In Germany, extraordinarily talented junior athletes are given the chance to attend so-called elite schools of sport (ESSs). These schools seek to provide a school setting in which the daily routines of athletic high-performance training can be optimally adjusted with the affordances of regular school education (Alfermann & Preis, 2013). Nevertheless, elite student-athletes have to cope with the problem of organizing their dual careers (Borggrefe & Cachay, 2012). They are obliged to coordinate the role of being a high-performance athlete (e.g., continuous and systematic training, more than 16 h/week of training on average, taking part in national and international training camps and competitions) with that of being a student (e.g., attend lessons regularly, pass examinations, graduate successfully from school). In this regard, researchers have referred to the comparatively elevated stress levels of elite student-athletes (Brettschneider, 1999) and their limited opportunities for social contact and life outside school (Brettschneider & Klimek, 1998), with the threat of high individual social costs in general (Emrich, Fröhlich, Klein, & Pitsch, 2009). There is recent evidence, on the other hand, that elite student-athletes’ chronic mood and their psychological health are not statistically different from those of same-age nonathletes (Brand, Wolff, & Hoyer, 2013). It also has been shown that elite student-athletes who live at affiliated boarding schools at the ESS might develop better volitional skills than nonathletes (Elbe, Szymanski, & Beckmann, 2005).

From a sociological viewpoint, there is apprehension that the sport system tends to produce an instance of total commitment (German: Hyperinklusion; Cachay & Riedl, 2002; Göbel & Schmidt, 1998), making it difficult for elite student-athletes to reconcile the obligations of successful participation in the general education system (Borggrefe & Cachay, 2010). Attempting an athletic career at an ESS does not prevent student-athletes from getting into risky situations (Teubert, 2009). Athletic success might stay away in spite of all efforts, or an injury might terminate all anticipated rewards from such a career. In fact, most careers in high-performance sport will come to an end after some more or less successful years. General education from school (and/or other institutions in the educational system) thus remains an important resource for athletes’ later lives.

Germany’s ESSs represent educational organizations in a modern, open, civil society (Hummel & Brand, 2010). Most astonishingly, evidence on the middle- and long-term development of elite student-athletes’ school achievements is almost lacking (Prohl & Emrich, 2009). There are previous studies in which student-athletes’ school grades were monitored, illustrating that German ESSs provide settings in which dual careers are possible (Richartz & Brettschneider, 1996; Teubert, Borggrefe, Cachay, & Thiel, 2006). However, none of these studies have used school grades, or school grade development, as predictors of school achievement in general education.

The aim of the present study was to empirically explore ESS student-athletes’ school grade development and compare it with that of program dropouts. Program dropouts are defined as students who either have been deselected from their ESS’s high-performance sport program because they have missed athletic performance criteria, or who have quit pursuing an athletic career with the ESS’s program for other reasons (and have either left the school or remained there without further participating in the high-performance sport program). Additional cross-sectional analyses compare student-athletes’ average school grades after lower secondary school with those of students who were never enrolled at an ESS (school census results). Inferior school grades in student-athletes might be interpreted as indicators of undesirable total commitment.

Methods

Sample and data

Our main unit of analysis was 260 (159 male, 101 female) ESS student-athletes who joined an ESS in Brandenburg (the federal state has three ESSs) at class level 7 in 2008. This group of ESS starters comprises the whole age cohort of student-athletes in one of Germany’s 16 federal states. These student-athletes were asked to fill out a questionnaire during their first week at the ESS (and 91 % of them did). The same questionnaire was presented at the end of every following school year until 2012 (i.e., after class levels 7, 8, 9, and 10). This led to a repeated-measures design with five data collection waves.

Between class level 7 and 10, 57 (16 female) students dropped out and left their ESS before the end of lower secondary school (school dropouts). Another 45 (29 female) were still ESS students but had dropped out of their ESS’s high-performance athletic training program (deselected student-athletes). No information is available on why students left the ESS or why they were no longer part of the athletic program.

