Dominant achievement goals and academic outcomes across tracks in high school

Figures & data

Table 1. Sample (S) data and comparison with population (P).

Track	Sample (S)		Population (P)		Difference
	N	%	N	%	S–P
A	3863	27.7	41,858	23.8	+3.9
B	3968	28.4	38,234	21.8	+6.6
C	3450	24.7	49,106	27.9	−3.2
D	1618	11.6	26,637	15.2	−3.6
E	1071	7.7	19,932	11.3	−3.6
total	13,970	100.1	175,767	100.0	.1

Table 2. The instrument used to determine the Dominant Achievement Goal (DAG) in 2011.

For each item, choose either A or B
This year, I find it most important in school …
	A			B
(1)		to get higher grades than most of my classmates	òr		not to get lower grades than most of my classmates
(2)		to get higher grades than to which I am normally capable	òr		not to get lower grades than to which I am normally capable
(3)		to get higher grades than most of my classmates	òr		to get higher grades than to which I am normally capable
(4)		not to get lower grades than to which I am normally capable	òr		not to get lower grades than most of my classmates
(5)		not to get lower grades than most of my classmates	òr		to get higher grades than to which I am normally capable
(6)		not to get lower grades than to which I am normally capable	òr		to get higher grades than most of my classmates

Table 3. Distributional characteristics.

	N	Min.	Max.	M	SD	%
Grade Dutch	13,768	.0	9.9	6.72	.95
Grade English	13,757	.0	9.9	6.78	1.23
Grade math	13,620	.0	9.9	6.68	1.37
Gender (girl)	14,911					51.12
Self-efficacy	14,796	1.00	5.00	3.51	.65
IQ	13,764	44.49	152.38	100.24	14.87

Table 4. Variance-covariance matrix with S.E. and correlations (bold) for the random part of Model 1 on the three levels.

	Dutch	English	Math
School level
Dutch	.044 (.010)	.023 (.009)	.019 (.011)
English	.444	.059 (.014)	.028 (.013)
Math	.283	.362	.105 (.021)
Class level
Dutch	.129 (.010)	.059 (.009)	.035 (.009)
English	.370	.197 (.016)	.044 (.011)
Math	.238	.282	.176 (.016)
Student level
Dutch	.722 (.009)	.306 (.009)	.310 (.010)
English	.318	1.281 (.016)	.193 (.013)
Math	.287	.134	1.617 (.021)

Table 5. Student characteristics, DAG, track and their effect on grades Dutch, English and Math.

	Model
	2. Student Characteristics						3. Student Characteristics, DAG and Track^a
	Grade Dutch		Grade English		Grade Math		Grade Dutch			Grade English		Grade Math
Fixed part	β	SE	β	SE	β	SE	β	SE		β	SE	β	SE
Characteristic
Intercept	6.525***	.028	6.721***	.033	6.698***	.0039	6.605***	.054		6.501***	.067	6.895***	.076
Gender (girl)	.419***	.016	.095***	.022	−.023	.023	.416***	.016		.093***	.022	−.024	.024
IQ	.006***	.001	.005***	.001	.027***	.001	.006***	.001		.005***	.001	.027***	.001
Self-efficacy	.255***	.012	.308***	.017	.507***	.018	.246***	.013		.294***	.017	.495***	.019
Pap							.237***	.038		.249***	.052	.236***	.056
Pav							−.017	.030		−.030	.042	−.023	.045
Map							−.001	.025		−.014	.034	.014	.037
Mav							.043*	.022		−.021	.031	.013	.033
Track A							.064	.062		.577***	.076	.015	.084
Track B							−.278***	.061		.058	.075	−.288***	.083
Track C							−.188***	.058		.152*	.071	−.316***	.078
Track D							−.064	.055		.184**	.069	−.475***	.075
Random Part
Variance at school level	.047***	.011	.058***	.014	.104***	.021	.045***	.010		.056***	.013	.097***	.020
Variance at class level	.136***	.010	.194***	.016	.191***	.016	.113***	.009		.145***	.013	.159***	.015
Variance at student level	.648***	.009	1.233***	.017	1.405***	.019	.646***	.009		1.123***	.017	1.403***	.019
Total variance	.831		1.488		1.700		.804			1.324		1.659
ICC school	.057		.039		.061		.056			.042		.059
ICC school +class	.220		.170		.174		.197			.152		.154
Model Fit
−2*loglikelihood:	102,698.388						102,408.500
Number of schools	123						123
Number of classes	834						834
Number of students	11,925						11,925

^a In model 3 the group without a DAG serves as the reference group for the variable DAG and track E serves as the reference group for the variable Track.

