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Towards a better understanding of self-selection to teacher training programmes: A case study of a renowned public university in Poland Cover

Towards a better understanding of self-selection to teacher training programmes: A case study of a renowned public university in Poland

Open Access
|Oct 2023

Figures & Tables

Figure 1.

Predicted probability of completing concurrent and consecutive teacher training, by percentile of the average Matura rank outcome and by percentiles of achievements during the first year at UW
Predicted probability of completing concurrent and consecutive teacher training, by percentile of the average Matura rank outcome and by percentiles of achievements during the first year at UW

Figure 2.

Predicted probability of completing consecutive teacher training, by field of studies, and by decile of Matura outcome/first-year achievements
Predicted probability of completing consecutive teacher training, by field of studies, and by decile of Matura outcome/first-year achievements

Predicted probabilities of completing teacher training

(1)(2)(3)(4)(5)(6)
VariableCategoriesConcurrent modeConsecutive modeSTEMHumanForeign languagesSocial sciences
Gender
Male0.47%8.42%9.43%9.80%22.26%0.57%
Female4.54%11.56%13.81%13.63%25.18%1.20%
Social stipend
Yes4.30%13.21%15.29%15.88%28.76%1.06%
No3.32%10.46%11.61%12.20%24.13%1.03%
Number of Matura subjects taken at advanced level
14.89%9.98%15.32%15.41%19.37%0.39%
32.84%11.08%11.44%12.1%25.41%1.06%
51.61%12.27%8.33%9.23%32.27%2.46%
Mode of university programme
full-time4.49%11.32%12.57%13.50%25.83%0.97%
part-time (evening)0.04%5.20%10.39%18.90%8.18%1.69%
part-time3.54%6.20%1.93%6.37%15.64%1.16%
Population of hometown
5,0004.82%9.77%11.78%18.73%19.07%1.07%
500,0003.32%11.08%12.45%12.20%25.59%1.03%
Unemployment rate in hometown
mean − 1 std. dev.3.58%10.53%10.71%12.75%25.19%0.95%
mean + 1 std. dev.3.39%11.19%13.62%13.00%24.44%1.12%
MA/BA
MA-15.20%17.20%16.82%34.38%1.12%
BA-6.67%5.56%8.56%16.49%0.84%
Erasmus experience
Yes-10.55%10.41%6.30%25.72%0.99%
No-11.00%12.65%13.70%24.31%1.06%

Logit regression outcomes: concurrent versus consecutive mode of teacher training

(1)(2)
ConcurrentConsecutive
Gender (f)2.374***0.462***
(0.148)(0.0675)
While in secondary school
General sec. (vs. vocational)0.578***0.666
(0.170)(0.355)
Matura outcome12.54***−4.234**
(1.358)(1.474)
Matura^2−14.24***4.371***
(1.109)(1.045)
N of subjects at advanced level−0.303***0.0785**
(0.0311)(0.0282)
Log_hometown population−0.094***0.0422
(0.0318)(0.0421)
Unemployment in hometown−0.03060.0454
(0.0474)(0.0424)
Local revenues in hometown0.112*−0.187*
(0.0568)(0.0946)
While at the university
Starting on time_0.687***−0.688***
(0.170)(0.140)
1st year achievements 5.924***
(1.555)
1st year achievements^2 −6.513***
(1.378)
Social stipend0.293***0.361***
(0.0752)(0.0667)
Evening mode−4.793***−1.072***
(0.579)(0.213)
Part-time mode−0.267***−0.845***
(0.0799)(0.140)
MA (vs. BA)−0.226***1.199***
(0.0651)(0.0647)
Erasmus experience −0.0638
(0.0616)
constant−6.132***−6.380***
(0.786)(0.972)
Pseudo r20.1950.311
N3977923336

Descriptive statistics (mean, sd) for continuous variables

Independent variablesFull sampleOf which:Restricted sampleOf which
PedagogySTEMHumanitiesForeign languagesSocial Sciences
Hometown population*874,298 (805,313)793,140 (820,562)886,023 (802,214)875,805 (797,393)901,727 (809,809)855,417 (801,783)908,130 (802,173)
Hometown revenues per capita (PLN) ††3,541 (1,826)3,393 (2,124)3,578 (1,834)3590 (1766)3589 (1810)3508 (1961)3613 (1797)
Hometown unemployment (%)††7.99 (5.85)8.45 (5.94)7.892085 (5.84)7.90 (5.74)7.86 (5.91)8.11 (5.96)7.74 (5.78)
Matura subjects at advanced level2.61 (1.05)2.08 (1.08)2.67 (1.01)2.71 (0.87)2.53 (0.98)2.71 (0.98)2.68 (1.11)
Matura outcome (Si sec) †††0.727 (0.152).609 (.140).737 (0.146)0.768 (0.136).0723 (0.139)0.754 (0.139)0.712 (0.156)
Achievements at UW (Si univ) ††††0.557 (0.115).525 (0.095).559 (0.114)(0.576) (0.130)(0.546) (0.120)0.564 (0.114)(0.549) (0.096)

