Instructional Design and Engaged Learning

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Instructional Design and Engaged Learning

Module Eight - Building Lessons with Numbers

Many aspects of medical decision-making rely upon the capacity of the personnel to interpret data - to make reasonable judgments and inferences. The Net offers a rich and fertile collection of databases with which to develop and practice these analytical skills. In the example below, the task requires a comparison of cities using weather data. Your challenge is to build a similar learning experience based on medical data. Note that the example below uses choice as the organizing basis for driving the thinking challenge.

Which City?

There are many aspects of weather that might influence the choice of a town or city as a new home. Pick 4-5 of the following, enter them on the top row in a table using MS Word and then compare the following towns and cities based on the criteria you selected.

Rainfall mm mean annual
Wet days >1.0mm
Sunshine hours mean annual
Temp Mean Max Jan
Temp Mean Max Jul
Temp Mean Min Jan
Temp Mean Min Jul
Temp Extreme Max
Temp Extreme Min
Screen Frost days
Ground Frost days
Wind mean speed km/h
Gust Days >93 km/h

Auckland, Albert Park
Rotorua Aero
Hamilton, Ruakura
Gisborne Aero
Wellington, Kelburn
Nelson Aero
Christchurch Gardens
Dunedin, Musselburgh
Invercargill Aero

Which town or city comes out best when you consult the actual data? Click here for MetService.

Create a data based slam dunk digital basis requiring analysis, interpretation and/or synthesis and evaluation using medical data. Take advantage of PubMed - a service of the U.S. National Library of Medicine and the National Institutes of Health - or some other medical database you know and trust.

Next module. Please do not proceed until asked to do so by the workshop leader.