This means that 39.2 % (n = 102) of all the students who were enrolled in the year 2008 lost their status of being a student-athlete. All of them are referred to as program dropouts in our study. There were 60.8 % (n = 158) of student-athletes remaining.

Although there is an unbalanced data structure (missing cases at measurement points, due to school dropout, or absence because of training camps, competitions, or illness), our statistical approach of multilevel regression analyses allows for the inclusion of the complete set of 260 cases. Conveniently, 88.1 % of the students participated in three or more collection waves (48.1 % in all five collection waves), thereby giving us the opportunity to calculate individual trajectories of change (Singer & Willett, 2003). Detailed descriptive information on the cohort under investigation, as well as the study participants, is given in ◉ Table 1.

Table 1 Descriptive data of the study cohort in five data collection waves
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Sport disciplines taught at the three ESSs in Brandenburg (and thus represented in our sample) are artistic gymnastics, boxing, canoeing/kayaking, cycling, handball, judo, modern pentathlon, rowing, shooting, soccer, swimming, track and field athletics, triathlon, volleyball, weight-lifting, and wrestling. Due to small subsample sizes, no analyses on discipline-specific phenomena were performed. The school settings of the ESSs in Brandenburg are circumstantially described in Borchert (2013).

Measures and variables

Participants reported their average school grades in mathematics and German, using the standard German 6-point grading system (1 = very good/excellent, 2 = good, 3 = satisfactory/average, 4 = fair/pass, 5 = poor/deficient, 6 = fail). In the German school system, an overall average grade of 4 is needed to graduate to the next class level. School grades were treated as continuous variables in our analyses. The variables gender (0 = male, 1 = female) and dropout (0 = program dropout, 1 = student-athlete) were dichotomously coded.

The federal state’s school census results, including average class level-10 school grades in mathematics and German from all schools in Brandenburg, were extracted from the Central System for Online Administration of School Information (ZENSOS).

Statistical analyses

The SPSS® 21.0 software package was used for all statistical analyses. Missing values within multiple-item scales (i.e., within cases at measurement points) were substituted with a common expectation-maximization algorithm. The repeated measurements of school grades in mathematics and German (level 1) were nested within individuals (level 2). The longitudinal dataset was thus analyzed with two separate hierarchical multilevel analyses. The main advantages of such a multilevel formulation are the method’s robustness against unequal spacing and unbalanced datasets, and that estimations are made on the individual level (accounting for heterogeneous regression slopes) rather than on the sample level. This is different from the more restrictive assumptions of alternative statistical methods like repeated-measures analysis of variance (Field, 2009; Keller, 2003).

Unconditional means models allow to split level-1 and level-2 variances in the absence of predictors. This is a necessary check for systematic variation in outcome variables. The unconditional growth model is needed to check whether there is (unconditional) significant change over time. The participants’ age was used as the temporal variable, grand mean centered (0 = age − 12.92) for its initial status in the year 2008. This individualization of the temporal predictor results in a superior data fit when great variance (as is the case with the broad ranges of age in each wave; ◉ Table 1) would otherwise remain unexplained (Singer & Willett, 2003). The predictor variables age, gender, dropout, and the two resulting cross-level interaction terms (gender × age, dropout × age) were entered successively into the model.

  1. 1.

    Level 1: Yti = b0i + b1i (ageti − 12.92) + εti

  2. 2.

    Level 2: b0i = γ00 + γ01 genderi + γ02 student-athletei + u0i

  3. 3.

    Level 2: b1i = γ10 + γ11 genderi + γ12 student-athletei + u1i

  4. 4.

