Analytics Deep Dive: Assignment Engagement Analytics Panel

Today’s post is the third installment of our OttoLearn analytics deep dive. Last week, we explored the Learner Engagement analytics panel, which summarizes your learners’ overall performance and engagement. 

This week, we’ll look closely at the Assignment Engagement analytics panel

This panel summarizes your Module assignments and compares engagement between learners who have reached their target mastery strength and those who haven't.

The OttoLearn analytics page, showing three analytics panels. The Assignment Engagement panel is the third panel (from left to right) of the three, and it is circled with a blue box. The other two panels to the left of the Assignment Engagement panel are blurred out.

The first two analytics in the panel provide information on assignments

To review, an “assignment” is an association between a learner and some content. For example, if a learner is assigned a Mastery Profile containing three Modules, this is counted as three Module assignments. 
Close-up of the first row on the Assignment Engagement panel, showing two blocks: one with the number of Module assignments (384) and the number of Module assignments not started (9).

The Module Assignments metric shows how many learner - Module associations there are. This might sound familiar because the same metric also appears in the Learner Engagement analytics panel that we looked at last week.

In the screenshot above, you can see that I have 384 Module assignments. The text below — that reads “7 Modules assigned” — indicates that 7 different Modules have been assigned to my learners. Each learner may be assigned one or more of these Modules. 

The Module Assignments Not Started metric shows that of these 384 assignments, 9 of them have not been started. 

“Not started” means that no Activities have been performed within that Module assignment. Therefore, you want the number of Module Assignments Not Started to drop over time. 

The following two analytics focus on Module assignments where learners have reached their target mastery strength. The target mastery strength learners must achieve is based on the mastery goal you set for each Module. 

Close-up of the second row on the Assignment Engagement panel, showing two blocks: one with the percent of assignments in mastery assigned in the last 30 days (20%) and the number of assignments in mastery assigned OVER 30 days ago (88%).

The metric on the left, Assignments in Mastery (assigned in the last 30 days), shows the percentage of Module assignments that took place in the past 30 days where learners have reached their target mastery strength. For example, in the screenshot above, of the 10 module assignments in my account in the past 30 days, learners have reached their target mastery strength in 20% of them. Put another way, this means that of the 10 Modules assigned in the past 30 days, two are in mastery. 

This metric illustrates how learners are engaging with newly assigned content.

Assignments in Mastery (assigned over 30 days ago) shows the percentage of Module assignments that took place more than 30 days ago where learners have reached their target mastery strength. In the screenshot above, you can see that 374 of my Module assignments took place over 30 days ago and learners have achieved their target mastery strength in 88% of them. 

Together, these two metrics give you a short- and long-term view of progress toward mastery in your account.

Below, is a graphical representation of how learners engage with your content based on their mastery status (if they were at their target mastery strength) at the end of each month.

Close-up of the third block on the Assignment Engagement panel. This block shows a graph that depicts the trend of assignments: not in mastery but engaged; not in mastery and not engaged; in mastery and engaged; and in mastery, but not engaged. Those not in mastery show the trend going up then down, showing that the number of unengaged assignments started low, went up slightly, then started to decline. Those in mastery started high, but then slowly starts to decline.

The blue bars represent learners who were not at their target mastery strength at the end of the month. Specifically, the lighter blue portion of each bar represents learners who engaged with their training, while the darker blue represents learners who did not engage. 

The dark blue bars in this graph are most concerning as they represent disengaged learners who have not reached their target mastery strength. Ideally, you want to see little to no dark blue.

The orange bars represent learners who were at their target mastery strength at the end of the month.  The lighter orange portion of each bar represents learners who engaged with their training, while the darker orange represents learners who did not engage. If learners have nothing to learn, they may not be prompted to engage. 

When you assign new training or add new learners, the blue bars will represent a larger portion of your graph. As learners reach their target mastery strength, this will flip, and the orange bars will take up a larger portion.

As you can see in the screenshot above, my orange bars are significantly taller than my blue bards. This is great because it means most of my learners have already reached their target mastery strength. I can now focus my attention on the blue bars. Using this information alongside the other analytics panels, I can figure out if these learners have been assigned new content, are making slow progress, or simply aren’t engaging.

The purple line represents the total number of Activities completed each month.

As learners reach their target mastery strength, they will have less to learn or train. As a result, this line often starts to trend downward as the orange bars get taller.

The screenshot above shows the number of Activities completed in October is about half of what it was in August.

The black line represents the total number of Activities completed in Module assignments where learners were not at their target mastery strength at the end of the month.

This line tends to trend in the same direction as the blue bars in your graph.