Logit regression outcomes by field: consecutive mode of teacher training

(1)(2)(3)(4)
STEMHumanitiesForeign languagesSocial sciences
Gender (f)0.540***0.411*0.229*0.874*
(0.116)(0.164)(0.110)(0.370)
While in secondary school
General secondary (vs. vocational)−0.02381.2790.9500
(0.582)(0.759)(0.648)(.)
Matura outcome6.5060.290−8.758***−2.727
(3.473)(3.121)(2.174)(8.127)
Matura^2−6.053*−0.03248.889***3.100
(2.503)(2.287)(1.524)(5.629)
N of subjects at advanced level−0.216**−0.161*0.242***0.550***
(0.0696)(0.0645)(0.0402)(0.148)
Log hometown population0.0182−0.1270.119*−0.0114
(0.0938)(0.0964)(0.0602)(0.225)
Unemployment in hometown0.172*0.0111−0.02880.0976
(0.0843)(0.0943)(0.0653)(0.245)
Local revenues in hometown−0.1940.0285−0.191−0.0481
(0.208)(0.214)(0.138)(0.535)
While at the university
Starting on time−0.167−0.700*−1.042***−1.414*
(0.307)(0.308)(0.215)(0.700)
1st year achievements5.752−6.753*11.45***21.00
(3.409)(2.928)(2.457)(12.81)
1st year achievements^2−2.9206.437*−13.48***−17.03
(2.903)(2.670)(2.214)(10.82)
Social stipend0.410***0.340*0.345**0.0373
(0.123)(0.143)(0.106)(0.449)
Evening mode−0.2740.453−1.771***0.679
(1.054)(0.393)(0.370)(0.471)
Part-time mode−2.310**−0.904***−0.856***1.016
(0.746)(0.258)(0.198)(0.632)
MA (vs. BA)1.487***0.827***1.365***0.341
(0.150)(0.145)(0.0934)(0.388)
Erasmus experience−0.282−0.935***0.108−0.0865
(0.154)(0.245)(0.0803)(0.296)
constant−7.683***0.887−5.897***−9.973
(2.072)(2.328)(1.621)(5.592)
Pseudo R20.2550.1180.2760.311
N4975315858157355

Frequencies for categorical variables

VariablesFull sampleOf which:Restricted sampleOf which:
PedagogySTEMHumanitiesForeign languagesSocial Sciences
Dependent variables
Teachers in concurrent mode3.5100-----
Teachers in consecutive mode6.29-10.9010.5712.6724.670.89
Independent variables
Gender
Female69.3096.5369.9253.0976.9385.3867.89
Male30.703.4730.0846.9123.0714.6232.11
Type of secondary school
General97.9996.8298.7599.3398.6799.3297.99
Vocational2.013.181.250.671.330.682.01
Social stipend
receiving12.5620.3813.1314.8416.4013.1410.72
not receiving87.4479.6286.8785.1683.6086.8689.28
Mode of studying
full time75.9572.9084.7598.5188.9387.1372.25
part time11.780.227.780.362.828.1714.39
evening12.2726.887.471.138.254.7013.36
Highest degree obtained
MA52.3444.8048.9450.9448.6446.5449.38
BA47.6655.2051.0649.0651.3653.4650.62
Starting on time
starting the programme on time95.0697.1895.2794.0595.4894.8396.32
joining later4.942.824.735.954.525.173.68
N39,7791,38423,7905,8343,2985,9998,659

Exemplary mechanisms of self-selection to teacher training

Sign of βDescription
sisecsisec2siunivsiuniv2
+0+0Double positive selection. Positive and linear self-selection to teacher training with respect to both Matura score and early achievements at UW
++Thriving specialists. Many teachers recruit themselves from among students who scored low on their Matura, but who perform very well within their UW programme.
000Random selection from among low-profile students. The effect of Matura score on self-selection to teaching is linearly negative. Later experience at the university has no impact on students’ decisions
+00Middling skills selection. Teaching career is not attractive for low-performing students, but its attractiveness increases at a falling rate as we move along the achievements distribution.
0/+0+Falling back students. Achievements on Matura do not affect students’ choices, but teaching is more likely to be chosen be those struggling academically while at UW
+00Mismatched. Prospective teachers had good scores on their Matura, but nevertheless they struggle at their university programme.
00Double negative. Negative and linear self-selection to teacher training with respect to both Matura score and early achievements at UW
DOI: https://doi.org/10.2478/ceej-2023-0021 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001
Language: English
Page range: 371 - 390
Published on: Oct 31, 2023
Published by: Faculty of Economic Sciences, University of Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Mikołaj Herbst, Tomasz Zając, published by Faculty of Economic Sciences, University of Warsaw
This work is licensed under the Creative Commons Attribution 4.0 License.