Adapting to Major Disruptions to the Learning Environment: Strategies and Lessons Learnt During a Global Pandemic.

Dealing with rapid, unanticipated disruptions to established learning environments are challenging. There are a number of situations that may require this including natural disasters such as weather disturbance, viral pandemics, or political unrest and violence. For example, the COVID-19 pandemic provided medical educators with this challenge and enabled valuable lessons to be learnt. These can be utilized to prepare for other occurrences in which disruptions must be faced and high-quality education delivered. Focus should be placed both on successful transition of learning events to a new modality appropriate to the emerging climate and on reliably assessing efficacy of these new educational strategies with identification of those best suited to the new environment. We present a framework, based on local lessons learnt, by which the challenges faced during an educational disruption can be addressed, and describe methods to determine which changes are most effective and should be durable.

Measurements of roll, steering, and the far-field wake in track cycling.

A series of measurements taken with two instrumented track bicycles in a velodrome are presented. The bicycle wheel speed, cadence, roll angle, steering angle, power, and airspeed are recorded. The experimentally-measured values are compared to existing theoretical models of roll and steering angles. The accuracy of the roll angle calculations is dependent on the fidelity of the modelled cyclist path and decreases for higher riding speeds. Experimental measurements of the steering angle show a reasonable agreement to theoretical calculations, albeit with reduced steering angles on the bends at higher speeds. There is also seen an increasing steering angle oscillation within each pedal cycle with increasing bicycle velocity which may influence a cyclist's rolling resistance and the aerodynamic flow around the bicycle's front end. Observations are made of changes in the flow field ahead of the bicycle due to the presence of other riders on the track, showing an effective tailwind of up to 0.7 m/s. The measured power shows a decrease at the bend entry due to the changing roll angle. Data presented in this paper provides new insights and can help to provide a validation of values used in existing track cycling analytic models.