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

Figure 1.

Figure 2.

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%

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)
1st year achievements		5.924***
		(1.555)
1st 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

Descriptive statistics (mean, sd) for continuous variables

Independent variables	Full sample	Of which:	Restricted sample	Of which
		Pedagogy		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 (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)
	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)
1st year achievements	5.752	−6.753*	11.45***	21.00
	(3.409)	(2.928)	(2.457)	(12.81)
1st 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

Frequencies for categorical variables

Variables	Full sample	Of which:	Restricted sample	Of which:
		Pedagogy		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

Exemplary mechanisms of self-selection to teacher training

Sign of β				Description
sisec	sisec2	siuniv	siuniv2
+	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