^* p < .05

^** p < .01

^*** p < .001.

Table 6. Student characteristics, DAG, track, DAG*Track and their effect on Grades Dutch, English and Math.

Fixed Part	Model
	4. Student characteristics, DAG, track and DAG*Track^a
	Grade Dutch			Grade English		Grade Math
	β	SE		β	SE	β	SE
Characteristic
Intercept	6.603***	.067		6.545***	.086	6.926***	.096
Gender (girl)	.415***	.016		.090***	.022	−.026	.024
IQ	.006***	.001		.005***	.001	.027***	.001
Self-efficacy	.246***	.013		.293***	.017	.494***	.019
Pap	.074	.105		.050	.144	.192	.159
Pav	.042	.106		.033	.143	−.078	.156
Map	.081	.082		−.128	.112	.031	.124
Mav	.019	.084		−.027	.115	−.093	.127
Track A	.093	.085		.498***	.111	.054	.122
Track B	−.280***	.081		−.061	.104	−.238***	.115
Track C	−.229***	.077		.137	.101	−.420***	.109
Track D	.008	.078		.217*	.104	−.529***	.114
Pap*TrackA	.345**	.135		.383**	.185	.257	.202
Pap*TrackB	.158	.132		.285*	.181	.050	.198
Pap*TrackC	.171	.127		.295**	.174	.008	.190
Pap*TrackD	.044	.140		−.164	.192	−.161	.212
Pav*TrackA	−.099	.124		.057	.169	−.123	.182
Pav*TrackB	−.054	.120		−.020	.163	−.072	.177
Pav*TrackC	−.022	.121		−.222*	.164	.156	.179
Pav*TrackD	−.099	.134		−.020	.163	.156	.199
Map*TrackA	−.139	.100		.047	.137	−.128	.149
Map*TrackB	−.065	.095		.235**	.130	−.098	.142
Map*TrackC	−.037	.094		.105	.129	.111	.142
Map*TrackD	−.133	.104		.122	.142	.051	.157
Mav*TrackA	−.009	.097		.057	.133	.036	.146
Mav*TrackB	−.026	.093		−.094	.128	.065	.141
Mav*TrackC	−.099	.094		−.030	.129	.195*	.142
Mav*TrackD	−.066	.104		−.181	.143	.144	.158
Random Part
Variance at school level	.044***	.010		.057***	.013	.097***	.020
Variance at class level	.113***	.009		.146***	.013	.159***	.015
Variance at student level	.645***	.009		1.227***	.016	1.400***	.019
Total variance	.802			1.430		1.656
ICC school	.055			.040		.059
ICC school +class	.196			.142		.155
Model Fit
−2*loglikelihood:	102,330.3014
Number of schools	123
Number of classes	834
Number of students	11,925

^a In model 4 the group without a DAG serves as the reference group for the variable DAG and track E serves as the reference group for the variable Track.

^* p < .10

^** p < .05

^*** p < .001.

Table 7. Spread in Grades per track based on Model 4.

	a	b	c	d	e
Dutch
Pap^a	.477	.244	.245	.175	.074
Pav	.001	.000	.020	.000	.042
Map	.000	.028	.044	.005	.081
Mav	.068	.057	.118	.010	.019
ndag	.058	.012	.000	.057	.000
English
Pap	.357	.335	.534	.094	.178
Pav	.174	.013	.000	.221	.161
Map	.113	.107	.166	.312	.000
Mav	.000	.067	.132	.000	.101
ndag	.084	.000	.189	.208	.128
Math
Pap	.650	.309	.200	.031	.285
Pav	.000	.061	.078	.078	.015
Map	.104	.000	.142	.082	.124
Mav	.144	.039	.102	.051	.000
ndag	.201	.067	.000	.000	.093

^a Per track and per subject the smallest predicted value was subtracted from the other predicted values.