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Every little helps
Favouritism towards girls
in Polish high-school exams
Michał Krawczyk
University of Warsaw
Does student’s gender affect
evaluation? Previous evidence
• Main strategy: relatively objective measures
(external and/or...
Deos it depend on the subject?
• Girls favoured in math etc., boys in literature
etc. (Breda and Ly, 2014, Lindahl, 2007 a...
It may not be due to teacher’s bias
• Girls tend to work harder during the year (so
perhaps deserve higher grades for cour...
Experiments
• Hinnerich et al. (2014): randomly selected exams
were anonymously re-graded. While overall
scores were much ...
Present project
• Data from matura exams 2010-2014
• Compulsory written exams in
Polish+foreign+math
• Oral in Polish+fore...
Oral exam in lang. (score 0-20): tobit
----------------------------------------------------------------------------------
...
Study 2: deviations from kernel
0
.01.02.03.04
0 20 40 60 80
Density kdensity score_written
Proportion of those whose score not
updated (upwards): written (t’hold 21)
Two-sample test of proportions 18-20 x: Number ...
Proportion of those whose score not
updated (upwards): oral (threshold 6)
Two-sample test of proportions 3-5 x: Number of ...
Everry little helps. Favouritism towards girls in Polish high-school exams
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Everry little helps. Favouritism towards girls in Polish high-school exams

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Prezentacja Michała Krawczyka na seminarium wewnętrznym GRAPE w listopadzie 2015 o faworyzowaniu płci na egzaminach w polskich liceach.

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Everry little helps. Favouritism towards girls in Polish high-school exams

  1. 1. Every little helps Favouritism towards girls in Polish high-school exams Michał Krawczyk University of Warsaw
  2. 2. Does student’s gender affect evaluation? Previous evidence • Main strategy: relatively objective measures (external and/or blind tests) vs. relatively subjective measures (tests marked by teachers, grades also reflecting coursework, oral presentations etc.). • Favouritism towards girls: Lavy (2008), Lindahl (2007), Angelo (2014), Falch and Naper (2013), Terrier (2014) Rauschenberg (2014).
  3. 3. Deos it depend on the subject? • Girls favoured in math etc., boys in literature etc. (Breda and Ly, 2014, Lindahl, 2007 and Cornwell et al., 2013). • (consistent with a theoretical paper by Mechtenberg, 2009) • Enzi (2015): exactly the opposite finding
  4. 4. It may not be due to teacher’s bias • Girls tend to work harder during the year (so perhaps deserve higher grades for course work). • Girls tend to show greater social skills, a more positive attitude towards the learning process etc., for which they are rewarded in class, see Cornwell et al. (2011) • Girls may underperform at objective, centralized exams due to greater test anxiety (Cassady and Johnson, 2008).
  5. 5. Experiments • Hinnerich et al. (2014): randomly selected exams were anonymously re-graded. While overall scores were much worse, this did not interact significantly with gender. • Van Ewijk (2010) and Sprietsma (2013) let teachers evaluate same essays signed as boy/girl, member of ethnic minority/majority. Typically no significant impact of gender • Costly, so smaller samples • Artificial, so teachers may behave differently
  6. 6. Present project • Data from matura exams 2010-2014 • Compulsory written exams in Polish+foreign+math • Oral in Polish+foreign • Study 1: Evaluation of oral exams may be more subjective and gender-biased than written exams • Study 2: Obviously arbitrary score adjustment around threshold may be gender-biased
  7. 7. Oral exam in lang. (score 0-20): tobit ---------------------------------------------------------------------------------- Variable | POL1 POL2 ENG1 ENG2 GER1 GER2 -------------+-------------------------------------------------------------------- score_writ. | .149*** .140*** .289*** .251*** .405*** .367*** score_wr^2 | .0003*** .0004*** .004*** .005*** .003*** .003*** female | .435*** .423*** .512*** .493*** .053 .032 town_to_20k | -.073*** -.311*** -.004 town_to_100k | .082*** -.484*** -.242* city_fr~100k | -.625*** -1.465*** -.774*** adult | -.396*** -1.016*** -.888*** special | 1.363*** .024 1.111 dyslexia | .151*** .109** -.142 first_time | 2.323*** 2.553*** 2.041*** _cons | 7.822*** 5.900*** 4.545*** 3.384*** 2.432*** 1.329*** -------------+----------------------------------------------------------------- N | 1628,009 1628,009 537,335 537,335 62,580 62,580
  8. 8. Study 2: deviations from kernel 0 .01.02.03.04 0 20 40 60 80 Density kdensity score_written
  9. 9. Proportion of those whose score not updated (upwards): written (t’hold 21) Two-sample test of proportions 18-20 x: Number of obs = 15577 y: Number of obs = 18667 ------------------------------------------------------------------------------ Variable | Mean Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Female | .1269179 .0026671 .1216904 .1321454 male | .1433546 .0025649 .1383275 .1483817 -------------+---------------------------------------------------------------- diff | -.0164367 .0037003 -.0236892 -.0091842 | under Ho: .0037186 -4.42 0.000 ------------------------------------------------------------------------------ diff = prop(x) - prop(y) z = -4.4202 Two-sample test of proportions: 19-20 x: Number of obs = 10981 y: Number of obs = 13096 ------------------------------------------------------------------------------ Variable | Mean Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- x | .0476277 .0020324 .0436443 .0516112 y | .0584148 .0020494 .0543981 .0624315 -------------+---------------------------------------------------------------- diff | -.0107871 .0028863 -.0164441 -.00513 | under Ho: .0029116 -3.70 0.000 ------------------------------------------------------------------------------ diff = prop(x) - prop(y) z = -3.7049
  10. 10. Proportion of those whose score not updated (upwards): oral (threshold 6) Two-sample test of proportions 3-5 x: Number of obs = 53210 y: Number of obs = 53108 ------------------------------------------------------------------------------ Variable | Mean Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- Female | .0819771 .0011893 .0796462 .084308 Male | .1043157 .0013264 .1017161 .1069154 -------------+---------------------------------------------------------------- diff | -.0223387 .0017815 -.0258303 -.018847 | under Ho: .0017826 -12.53 0.000 ------------------------------------------------------------------------------ diff = prop(x) - prop(y) z = -12.5314 Two-sample test of proportions: 4-5 x: Number of obs = 38868 y: Number of obs = 38388 ------------------------------------------------------------------------------ Variable | Mean Std. Err. z P>|z| [95% Conf. Interval] -------------+--------------------------------------------------------------- Female | .0844654 .0014105 .0817008 .0872299 Male | .1042774 .0015599 .1012201 .1073346 -------------+---------------------------------------------------------------- diff | -.019812 .002103 -.0239339 -.0156901 | under Ho: .002103 -9.42 0.000 ------------------------------------------------------------------------------ diff = prop(x) - prop(y) z = -9.4208

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