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

Variables	Full sample	Of which:	Restricted sample	Of which:
Variables	Full sample	Pedagogy	Restricted sample	STEM	Humanities	Foreign languages	Social Sciences
*Dependent variables*
Teachers in concurrent mode	3.5	100	-	-	-	-	-
Teachers in consecutive mode	6.29	-	10.90	10.57	12.67	24.67	0.89
*Independent variables*
Gender
Female	69.30	96.53	69.92	53.09	76.93	85.38	67.89
Male	30.70	3.47	30.08	46.91	23.07	14.62	32.11
Type of secondary school
General	97.99	96.82	98.75	99.33	98.67	99.32	97.99
Vocational	2.01	3.18	1.25	0.67	1.33	0.68	2.01
Social stipend
receiving	12.56	20.38	13.13	14.84	16.40	13.14	10.72
not receiving	87.44	79.62	86.87	85.16	83.60	86.86	89.28
Mode of studying
full time	75.95	72.90	84.75	98.51	88.93	87.13	72.25
part time	11.78	0.22	7.78	0.36	2.82	8.17	14.39
evening	12.27	26.88	7.47	1.13	8.25	4.70	13.36
Highest degree obtained
MA	52.34	44.80	48.94	50.94	48.64	46.54	49.38
BA	47.66	55.20	51.06	49.06	51.36	53.46	50.62
Starting on time
starting the programme on time	95.06	97.18	95.27	94.05	95.48	94.83	96.32
joining later	4.94	2.82	4.73	5.95	4.52	5.17	3.68
N	39,779	1,384	23,790	5,834	3,298	5,999	8,659

Table 1b.

Descriptive statistics (mean, sd) for continuous variables

Independent variables	Full sample	Of which:	Restricted sample	Of which
Independent variables	Full sample	Pedagogy	Restricted sample	STEM	Humanities	Foreign languages	Social 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 level	2.61 (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 (S_{i 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 (S_{i 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)

† Natural logarithm of the variable used in the estimation;

†† Variables are standardized (0,1) within student cohorts in the estimation;

††† Relative to all Matura takers in Poland within the same cohort;

†††† Relative to UW students within the same cohort taking the same courses during the 1^st year of the programme

* Student's hometown is the town where he/she attended secondary school

Table 2.

Exemplary mechanisms of self-selection to teacher training

Sign of β				Description
*s_{i_sec}*	s_{i_sec}²	*s_{i_univ}*	s_{i_univ}²	Description
+	0	+	0	Double 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.
−	0	0	0	Random 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
+	−	0	0	Middling 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
+	0	−	0	Mismatched. Prospective teachers had good scores on their Matura, but nevertheless they struggle at their university programme.
−	0	−	0	Double negative. Negative and linear self-selection to teacher training with respect to both Matura score and early achievements 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

Table 3.

Logit regression outcomes: concurrent versus consecutive mode of teacher training

	(1)	(2)
	Concurrent	Consecutive
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 outcome	12.54^***	−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	−0.0306	0.0454
	(0.0474)	(0.0424)
Local revenues in hometown	0.112^*	−0.187^*
	(0.0568)	(0.0946)
*While at the university*
Starting on time_	0.687^***	−0.688^***
	(0.170)	(0.140)
1^st year achievements		5.924^***
		(1.555)
1^st year achievements^2		−6.513^***
		(1.378)
Social stipend	0.293^***	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 r²	0.195	0.311
N	39779	23336

Standard errors in parentheses

* p < 0.05,

** p < 0.01,

*** p < 0.001

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

Table 4.

Logit regression outcomes by field: consecutive mode of teacher training

	(1)	(2)	(3)	(4)
	STEM	Humanities	Foreign languages	Social 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)	−0.0238	1.279	0.950	0
	(0.582)	(0.759)	(0.648)	(.)
Matura outcome	6.506	0.290	−8.758^***	−2.727
	(3.473)	(3.121)	(2.174)	(8.127)
Matura^2	−6.053^*	−0.0324	8.889^***	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 population	0.0182	−0.127	0.119^*	−0.0114
	(0.0938)	(0.0964)	(0.0602)	(0.225)
Unemployment in hometown	0.172^*	0.0111	−0.0288	0.0976
	(0.0843)	(0.0943)	(0.0653)	(0.245)
Local revenues in hometown	−0.194	0.0285	−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)
1^st year achievements	5.752	−6.753^*	11.45^***	21.00
	(3.409)	(2.928)	(2.457)	(12.81)
1^st year achievements^2	−2.920	6.437^*	−13.48^***	−17.03
	(2.903)	(2.670)	(2.214)	(10.82)
Social stipend	0.410^***	0.340^*	0.345^**	0.0373
	(0.123)	(0.143)	(0.106)	(0.449)
Evening mode	−0.274	0.453	−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 R²	0.255	0.118	0.276	0.311
N	4975	3158	5815	7355

Standard errors in parentheses

* p < 0.05,

** p < 0.01,

*** p < 0.001

Specification includes also dummies for student cohorts, faculties at UW, and regions (voivodeships) in which students have graduated from secondary school

Table 5.

Predicted probabilities of completing teacher training

		(1)	(2)	(3)	(4)	(5)	(6)
Variable	Categories	Concurrent mode	Consecutive mode	STEM	Human	Foreign languages	Social sciences
Gender
	Male	0.47%	8.42%	9.43%	9.80%	22.26%	0.57%
	Female	4.54%	11.56%	13.81%	13.63%	25.18%	1.20%
Social stipend
	Yes	4.30%	13.21%	15.29%	15.88%	28.76%	1.06%
	No	3.32%	10.46%	11.61%	12.20%	24.13%	1.03%
Number of Matura subjects taken at advanced level
	1	4.89%	9.98%	15.32%	15.41%	19.37%	0.39%
	3	2.84%	11.08%	11.44%	12.1%	25.41%	1.06%
	5	1.61%	12.27%	8.33%	9.23%	32.27%	2.46%
Mode of university programme
	full-time	4.49%	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-time	3.54%	6.20%	1.93%	6.37%	15.64%	1.16%
Population of hometown
	5,000	4.82%	9.77%	11.78%	18.73%	19.07%	1.07%
	500,000	3.32%	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%

* The table does not include the variables related to students’ academic achievements, for which the probabilities are shown in more detail in figures 1 and 2, or these sociodemographic variables which proved insignificant in all specifications.

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.2478/ceej-2023-0021 | Journal eISSN: 2543-6821 | Journal ISSN: 2544-9001

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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

Keywords:

Teacher education,

Concurrent training,

Consecutive training,

Self-selection,

University,

Poland

JEL:

I21,

I23,

I28

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures,

Microeconomics,

Macroeconomics,

Economic policy

© 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.

Volume 10 (2023): Issue 57 (January 2023)

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

Figures & Tables

Table 1a.

Table 1b.

Table 2.

Figure 1.

Table 3.

Figure 2.

Table 4.

Table 5.

Paradigm

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