iQualify is chock-full of data.
- You can feed data in from your own systems.
- You can see the data we’ve got in-app about learners and classes.
- And, you can feed data out into other systems enabling you to create your own collection of user data for analysis.
Let’s take a look at an example of the sort of data we’re talking about here. Let’s say a learner has just completed a course and earned a badge.
That “event” (and data) can inform other decisions down the track, outside of iQualify.
For example, maybe this event means that a new course is suggested to the learner as a next step. Or, this event could be added as a data point in a graph to assess whether there's a long term trend in better professional or workplace outcomes associated with this learning. For example, you could use this data to research the question: "Does achievement of these badges lead to customer queries being solved in a shorter amount of time?"
We enable the collection of a whole heap of data. And we know that you want to be able to put that data to good use. You are the owners of your data. For our part, it’s important to make sure we are making good, principled decisions about how we do that. In the rest of this post, we’ll be talking through the principles we follow in relation to data.
The iQualify approach to data
We have a wide variety of event types that can be collected from a range of interactions. Collecting this data at scale could be of interest to data scientists and developers so that they can build their own large datasets for analysis. But, we still need to make sure non-power users get the information they need in a format they can use.
Our goal is to enable you to share or consume data that can result in informed decision making without forgetting about the people at all points of the process. Especially learners. Here are the key data principles we follow.
- Be transparent
- Get the right data into the right hands
- Guide good choices
Now onto more detail of what each of these principles means and what they can look like in practice.
Transparency comes in a few forms when it comes to data.
Firstly, be completely transparent with people about what you're collecting and why it's useful to you (and, in turn, them). And make sure they can ask you about this.
Secondly, be transparent describing the data you can and cannot share with users on the receiving end of the data. Make sure the structure and intent of the data is well understood.
How iQualify informs your learners
The first thing we do is describe to every learner precisely what data is being collected. They can see this for themselves under their profile.
Coupled with this, we make sure learners have the means to get in contact with us to ask the question, can you show me what you have collected? The answer, of course, is yes.
Get the right data into the right hands
The next principle is to make sure that the way you allow people to access or connect to data helps get it into the right hands. This can range from what someone can access, through to how you give them access.
If you think about the experience of the person viewing the data in context of their other goals, you're more likely to get good outcomes.
Empowering your people and systems in iQualify
We have varying levels of access depending on your role. For example, our facilitators can see a lot of learning analytics on the Class Console but they won’t have access to every piece of data. The right data for a facilitator is the data that can help them make effective teaching decisions about who needs their support and what changes they might need to make to their delivery.
Show too little and important pieces of information are missing, possibly affecting teaching decisions. Show too much and it becomes like white noise.
However, technical responsibilities in an organisation might include:
- using data to automate a learner's experience across the organisation
- adding to an analytics database for more reporting
- lodging specific events into an appropriate system of record.
In the context of these goals, these users need access to real time event data and our API to connect iQualify up to any other system that can use that data. And, because of its global nature, access to these areas is carefully managed.
Guide good choices
With a bare room, the furniture you add and the way you arrange it can really alter how the room is used. The same can be said for data. The format and type of data can very much inform its use. As a short example, serving up the longest without progress tile on our Class Console might encourage facilitators to chase up learners who haven't been regularly engaging with their course.
This is why you should always try to guide good choices in viewing, handling and using data. We often think of this as providing good defaults. When you provide good defaults, you help limit mistakes and/or misinterpretation of data.
Matching data to goals in iQualify
As with the previous principle, thinking about a user’s goals really helps. If your goal is a very transactional one, for example if you are trying to get the learners to complete a course then giving you complex reporting tools isn't going to help. Also giving you direct access to data in a spreadsheet format can be very harmful when you accidentally share that sheet with the world. So a good default in this case, is to embed visualisation based on the data in the app, right where you need it.
When meeting your goals needs real time event data, we offer an anonymised version of those events. Events can be captured from iQualify without user data if they are used solely for analysis of trends. We also provide comprehensive tutorials that describe how a range of data insights can be created. These worked examples are another way of providing good defaults.
By following a common set of principles, we are preparing for the best use of data and we can look after a range of different outcomes. We can make sure that we and others are clear about data collection, that we are presenting the right information to the right people, and in the right way for them. We also make sure the contributors (in this case, often learners) are informed and respected and that those supporting them (from facilitators to administrators to leadership) can make informed decisions.