Every organization that uses digital technologies to deliver valuable experiences has to its avail a wealth of data ready to use. For many reasons, few do. There are many reasons why, and depending on those we can assess the so-called “Digital Maturity” for a given organization. Their level of “fear” involving security of privacy, which without a doubt should be taken seriously, can be seen as the level of understanding of the data, as well as the policies that would allow for an appropriate use of them.
Education and learning apps are no exception. Relatively simple methods to keep track user behavior throughout their use of a system could result in eye-opening insight that could speed up desired results. Most systems today generate tons of data on user attributes, behavior, and –on the case of education– performance that could feed design choices, and up the stream towards entire design strategies.
Most of the new trends that populate the EdTech world, from microlearning and gamification, to the great beyond of “personalized learning,” have one thing in common. They are based on data from a given student sample. You might see the problem with that: They attempt to turn general principles with insufficient evidence into holy grails.
The solution, of course, is not to throw them altogether, but to consider them as starting points for more local explorations. Don’t focus on data from an anecdotal or idealized learner. Work with those in front of you.
Learning Analytics with Google 101
Given its omnipresence, there isn’t a more obvious way to start building a repository of data than through Google Analytics (GA). The complete suite is a robust, if at times clunky interface capable of key user insight. People including instructional designers, who provide GA solutions to education professionals or in learning contexts, often find surprised reactions, generally followed by excitement at the possibilities.
After an explosion in the practice of Analytics, Google released Tag Manager (GTM). This application simplifies the process of setting up the tracking of data capture and following up behavioral goals.
If you are not familiar with GA and Learning Analytics, let’s take a look at some basic issues before considering implementing a Learning Analytics strategy in your LMS.
What are Learning Analytics?
In a way, “Analytics” is just another term for meaningful statistics about users using digital platforms. In a more practical sense, Analytics aim to answer questions involving user attributes and behavior within the scope of a website or application. Answer which could be answer or hinted at from quantitative measurements and indicators.
Learning Analytics are an application of said systems and methods to the context of users in digital and online learning experiences. Learning Analytics add new concerns about the “consumption” of content from an educational standpoint, and how data both reflects and informs the process. Ultimately, Analytics in general as well as in the context of learning must lead to the optimization of the system (website, application).
Given that the practice of Analytics originated in commercial and marketing contexts, there is a consistent tension between what is desirable to track, measure and optimize for in a system. There are countless examples in which desirable outcomes for the learner can conflict with the organization’s goals. The systems responsible for the generation of Learning Analytics are, of course, not at fault.
For years, a staunch advocate of Learning Analytics done right, that is, that actually validate a learning process, is Moodle HQ’s Research Analyst Elizabeth Dalton.
Are Learning Analytics and Google Analytics the same?
GA is the name of platform Google offers, the free version of which is by far the most popular analytics solution used today.
Learning Analytics refers to the practice of analytics applied to the learning process. As Dalton warns, using data from platforms like GA to draw conclusions for learners deserves some caution.
Properly built indicators (built in GA or elsewhere), tied around learning goals could be an interesting, and potentially groundbreaking approach to uncover insight about learners. For instance, redefining the idea of “conversion” and designing a “user funnel” around Competencies and CBE Learning Plans can be an enticing proposition for learning organizations.
What is Google Tag Manager?
As mentioned earlier, GTM provides a unified dashboard for Analytics and user tracking, based around three key concepts:
- Tags, or “data capsules” that link a given action from a user to a location on the system
- Triggers, or rules through that set off a data capture action by one or more tags
- Variables, or the actual data included in the tag’s capture
For every tag, there’s a trigger. When the data is triggered, it’s “shot,” by which I mean it captures the state or value of chosen variable at a given point in time.
Do I still need Google Analytics if I have Google Tag Manager?
Short answer: Yes.
The reality is that GTM will greatly increase your GA experience by giving more refined data points, and if you set up a simple and clear language for your tags, aligned with your strategic goals.
Without GA (or an Analytics tool), GTM will not give you much value.
GTM is not actually an Analytics dashboard. It might be better thought of as a traffic light for Analytics tracking. With GTM, it is much easier to add different Analytics pipelines to a website. This include the infamous “Facebook Pixel,” Google AdWords Conversion Tracking, and basically every one of the trackers social media sites offer today. They usually ask you to modify parts of the code on your site, which even if you have access to and know you way around HTML and JavaScript, it can still be prone to errors. Conversely, after just one HTML site edit, GTM lets you manage every tracker from the same place and make as many edits as you want afterwards, without touching the code of your LMS ever again.
Are there other GA-related technologies I should know about?
GA, GTM and Google AdWords if you are interested to advertise, are the core technologies offered by Google. If you are interested on managing how your website appears on Google, add Search Console to the list. Including all the available tools, the full free Google Analytic bundle consists of:
- Analytics (GA)
- Tag Manager (GTM)
- Search Console
- AdWords
- Optimize
- Data Studio
Optimize and Data Studio provide testing and data visualization functionality, respectively. They expand on features that you can already find with GA and GTM, or even through your own site.
Getting started: A Learning Analytics Strategic Planning primer
Hopefully this will give you a good idea of how these technologies can be set up.
Now, it’s time to forget all about it!
As we continue our exploration into digital strategies for educational content, it will become clear that these technologies are tools or languages through which you can build your plan and workflow.
But, and I cannot stress this enough: They will not build a learning content strategy for you.
It is a painful reality that, to this day, we do not have appropriate instructional design and development tools. That also goes for general purpose technologies involving “envisioning,” “design thinking” and the like. In the case of learning the situation is even more acute, given the limited level of standardization in pedagogy and quantitative approaches, and the issue of “Digital Maturity” mentioned earlier.
Broadly speaking, a planning exercise must begin with a studious analysis of the Problem or “Learning Challenge,” accompanied by direct or indirect (proxy) quantitative indicators. A set of measurements for these indicators before the start of the project will provide a baseline that will allow for impact evaluation of the strategic programs.
The indicators usually belong to two groups: Context-specific and managerial. The latter are more or less universal analytics for the efficacy or reasonable use of the resources allotted to the project. The holy grail of which is the ROI on Learning.
In practice, the launchpad of a digital content implementation strategy is a mix of the following items, each of which includes a series of attributes. Plans are streams that combine at least one of each item. For statistical common sense, each stream must carry out an intervention for a group, making it a “test” which must be accompanied with a “control stream”:
- Message
- Target Audience
- Channels
- Schedules
- Theory of Response
We will continue to expand on practical, measurable content strategies if we detect interest among our readers, of if we receive interest from organizations to carry out in-depth capacity building content and experiences.
We invite you to share and discuss this content online, within your team, with colleagues and peers.
In the meantime, some resources
- Learning Analytics Pulse (And don’t miss our Learning Analytics Competency Roadmap series)
- How LMSPulse uses Analytics: See our audience insights at work at #ThePulse
- Interested in adding a quantitative layer in your learning project management? Willing to document your process and share it with the world? Reach out to us
- For more on Learning Analytics with Google, check out the free online courses from the Google Analytics Academy
- Rate your organization under Google and BCG’s Digital Maturity Benchmark
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