Nowadays, quantitative methodologies have been traditionally adopted to evaluate learning processes in a broad sense, including class interventions and large-scale surveys. However, only recently there has been an increased use of rigorous psychometric assessment of new instruments, randomized clinical trials, longitudinal designs and multivariate analyses in STEM (Science – Technology – Engineering – Mathematics) education field. This thematic issue seeks applied and methodological papers addressing challenging problems using new and established statistical methods to the field of STEM education.Read more about Call for Papers Thematic issue on "Measurement in STEM Education"
About the Journal
Research topics cover human, social and environmental sciences. They include the planning and evaluation of systems, services and policies, the study of local, regional, national and international organizations, and, in particular, the protection of health, education and training, social services, employment and professions, cultures, minorities, social habits and deviant behavior, inequalities and poverty, leisure and sport, pollution and protection of the natural environment, communications and the information society.
Statistica Applicata - Italian Journal of Applied Statistics (ISSN:1125-1964, E-ISSN:2038-5587) applies the Creative Commons Attribution (CC BY) license to everything we publish. Developed to facilitate Open Access, this license lets authors maximize the impact or their research by making it available for anyone, anywhere in the world to find, read and reuse. Under this license, authors agree to make articles legally available for reuse, without permission or fees, for virtually any purpose. Anyone may copy, distribute or reuse these articles, as long as the author and original source are properly cited.
1. The relationship between players’ average marginal contributions and salaries: an application to NBA Basketball using the generalized Shapley value (Biancalani, F., Gnecco, G., Metulini, R.)
2. Evaluation of off-the-ball actions in soccer (Wu, L., Swartz, T.)
3. A survival analysis to discover which skills determine a higher scoring in basketball (Macis, A., Manisera, M., Sandri, M., Zuccolotto, P.)
4. Football analytics based on player tracking data using interpolation techniques for the prediction of missing coordinates (Karlis, D., Kontos, C.)
5. Gender comparison of in-match psychological traits of tennis players: dynamic network analysis (Milekhina, A., Breznik, K., Restaino, M.)