DevLearn session summary 4. Stories from the last half of week Two

So this is it, DevLearn is over for another year. Thanks to everyone at the eLearning Guild for putting it on – It’s been a great event. There have been a lot of really informative sessions, but too little time to see everything. So, what we did for PTT is choose the ones that we think are most useful for learning design and learning transfer. With that in mind, here are the final few sessions that we liked from the last two days of the conference.

1. Planning your learning data strategy with Steve Foreman

What Steve doesn’t know about data analysis for learning programs can be written on the back of a postage stamp. We’ll try and condense it here to the main points. The first part of the session looked at the kind of decisions various people need to make using data:

  1. Users: Find what I need now; Make best use of my time; Minimise work disruption; Don’t miss important things
  2. L&D funders: Determine if L&D is appropriately funded; Make sure L&D is focused on business needs; Know if learning has a positive impact
  3. L&D professionals: Determine if solutions are being used by the right people; Evaluate solution’s effectiveness; Measure learning’s impact
  4. Others: (Compliance, HR, IT, Legal, Sales): Various needs that can’t be ignored. Stay in touch with these stakeholders

What is learning data? ‘Data generated by people’s use of learning solutions and technology-enabled learning ecosystems’

There are 3 types of learning data: 

What is a Learning data strategy and what are the step needed to make it meaningful? ‘A set of goals and action plans for using learning data to inform meaningful answers to strategic questions posed by users, L&D funders, and other key stakeholders’

For each step, take a look at the slide gallery below for more details about the steps and what you should do. The first slide looks at data goals. The next three slides list questions that should be answered to make sure you can meet your data goals. Once you have gone through those two steps you should: identify the correct data, evaluate its quality (60% of all data work is cleaning data for analysis), plan a data collection, and finally create meaningful dashboards.

2. Minimise friction in your learning ecosystem with Jeremy Roberts

The Fogg behaviour model relies on an intersection of three elements to increase the chance that behaviour will occur. In other words, people are more likely to change their behaviour if they are motivated, have been prompted, and have the ability to do so. That intersection is shown in the chart below.

In the absence of prompts, or anything that increases motivation or ability there will be friction. Friction slows down changes of behaviour. So, to increase the chances that learning gets used, you should ask yourself these three questions:

You can use the slide gallery below to work through questions that tell you it Prompts, Motivation, and Ability are being optimised. You can also assess how well you’re doing in each area to see where you can improve your designs and make sure your Fogg model has the correct intersection.

A quick summary would be:

  • Prompts: People will react to environmental prompts such as push (emails) or if/then (conditions) which can be used in the workplace to get a prompt to someone digitally. Hint: make it super appealing.
  • Motivation: People react to motivators and de-motivators such as pleasure/pain, hope/fear, acceptance/rejection. All of these things are influenced by specific audience needs. Hint: know what those needs are and play to them. 
  • Ability: Get to the point quickly by reducing number of clicks, increasing bandwidth, and improving hardware to keep people engaged. Hint: make learning super easy to grab and use.

That’s all from DevLearn for 2020. Thank you Steve and Jeremy for great session. We hope you found these summaries useful. Look out for future articles, posts and other expertise to help you with your learning design efforts.

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