Torsten Zesch
Biographic Data
| ID | 10103022 |
|---|---|
| NAME | Torsten Zesch |
| GIVEN NAMES | Torsten |
| FAMILY NAME | Zesch |
| SIGNATURE | ZESCH T |
| AFFILIATIONS | University of Duisburg-Essen |
| ORCID | 0000-0002-9678-3825 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Automated Scoring of Teachers’ Pedagogical Content Knowledge – A Comparison Between Human and Machine Scoring
To validly assess teachers’ pedagogical content knowledge (PCK), performance-based tasks with open-response formats are required. Automated scoring is considered an appropriate ap-proach to reduce the resource-intensity of human scoring and to achieve more consistent scor-ing results than human raters. The focus is on the comparability of human and automated scor-ing of PCK for economics teachers. The answers of (prospective) teachers (N=852) to …
Readability for foreign language learning
In this paper, we analyse the differences between L1 acquisition and L2 learning and identify four main aspects: input quality and quantity, mapping processes, cross-lingual influence, and reading experience. As a consequence of these differences, we conclude that L1 readability measures cannot be directly mapped to L2 readability. We propose to calculate L2 readability for various dimensions and for smaller units. It is particularly important to…
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Readability for foreign language learning
In this paper, we analyse the differences between L1 acquisition and L2 learning and identify four main aspects: input quality and quantity, mapping processes, cross-lingual influence, and reading experience. As a consequence of these differences, we conclude that L1 readability measures cannot be directly mapped to L2 readability. We propose to calculate L2 readability for various dimensions and for smaller units. It is particularly important to…
Automated Scoring of Teachers’ Pedagogical Content Knowledge – A Comparison Between Human and Machine Scoring
To validly assess teachers’ pedagogical content knowledge (PCK), performance-based tasks with open-response formats are required. Automated scoring is considered an appropriate ap-proach to reduce the resource-intensity of human scoring and to achieve more consistent scor-ing results than human raters. The focus is on the comparability of human and automated scor-ing of PCK for economics teachers. The answers of (prospective) teachers (N=852) to …
Artificial Intelligence (2 works) · Computer Science (2 works) · Natural language processing (2 works) · Psychology (2 works) · Artificial Intelligence (1 work) · Cognitive psychology (1 work) · Comparability (1 work) · Comprehension (1 work) · Concreteness (1 work) · Context (archaeology) (1 work)