    Composite: Yti = γ00 + γ01 genderi + γ02 student-athletei + γ10 ageti + γ11 genderi × (ageti − 12.92) + γ12 student-athletei × (ageti − 12.92) + [εti + u0i + u1i ageti]

The term Yti is the individual i value (i = 1, 2, …, N) of mean school grades, and age ti is his or her age (in years) at time t (t = 1, 2, …, T). Thus, b0i represents an individual i’s true initial status, when age ti is 0; b1i represents an individual i’s true rate of change for each unit of increase in age; and εti is the unpredicted portion of individual i’s outcome at occasion t. The residual εti is assumed to be independently drawn from a normal distribution with mean 0 and variance \(\sigma _{\varepsilon }^{2}\). In the level-2 submodels, γ00 and γ10 are the level-2 intercepts. Initial status and rate of change represent an average individual male athlete (male = 0) in the group program dropout (program dropout = 0). γ01 and γ11 represent level-2 slopes for the effect of gender on the change trajectories by providing increments (or decrements) to both initial status and rates of change for female students (female = 1). γ02 and γ12 represent level-2 slopes for the effect of student-athlete on the change trajectories by providing increments (or decrements) to both initial status and rates of change for individuals of the two groups (student-athlete = 1). Both level-2 residuals, u0i and u1i, represent the deviations of initial status and rate of change of the individual change trajectories from the average population.

Cross-sectional comparisons (school grades at class level 10 of student-athletes and program dropouts vs. school census results) were analyzed using one-sample t tests for the school subjects mathematics and German separately.

Results

Descriptive statistics for all variables are summarized in ◉ Table 1. Checks for gender differences revealed no statistically significant influences in mathematics, neither for initial status (t(223) = 1.12, p = 0.26) nor for slope (t(199) = − 0.19, p = 0.85). For German, however, female students were enrolled in the ESS with a significantly better average school grade (t(238) = − 2.69, p = 0.01). The subsequent statistical growth in German was again unaffected by gender (t(204) = − 0.71, p = 0.48). The null (unconditional means) models yielded intraclass correlation coefficients of ρ = 0.54 for mathematics and ρ = 0.51 for German. This means that 54 and 51 % of the variability in the dependent variables is due to differences between persons, thus indicating the appropriateness of a level-2 analysis (ρ ≥ 0.05). The taxonomy of all multilevel models for school grades in mathematics and German is given in . Tables 2 and 3.

Table 2 Taxonomy of multilevel models for the dependent variable mathematics (school grades)
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Table 3 Taxonomy of multilevel models for the dependent variable in German (school grades)
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Checks for longitudinal change (unconditional growth models) revealed a significant yearly decrease in all students’ school grades from the beginning to the end of lower secondary school. Starting from grade 2.43 at the beginning of class level 7, all students’ performance in mathematics deteriorated by 0.08 units per year (t(199) = 5.09, p < 0.01). Grades in German developed very similarly. Starting from an average grade of 2.24, there was a deterioration of 0.09 units with each year of age for all students (t(205) = 6.67, p < 0.01).

Final model analyses revealed significant differences in the school grades of student-athletes and program dropouts. Regression diagrams, with highlighted initial status and time trajectories, are illustrated in . Figs. 1 and 2 (grades in mathematics and German).

Fig. 1
figure 1

Fitted ordinary least squares trajectories for school grades in mathematics. Dashed lines represent individual regression lines; continuous lines represent the groups’ average growth trends

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Fig. 2
figure 2

Fitted ordinary least squares trajectories for school grades in German. Dashed lines represent individual regression lines; continuous lines represent the groups’ average growth trends

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Student-athletes were enrolled in the ESS with an average grade in mathematics of 2.27. This was significantly better than the 2.58 reached by future program dropouts (t(235) = − 2.91, p < 0.01). Gender did not influence this effect. Student-athletes as well as program dropouts had a significant decrease in mathematics school grades by 0.12 units per year (t(233) = 3.70, p < 0.01). The initial difference between student-athletes and later program dropouts before school enrollment in class level 7 was preserved over time (as indicated by the insignificant interaction term student-athletes × age (t(217) = − 1.43, p < 0.15).Footnote 1

A similar pattern of results was apparent for grades in German. Male student-athletes had already enrolled in the ESS with a better school grade of 2.25 on average, compared with future male dropouts with an average grade of 2.50 (t(251) = − 2.39, p < 0.02). This group difference was even accentuated in female students (t(236) = − 2.90, p < 0.01). Female student-athletes started with an average grade in German of 1.95, compared with future female program dropouts’ average grade of 2.20. Male and female student-athletes’ as well as program dropouts’ school grades in German then decreased by 0.11 units per year (t(236) = 3.91, p < 0.01). The initial difference in school grades in German (between student-athletes and program dropouts) was preserved over time (both interaction terms, gender × age as well as student-athletes × age, remain statistically insignificant).Footnote 2

