Overview
Kompost ― Identification of indicators for competence assessment of students’ essays and development of a prototype for computer-assisted text analysis
Description
Using methods from computational linguistics, this project will identify indicators of the quality of students’ texts in the German language. Special emphasis will be placed on the evolution of those quality indicators across competence levels, i.e. the development of observable parameter values over time as the students’ language skills improve. The study will be based on essays, test results, students’ attitudes and personal information from the city of Hamburg’s longitudinal KESS study, as well as material from other surveys. The core of this dataset is comprised of approximately 9000 essays which were rated along several dimensions.
Language test results from the same pupils serve as an external criterion for the validation of the ratings and will also be related to the indicators in order to detect additional oblique patterns which a less objective and reliable human reader would be unable to find.
The research on the competence indicators will form the basis for the development of an online tool for the automated assessment of text quality. The tool will be created in close consultation with students and teachers and will provide the users with feedback in an easily accessible format. Furthermore, the results of the automated text analysis will be used in turn to inform the continued development of competence models.
Duration
01.11.2009 - 31.10.2012
Staff
Anke Lüdeling, Jasmine Bennöhr, Burkhard Dietterle
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Results
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