In the screenshot above, you can see that this line drops in October. This is the same month where I have more learners who are not engaged and not in mastery (the dark blue part of the blue bar).

At the bottom of the Assignment Engagement panel, you can see a representation of Engagement and Mastery by Module

Close-up of the fourth and final block on the Assignment Engagement panel, a sideways bar chart that shows the percent of engaged learners (a blue bar) and the percent of learners in mastery by module.

The blue bars represent the percentage of learners assigned each Module and engaged (completed at least one Activity). As you can see in the screenshot above, all of my Modules have 70% engagement or higher. 

The orange bars represent the  number of learners assigned to a Module who have reached their target mastery strength. Looking at the screenshot above, you can see that in each of my Modules, 80% (or more) of learners have reached their target mastery strength. 

When you first assign a Module, you want the blue bar to be as close to 100% as possible. This shows learners are engaging with your new content.

As learners reach their target mastery strength (orange bar), they will have less to learn or train and will engage less. Therefore the blue bars will usually get shorter as the orange bars get longer. This may vary depending on the engagement schedule(s) you have set up or if you regularly add new content to existing Modules.

Hopefully, you are finding this journey into OttoLearn analytics helpful. Stay tuned for our post next week on the Knowledge Gaps and Lifts analytics panel.

  • For learning content to enter and remain in a learner’s long-term memory, the learner needs multiple exposures to the content. Long-term encoding “needs opportunities for rehearsal and repetition,” Jan Breckwoldt et al. wrote in a study on mass vs. spaced learning.
  • Repeated exposures alone are not as helpful as spaced repetitions that ask learners to recall and apply information — and especially when learners have to use that information in different ways, many studies have found (for example Rohrer, Lin et al., and Bjork and Bjork).
  • The ability to remember information depends on the number of times a learner encounters it and the interval between repetitions, according to Tabibian et al.

Intrinsic

Extrinsic

Access to knowledge or performance support tools

Achieving a worthwhile or meaningful goal

Achieving a reward — a grade, a badge, points, a prize

Receiving an unexpected reward

Contributing to improving a project or a product

Wanting to be perceived as a team player, wanting to be liked

Improving performance or effectiveness relative to own past performance

Improving performance or effectiveness relative to coworkers; “winning” or being the best

Knowing enough to avoid making mistakes and do better work

Losing status or levels within a gamified framework as the result of making a mistake

Feeling of completing a task, accomplishing a goal, finishing a project

Doing the “right” thing — following rules or norms, being ethical

  1. Is the corporation’s compliance training program well designed?

    Prosecutors will look at whether the training is designed to prevent and detect wrongdoing and whether management is enforcing the program by means of training, incentives and discipline.

  2. Is the program being applied earnestly and in good faith? In other words, is the program being implemented effectively?

    Prosecutors are expected to directly investigate whether a program is merely a “paper program” or a sincere effort. Evidence of a company-wide commitment to ethics and compliance, promoted by senior and middle management, is needed.

  3. Does the corporation’s compliance training program work in practice?

    Good intentions and training don’t count if they don’t work; in assessing whether the program “works in practice,” prosecutors will look at how the suspected misconduct was detected, what the company’s investigation process is and how the company is trying to correct the problem.

Microlearning delivers small, narrowly focused bits of information.

Adaptive microlearning tailors that content to each learner’s knowledge gaps and learning goals, ensuring the training is relevant.

Continuous adaptive microlearning conditions each learner to engage with relevant training every day — for just a few minutes.

Current Rank

Previous Rank

Technology

1

1

Personalization/adaptive delivery

2

3

Artificial intelligence

3

new

Learning analytics

4

2

Collaborative/social learning

5

5

Micro learning

6

new

Learning experience platforms

7

7

Virtual and augmented reality

8

10

Mobile delivery

9

4

Consulting more deeply with the business

10

6

Showing value

11

new

Performance support

12

11

Neuroscience/cognitive science

13

13

Video

14

9

Curation

15

12

Developing the L&D function

No items found.

When people have a question or don’t know how to do something, what do they do?

Whip out a smartphone and look for information. What they don’t do is sign up for a 1-hour seminar.

Microlearning brings corporate eLearning into the modern paradigm. Microlearning describes eLearning content that is:

  • Narrowly focused
  • Short
  • Available on demand
  • Mobile-first or mobile-friendly

It must answer a question, meet an immediate need, or help the learner solve a problem.

In the City of BigTown, there was held a conference,
One of training professionals — those making a difference.
A difference to company ROI by delivering training,
From many perspectives — like Manufacturing.
And, too, there were call centers, colleges, corporate sectors,
Each chiming in about outcomes and metrics.
All shipped their training through an LMS platform,
But were desperately seeking true training reform.

