Inclusive education in the Netherlands: how funding arrangements and demographic trends relate to dropout and participation rates

There is a global trend towards including children with special needs in mainstream schools instead of placing them in special schools. However, the numbers of students in special schools varies greatly among regions due to variations in educational systems, funding arrangements – and the incentives that are associated with these arrangements – and demographic trends. In the Netherlands, a new policy aimed at inclusive education was introduced in 2014, together with financial measures to equalise funding for students with special needs across the country. The present study explored the effects of this equalisation policy, as well as the demographic trend of population decline, on dropout rates and participation rates in special education (namely, special schools for mainstream education and schools for special education). The data were retrieved from nation-wide registration systems. The results showed that population decline did not affect participation rates in special education, whereas decreases in funding did result in greater declines in participation rates in special education. Moreover, decreases in funding also resulted in higher dropout rates in areas with growing student populations. Although the reform of funding arrangements resulted in lower participation in special education, higher dropout rates might be a cost of this shift towards inclusive education.     

Evaluating strategic periodisation in team sport

The planned peaking for matches or events of perceived greatest priority or difficulty throughout a competitive season is commonplace in high-level team sports. Despite this prevalence in the field, little research exists on the practice. This study aimed to provide a framework for strategic periodisation which team sport organisations can use to evaluate the efficacy of such plans. Data relating to factors potentially influencing the difficulty of matches were obtained for games played in the 2014 Australian Football League season. These included the match location, opposition rank, between-match break and team “form”. Binary logistic regression models were developed to determine the level of association between these factors and match outcome (win/loss). Models were constructed using “fixed” factors available to clubs prior to commencement of the season, and then also “dynamic” factors obtained at monthly intervals throughout the in-season period. The influence of playing away from home on match difficulty became stronger as the season progressed, whilst the opposition rank from the preceding season was the strongest indicator of difficulty across all models. The approaches demonstrated in this paper can be used practically to evaluate both the long- and short-term efficacy of strategic periodisation plans in team sports as well as inform and influence coach programming.