay Scoring : Natural Language Processing in R.” Conference paper. In Technische Bildung Im Kontext von ‘Digitalisierung’ / ‘Automatisierung’ : Tendenzen, Möglichkeiten, Perspektiven - Wege Zu Technischer Bildung, edited by Maren Petersen and Gudrun Kammasch, 65–70. Berlin: IPW.
Gautschi, Curtis. “EFL Placement Testing for Engineering Students with Automated Essay Scoring : Natural Language Processing in R.” Technische Bildung Im Kontext von ‘Digitalisierung’ / ‘Automatisierung’ : Tendenzen, Möglichkeiten, Perspektiven - Wege Zu Technischer Bildung, edited by Maren Petersen and Gudrun Kammasch, IPW, 2020, pp. 65–70.
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