Educational texttechnology : quantifying task descriptions in a multilingual setting
- This thesis explores a variety of methods of text quantification applicable in the field of educational text technology. Besides the cohort of existing linguistic, lexical, syntactic, and semantic text quantification methods, additional methods based on Bidirectional Encoder Representations from Transformers (BERT) are introduced and analysed. The model, developed in this thesis, is tested on a multilingual data composed of task descriptions used in Test of Understanding in College Economics (TUCE). Quantitative features extracted from raw textual data are analysed using an array of evaluation methods with the goal of finding the best predictors of the target variable - the rate of correct student responses in TUCE.
Author: | Maksims Konca |
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URN: | urn:nbn:de:hebis:30:3-592128 |
Advisor: | Alexander Mehler |
Document Type: | Bachelor Thesis |
Language: | English |
Date of Publication (online): | 2021/03/24 |
Year of first Publication: | 2020 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Granting Institution: | Johann Wolfgang Goethe-Universität |
Date of final exam: | 2020/12/15 |
Release Date: | 2021/05/21 |
Tag: | Educational texttechnology |
Page Number: | 67 |
HeBIS-PPN: | 481475567 |
Institutes: | Informatik und Mathematik |
Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Sammlungen: | Universitätspublikationen |
Licence (German): | Deutsches Urheberrecht |