start distance
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Author(s):  
Lina Kaminskienė ◽  
Yi Chu Ling

The COVID19 pandemic has caused massive disruption in education practices worldwide and Lithuania was no exception. This article investigates how this period of uncertainties has been perceived by Lithuanian schools during school lockdown. The study aimed to explore the challenges that Lithuanian schools faced and how distance education practices has been reconsidered during school lockdown. The research was based on a survey of 406 sampled school leaders of public education institutions in Lithuania conducted two months into the first nationwide lockdown in spring 2020. This paper aims to discuss the challenges of distance education from the perspective of school leaders, and to link the findings of the study to recent studies related to schools’ responses to the pandemic situation. The survey responses indicated that schools initially focused on the organisation of staff training and technological preparation to start distance education during the first two weeks of lockdown. Their focus two months into the process shifted towards tackling challenges on students' responsiveness and assessment of students' achievements during distance education. Challenges are perceived as opportunities for reflection and growth, re-examine current institution strengths and weaknesses, and reconsolidate with the school communities in prioritising what the utter function in education is.  


2015 ◽  
Vol 10 (8) ◽  
pp. 1055-1057 ◽  
Author(s):  
Thomas Haugen ◽  
Espen Tønnessen ◽  
Stephen Seiler

Purpose:A review of published studies monitoring sprint performance reveals considerable variation in start distance behind the initial timing gate. The aim of the current study was to generate correction factors across varying flying-start distances used in sprint testing with photocells.Methods:Forty-four well-trained junior soccer players (age 18.2 ± 1.0 y, height 175 ± 8 cm, body mass 68.4 ± 8.9 kg) performed sprint testing on an indoor sprint track. They were allocated to 3 groups based on sprintperformance level. Times for 10- and 200-m sprint with foot placement ranging from 0.5 to 15 m back from the initial timing gate were recorded twice for each athlete.Results:Correction-factor equation coefficients were generated for each of the 3 analyzed groups derived from the phase-decay equation y = (y0 − PL) × exp(−k × x) + PL, where y = time difference (0.5-m flying start as reference), x = flying-start distance, y0 is the y value when time is zero, PL (plateau) is the y value at infinite times, and k is the rate constant, expressed in reciprocal of the x-axis time units; if x is in seconds, then k is expressed in inverse seconds. R2 was ≥.998 across all athlete groups and sprint distances, demonstrating excellent goodness of fit. Within-group time differences were significant (P < .05) across all flying-start distance checkpoints for all groups. Between-groups time-saving differences up to 0.04 s were observed between the fastest and the slowest groups (P < .05).Conclusions:Small changes in flying-start distances can cause time differences larger than the typical gains made from specific training, or even the difference between the fastest and slowest elite team-sport athletes. The presented correction factors should facilitate more meaningful comparisons of published sprint-performance results.


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