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Cognitive Load Theory as a Predictor for Citation Count

Ramos, Samuel Karl LU (2021) PSYK11 20202
Department of Psychology
Abstract
The purpose of this study is to examine if the cognitive load that is induced from different degrees of text complexity in scientific abstracts has an influence on how often the study will get cited. While the influence of cognitive load is well documented in research of activities such as attention allocation, decision making and reading comprehension, it is not known whether such effects can also be applied to more complex activities, such as whether a scientific paper will be influential (or not). In the present study, text induced cognitive load in scientific abstracts is captured by using the of Gunning Fog Index (GFI) and Dale-Chall Score (DCS) for text complexity, while also analyzing with the Type-Token Ratio (TTR). These three... (More)
The purpose of this study is to examine if the cognitive load that is induced from different degrees of text complexity in scientific abstracts has an influence on how often the study will get cited. While the influence of cognitive load is well documented in research of activities such as attention allocation, decision making and reading comprehension, it is not known whether such effects can also be applied to more complex activities, such as whether a scientific paper will be influential (or not). In the present study, text induced cognitive load in scientific abstracts is captured by using the of Gunning Fog Index (GFI) and Dale-Chall Score (DCS) for text complexity, while also analyzing with the Type-Token Ratio (TTR). These three text analysis tools capture varying levels of text complexity from word length, sentence length, and lexical sophistication and diversity, which have been shown to impact cognitive load. Apart from examining this relationship per se, the present study also investigates if the three measures of text induced cognitive load varies between different academic fields. The study found TTR to be significantly correlated with the citation count in all three search results while DCS and GFI were not. A post hoc analysis revealed only the DCS as having a significant difference for each comparison within academic disciplines. (Less)
Please use this url to cite or link to this publication:
author
Ramos, Samuel Karl LU
supervisor
organization
course
PSYK11 20202
year
type
M2 - Bachelor Degree
subject
keywords
Cognitive Load Theory, Gunning Fog Index, Type-Token Ratio, Dale-Chall Score
language
English
id
9040516
date added to LUP
2021-02-16 08:09:32
date last changed
2021-02-16 08:09:32
@misc{9040516,
  abstract     = {{The purpose of this study is to examine if the cognitive load that is induced from different degrees of text complexity in scientific abstracts has an influence on how often the study will get cited. While the influence of cognitive load is well documented in research of activities such as attention allocation, decision making and reading comprehension, it is not known whether such effects can also be applied to more complex activities, such as whether a scientific paper will be influential (or not). In the present study, text induced cognitive load in scientific abstracts is captured by using the of Gunning Fog Index (GFI) and Dale-Chall Score (DCS) for text complexity, while also analyzing with the Type-Token Ratio (TTR). These three text analysis tools capture varying levels of text complexity from word length, sentence length, and lexical sophistication and diversity, which have been shown to impact cognitive load. Apart from examining this relationship per se, the present study also investigates if the three measures of text induced cognitive load varies between different academic fields. The study found TTR to be significantly correlated with the citation count in all three search results while DCS and GFI were not. A post hoc analysis revealed only the DCS as having a significant difference for each comparison within academic disciplines.}},
  author       = {{Ramos, Samuel Karl}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Cognitive Load Theory as a Predictor for Citation Count}},
  year         = {{2021}},
}