H E A L T H I N S I G H T S researchers to measure over 4,000 pilots on 140 dimensions of size ( height , arm circumference , the distance between eyes , etc ). However , by using dimension averages to build the cockpit model , not a single pilot fit the new measurements once it was complete .
Chibeza Agley , Co-founder and CEO at OBRIZUM
If we relate this example to the healthcare industry , placing a senior doctor with 30 years of experience in the field and a recently qualified junior doctor on the same training programme at the same starting point is nonsensical . It fails to account for the abundance of hands-on experience and industry know-how that the more senior individual will have acquired in their career to date .
Most linear programmes today are measured based on completion data : have they completed the course , or have they not ? Naturally , this delivers a very limited overview of the programme ’ s effectiveness .
By providing learners with access to the same resources at the same time , the perception is that the linear learning approach will result in all participants developing the same knowledge at the same point in time .
But experience has shown us that this simply isn ’ t practical .
The impact on healthcare organisations
As we ’ ve established , the fundamental concept of linear learning is flawed as it doesn ’ t account for unique learning patterns and pre-existing knowledge baselines .
So , if the course is too challenging , it can overwhelm the less experienced learners . But backtracking through the basics for beginners can often lead to advanced learners becoming disengaged .
There is no such thing as an ‘ average ’ learner . Yet all too often these programmes are constructed against averages .
There is practical evidence that averages do not work . For example , the US Air Force commenced a project to redesign a plane ’ s cockpit in the 1950s where they employed
You wouldn ’ t prescribe the same treatment to patients with different ailments , so learning must be considered in the same way .
Adaptive learning : the ‘ magic pill ’
While it is true that different needs require different treatments , adaptive learning is as close as there is to a ‘ magic pill ’ in learning and development processes .
Much like the wider developments we ’ ve seen in the healthcare industry in recent years , there have been moves to upgrade the traditional approach to learning . One of which is the recommendation functionality , which typically involves a series of manually tagged programmes and courses that are suggested to a learner based on their roles , skills , peers and preferences .
Alternatively , organisers are required to run a manual pre-assessment on all participants before the individuals begin the course . Based on how well they scored on completion , each learner is then moved into the next course , creating a ‘ decision tree ’ style of learning where each course requires predefined labelling . As a more tailored approach than the one-size-fits-all method , this creates additional decision-making requirements for the programme leaders to decide which participants follow each path , at each stage .
The effective delivery of digital learning programmes should be considered much like a Sat Nav . By constantly assessing its current location in correlation with the desired
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