Both final models (for grades in mathematics and German) with the level-2 predictors gender and dropout reached a better data fit compared with the unconditional growth models [χ2(4) = 25.02, p < 0.01 (mathematics), and χ2(4) = 27.34, p < 0.01 (German)]. The amount of remaining unexplained variance indicated that additional predictors (at level 1 as well as at level 2) should be added in further studies.

Cross-sectional analyses showed that class level-10 elite student-athletes’ school grades in German [mean (M) = 2.5, standard deviation (SD) = 0.8] and mathematics (M = 2.5, SD = 1.0) did not differ from the federal state’s average (German: μ = 3.4, σ = 1.0; t(157) = − 0.90, p = 0.37; mathematics: μ = 3.3, σ = 1.2; t(157) = − 0.66, p = 0.51). The same was true for the program dropouts’ grades in German (M = 2.9, SD = 0.7; t(42) = − 0.33, p = 0.74) and mathematics (M = 2.9, SD = 0.8; t(42) = − 0.50, p = 0.62).

Discussion

This study’s aim was to empirically explore ESS student-athletes’ school grade development and compare it with that of ESS program dropouts. The 260 young elite athletes, who chose (with their parents’ consent, of course) to enroll in an ESS at class level 7 by the age of 13 years, started their school careers with “good” grades (in terms of the German grading system) from primary school. Subsequent dropout from the school’s athletic high-performance training program can be statistically predicted by weaker school grades from primary school. Program dropouts, defined as students who during lower secondary school were either deselected from athletic high-performance training by their coaches or refrained from high-performance training for other unknown reasons, entered the ESS with weaker grades in mathematics (− 0.31 grade units) and German (− 0.25 grade units). Similar yearly decreases in school performance (− 0.12 grade units per year in mathematics and – 0.11 in German) can be observed from school level 7 to 10 for all students (student-athletes and program dropouts). Such decreases can be observed throughout the German school system and across different types of schools (Baumert, Trautwein, & Artelt, 2003; Valtin, Badel, Löffler, Meyer-Schepers, & Voss, 2003). This leads to the situation that at the end of lower secondary school, student-athletes’ school performance accords with “good” grades, whereas program dropouts broadly arrive in the area of “satisfactory/average” school grades. It is, however, important to emphasize that both groups’ school grades did not significantly differ from the federal state’s school census norms; i.e., ESS students’ performance was not different from that of students from other schools without high-performance sport programs.

The superordinate research question of our study was whether there are reflections of total commitment by the system of high-performance sport (Borggrefe & Cachay, 2010) in ESS student-athletes’ school performance. The answer to this question is bipolar.

On the one hand, it became obvious that successful (in a sense that they are able to meet their ESS’s athletic criteria) student-athletes’ school grades are neither worse nor better than that of program dropouts and nonathletes. This may counter the hypothesis of total commitment (at least partially, with regard to school grades, as one eminent facet of school performance and school success). For the group of successful student-athletes, the criticism of Emrich et al. (2009), that individual costs for student-athletes at German EESs may be (too) high, can be put into perspective. This finding might also relativize one major argument of good judgment critique on school-based high-performance sport promotion (in the shape of German ESSs) that such programs reduce elite young athletes’ educational opportunities once their sporting careers have come to an end. Given that school grades in mathematics are a reasonable predictor of later job-related success (Baumert, Bos, & Lehmann, 2000), opting for an ESS is at least not automatically associated with early educational disadvantages. Results also correspond with anecdotal evidence gathered from such special schools’ principals in Australia, Canada, Sweden, and The Netherlands (Radke & Coulter, 2007). They have reported that in their experience, elite sport-students’ school grades are not seldom above average, as especially targeted support measures (e.g., private lessons for absent student-athletes) are routinely offered to them. Such offers have also been established in Brandenburg.

