Running mechanical alterations during repeated treadmill sprints in hot versus hypoxic environments. A pilot study

We determined if performance and mechanical running alterations during repeated treadmill sprinting differ between severely hot and hypoxic environments. Six male recreational sportsmen (team- and racket-sport background) performed five 5-s sprints with 25-s recovery on an instrumented treadmill, allowing the continuous (step-by-step) measurement of running kinetics/kinematics and spring-mass characteristics. These were randomly conducted in control (CON; 25°C/45% RH, inspired fraction of oxygen = 20.9%), hot (HOT; 38°C/21% RH, inspired fraction of oxygen = 20.9%; end-exercise core temperature: ~38.6°C) and normobaric hypoxic (HYP, 25°C/45% RH, inspired fraction of oxygen = 13.3%/simulated altitude of ~3600 m; end-exercise pulse oxygen saturation: ~84%) environments. Running distance was lower (P < 0.05) in HOT compared to CON and HYP for the first sprint but larger (P < 0.05) sprint decrement score occurred in HYP versus HOT and CON. Compared to CON, the cumulated distance covered over the five sprints was lower (P < 0.01) in HYP but not in HOT. Irrespective of the environmental condition, significant changes occurred from the first to the fifth sprint repetitions (all three conditions compounded) in selected running kinetics (mean horizontal forces, P < 0.01) or kinematics (contact and swing times, both P < 0.001; step frequency, P < 0.001) and spring-mass characteristics (vertical stiffness, P < 0.001; leg stiffness, P < 0.01). No significant interaction between sprint number and condition was found for any mechanical data. Preliminary evidence indicates that repeated-sprint ability is more impaired in hypoxia than in a hot environment, when compared to a control condition. However, as sprints are repeated, mechanical alterations appear not to be exacerbated in severe (heat, hypoxia) environmental conditions.     

An explicit multicomponent alphabet writing instruction program in grade 1 to improve writing skills

European Journal of Psychology of Education - Learning to write involves the acquisition of several skills, not the least of which is handwriting. Indeed, studies in cognitive psychology have...     

Machine Learning Literacy for Measurement Professionals: A Practical Tutorial

The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, Machine Learning (ML) emerges as an increasingly important skill in the toolbox of measurement professionals in this new era. However, most ML tutorials are technical and conceptual-focused. Therefore, this tutorial aims to provide a practical introduction to ML in the context of educational measurement. We also supplement our tutorial with several examples of supervised and unsupervised ML techniques applied to marking a short-answer question. Python codes are available on GitHub. In the end, common misconceptions about ML are discussed.