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

1. Every little helps
Favouritism towards girls
in Polish high-school exams
Michał Krawczyk
University of Warsaw

3. 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).

4. 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

5. 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).

6. 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

7. 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

8. 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

9. Study 2: deviations from kernel
0
.01.02.03.04
0 20 40 60 80
Density kdensity score_written

10. 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

11. 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