On the other hand, 18.5 % of the students who enrolled in the ESS at class level 7 left the ESS already within the following 4 years, ahead of time, before having finished lower secondary school (at the ESS). Information about this group’s motivation or about these students’ further careers (in general education and in sport) is unfortunately not available. Another 20.8 % chose to stay at their ESS, but dropped out of high-performance sports. Again, we have no information about their motivation to do so. It is important to acknowledge that the total commitment hypothesis (Borggrefe & Cachay, 2010) might be a valid explanation for all these dropouts. These students may have been unable to reconcile the obligations of successful participation in the general education system and high-performance athletic training at the same time. Brand et al. (2013) found evidence for deselected ESS student-athletes’ elevated risk of suffering from psychological symptoms. Some of our results can thus be interpreted in light of the findings by Riedl and Cachay (2002) from older adolescent athletes. They illustrated that only a minority of young athletes (older adolescents in their study) would opt for a potential career in elite sports when their general education was seriously compromised.

It is interesting that almost no differences in school grades between female and male student-athletes were found, which is in contrast to current knowledge from general education research (Deutsches Institut für Internationale Pädagogische Forschung, 2012). One explanation is that the better school grades of successful student-athletes might be rooted in earlier preselection processes. Most students who are enrolled in class level 7 at an ESS are already experienced and have been successful at lower competitive levels in previous years. It is thus a very interesting open question whether student-athletes’ advantage in school grades at the time of their school enrollment is also accompanied by a preexisting advantage in athletic skills (which are of course independent of gender).

Our empirical data also strengthen the idea that emerging as an above-average adolescent student-athlete might presuppose above-average cognitive abilities, making it easier for these students to cope with general educational demands at school (Richartz & Brettschneider, 1996). Elite young athletes might be particularly aware of the necessity to perform well in school (regular education), e.g., if they want to receive exemption for competitions and training camps. To advance their careers in the athletic domain, student-athletes may strive for success with greater motivation and work harder for their goals in various areas.

A question directly resulting from our data is whether future success in high-performance sport, or at least an elite student-athlete’s success in getting along with the dual pressure of high-performance sport and general education at an ESS, can be statistically predicted. We have shown that school grades from primary school is such a predictor. It is thus important to include the early school performance of young talents as an informative variable into the ESS nomination process before school enrollment. It is, however, important to note that it is only one of several other possible predictors, which have not been analyzed so far, for example self-discipline, self-efficacy, or conscientiousness as a personality trait. In light of the presented data, future studies should focus even more on predictors of later success in sport.

Limitations

One limitation of our study is that we focused on elite student-athletes from the federal state of Brandenburg only. This state modified structural aspects of their ESS program in 2008 (Borchert, 2013). Compared with other school-based high-performance sport promotion programs, Brandenburg has tried to better integrate the two rather disparate systems of educa­-tion and high-performance sports. For example, high-performance training became part of the ESS school curriculum, with the result that, for instance, more time resources for homework were created. Borggrefe and Cachay (2010) have identified the Brandenburg program as an example of successful structural coupling. Better learning conditions for student-athletes may influence their school performance (better school grades). Thus, it should be further analyzed whether student-athletes from Brandenburg are representative of other ESSs.

Last but not the least, we are completely aware that education is a faceted construct, and that cutting down to “simple” school grades is a sort of oversimplification  (Krüger & Neuber, 2012). It is also a fact that school grades are always coupled with social reference standards (Ingenkamp, 1977), and that we cannot be sure that all elite sport-students attained their good grades by having to  reach the same school standards compared with other students from their age groups, at regular schools without ESS programs. On the other hand, we do not see any reason to doubt the fairness and professionalism of Brandenburg’s ESS teachers in this issue. We, therefore, prefer to conclude from our empirical analyses that it is important to challenge the German ESS system and to continually criticize deficiencies from an academic viewpoint (Emrich et al., 2009). With regard to a potentially discarded general education in Germany’s ESSs for the sake of the “blind” promotion of athletic excellence, we tend to say “no,” this might not automatically be the case.