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Analysis of question text properties for equality monitoring Cover

Analysis of question text properties for equality monitoring

By: Daniel Zahra and  Steven A. Burr  
Open Access
|Oct 2018

Figures & Tables

Table 1

Demographic profile of candidates

Demographic factors

Total

Gender

Female

171

Male

174

Ethnicity

White

201

Asian

 95

Other

 39

Missinga

 10

Disability

No known disability

309

Specific learning difficulty

 17

Other disability

 19

Total sitting the assessment

345

aExcluded from subsequent analyses of Ethnicity

Fig. 1

Data compilation process

Table 2

Pearson correlation coefficients between measures of language complexity and item scores, by demographic factor levels. No correlations were statistically significant at p = 0.05

Measures

Factors

FRE

Grade

Word count

Sentence count

WpS

Gender

Female

0.038

−0.029

0.069

−0.039

−0.018

Male

0.074

−0.051

0.110

−0.026

 0.005

Ethnicity

White

0.057

−0.037

0.080

−0.047

 0.003

Asian

0.062

−0.055

0.116

 0.005

−0.021

Other

0.047

−0.036

0.082

−0.032

−0.028

Disability

No known disability

0.060

−0.043

0.088

−0.033

−0.008

Specific learning difficulty

0.055

−0.056

0.106

−0.012

−0.036

Other disability

0.008

 0.005

0.085

−0.039

 0.049

Overall

0.056

−0.043

0.094

−0.027

−0.015

FRE Flesch Reading Ease, WpS words per sentence

Fig. 2

Scatterplot of word count by average item score. Points coloured by gender for illustration. Items were scored −0.25 for incorrect, 0 for don’t know, and 1 for correct

Language: English
Published on: Oct 23, 2018
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2018 Daniel Zahra, Steven A. Burr, published by Bohn Stafleu van Loghum
This work is licensed under the Creative Commons Attribution 4.0 License.