Please use this identifier to cite or link to this item:
http://doi.org/10.25358/openscience-5243
Authors: | Wahlen, Andreas Kuhn, Christiane Zlatkin-Troitschanskaia, Olga Gold, Christian Zesch, Torsten Horbach, Andrea |
Title: | Automated scoring of teachers’ pedagogical content knowledge : a comparison between human and machine scoring |
Online publication date: | 21-Oct-2020 |
Year of first publication: | 2020 |
Language: | english |
Abstract: | To validly assess teachers’ pedagogical content knowledge (PCK), performance-based tasks with open-response formats are required. Automated scoring is considered an appropriate approach to reduce the resource-intensity of human scoring and to achieve more consistent scoring results than human raters. The focus is on the comparability of human and automated scoring of PCK for economics teachers. The answers of (prospective) teachers (N = 852) to six open-response tasks from a standardized and validated test were scored by two trained human raters and the engine “Educational SCoRIng Toolkit” (ESCRITO). The average agreement between human and computer ratings, κw = 0.66, suggests a convergent validity of the scoring results. The results of the single-sector variance analysis show a significant influence of the answers for each homogeneous subgroup (students = 460, trainees = 230, in-service teachers = 162) on the automated scoring. Findings are discussed in terms of implications for the use of automated scoring in educational assessment and its potentials and limitations. |
DDC: | 300 Sozialwissenschaften 300 Social sciences 330 Wirtschaft 330 Economics |
Institution: | Johannes Gutenberg-Universität Mainz |
Department: | FB 03 Rechts- und Wirtschaftswissenschaften |
Place: | Mainz |
ROR: | https://ror.org/023b0x485 |
DOI: | http://doi.org/10.25358/openscience-5243 |
Version: | Published version |
Publication type: | Zeitschriftenaufsatz |
License: | CC BY |
Information on rights of use: | https://creativecommons.org/licenses/by/4.0/ |
Journal: | Frontiers in education 5 |
Pages or article number: | Art. 149 |
Publisher: | Frontiers Media |
Publisher place: | Lausanne |
Issue date: | 2020 |
ISSN: | 2504-284X |
Publisher URL: | https://doi.org/10.3389/feduc.2020.00149 |
Publisher DOI: | 10.3389/feduc.2020.00149 |
Appears in collections: | JGU-Publikationen |
Files in This Item:
File | Description | Size | Format | ||
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wahlen_andreas-automated_scor-20201021123117590.pdf | 886.22 kB | Adobe PDF | View/Open |