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Potsdam Textbook Corpus (PoTeC)


Jäger, Lena A; Kern, Thomas; Haller, Patrick (2021). Potsdam Textbook Corpus (PoTeC). OSF: Open Science Framework.

Abstract

The Potsdam Textbook Corpus (PoTeC) is a corpus of eye-tracking-while-reading data where participants (N=75) read a series of German short texts taken from college level textbooks of physics and biology. The experiments were conducted within a 2x2 fully-crossed factorial design with the reader’s expertise (advanced vs beginner) and major (physics vs biology) as factors. Reading comprehension was assessed using text comprehension questions. Moreover, background questions that required additional knowledge beyond the presented text tested the general domain knowledge.
The repository contains the eye-movement data (1000 Hz) as well as the stimulus text data with extensive linguistic feature annotations at the sub-lexical, lexical und supra-lexical level. Therefore, the PoTeC is ideal for studying cognitive processes related to sentence comprehension at all linguistic levels (e.g. lexical, syntactic, discourse) as well as higher-level text comprehension.

Abstract

The Potsdam Textbook Corpus (PoTeC) is a corpus of eye-tracking-while-reading data where participants (N=75) read a series of German short texts taken from college level textbooks of physics and biology. The experiments were conducted within a 2x2 fully-crossed factorial design with the reader’s expertise (advanced vs beginner) and major (physics vs biology) as factors. Reading comprehension was assessed using text comprehension questions. Moreover, background questions that required additional knowledge beyond the presented text tested the general domain knowledge.
The repository contains the eye-movement data (1000 Hz) as well as the stimulus text data with extensive linguistic feature annotations at the sub-lexical, lexical und supra-lexical level. Therefore, the PoTeC is ideal for studying cognitive processes related to sentence comprehension at all linguistic levels (e.g. lexical, syntactic, discourse) as well as higher-level text comprehension.

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Additional indexing

Item Type:Scientific Publication in Electronic Form
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English, German
Date:22 January 2021
Deposited On:13 Jan 2022 14:09
Last Modified:14 Mar 2022 08:44
Publisher:Open Science Framework
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://osf.io/dn5hp/

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