Antonio

One was Antonio, who hated the manuals —
For his product revisions and updates, they were annual.
Plus his printing costs? Oh, they were crazy!
And he truly believed that franchisors were hazy.

None knew how to train in an effective way,
"There’s too much to read, to do!” they’d all say.
For there were many levels of training to assign,
From the top at head office, down to those on the front-line.

Trainers Helen and Abinash nodded, “We agree!”
Said Feng, "Paper and handbooks? Just another dead tree.
On the job, not everyone will have the info they need,
Because the content changes and updates they never did read.
They never learned the content added along the way
That may apply to their region or division today.
Plus, in the field with team members in many locations,
Mobile-first training would make a stronger foundation!

Said Sales trainer Jane of her PDFs stored online,
“They’re rarely revisited after onboarding time.
I need content delivered in snack-sized bites,
And the ability to test them until they get it right.”
Ursula
chimed in, "Onboarding’s a pain for new hires,
With most feeling like their hair is on fire!
Plus, promoted reps must refresh what they know
To be properly prepared to perform their new role."

"I deal with compliance," sighed Manal the Banker.
Abinash nodded, Frank turned to thank her,
For she’d raised the ugliest concern of them all —
That certifications aren’t based on year-long recall.
“To maintain the standards and follow each rule,
We need more than one test that comes out of the blue.
When it comes to things like health & safety, it's a game-changer
Because if their training is lacking, they could be in danger.”

Antonio

Continuing he asked, “Could training be location-specific?
As learners move through the plant, alerts would be terrific!”
Helen asked who used traditional classroom training
Combined with online to keep interest from waning.
Did they have workshops, seminars, or events,
The kind that take workers away from their desk?
"They learn at that moment, then likely forget —
is there a way to get long-term retainment?”

Rachel had been quiet, she’d said not a word,
When suddenly she leaned in so her voice would be heard.
"We solved these concerns after ditching binders and books —
We use daily drip training and our learners are hooked!
When we update our content, it gets to them faster,
And metrics and KPIs reveal the content 'masters.'
We use OttoLearn for microlearning and we’ve been thrilled,
for all of our training needs — and more — are fulfilled."

So ends our tale of the nine trainers complaining
about the problems they had delivering training.
Training that mattered, with metrics and firm ROI,
Based on data analysis of prime KPIs.
Many problems they shared, with no clear resolution,
Found Agile Microlearning with Otto was the solution!
Microlearning both adaptive and agile saved them from disaster,
Making trainers and trainees learn happily ever after!

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  • Indonesian
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  • Persian (Farsi)
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Content Studio

  • Combining the question and activity tabs
  • New WYSIWYG editor which is “inline” with the text
  • Ability to include media (images, video, audio) within activities (question, answers and feedback)
  • Icons to indicate correct answer, position locking, whether or not the answer is visible to learners (active), and override feedback

Recently Released

  • Learner password reset
  • Streamlined data entry into the content studio, by being able to quickly add
  • Numerous small updates and bug fixes
  • Check out our most recent updates and add yourself to be automatically notified when we push updates

Option

Pros

Cons

Seats

  • Super easy to understand
  • Very predictable cost, if you have a specific number of users (eg: employees)
  • Doesn’t differentiate between users that have different volumes.
  • Have to purchase seats for your maximum number of users.‍

Active Users
(Typically the number of users that log in during a month)

  • You don’t need a license for every specific user, you can often only license half of your users (since perhaps only half ever log in during a month)
  • Typically there is a large cost for going over your licensed number of users, which can be incredibly expensive (eg: 5-10x more than your licensed cost)
  • You often have to “play games” as an administrator, not wanting to do a mass course enrollment if you have only have your users licensed in a month

Trend

What It Means

Why It Matters

Adaptive Learning

An algorithm determines each learner’s knowledge gaps and feeds them practice activities to close those gaps.

Efficiency. Learners learn the material faster because they spend less time on what they already know.

Personalized Learning

Learners can follow a scaffolded learner path or self-direct their learning.

Learners are inquisitive. We all Google for information when we need it, so why lock learners into a particular learning path?

Learners engage the most when they are allowed to deviate from a set path and explore available content.

At the end of the day, as long as each learner reaches their mastery goal, the particular path they took to reach there is unimportant.

Microlearning

Delivering content to the learner in smaller chunks.

Chunking content is important only if it is paired with the ability to search for and find specific content chunks “on demand” and the ability to consume just the chunks a learner needs. With these features, training doubles as a performance support.

Learning Experience (LX) Design

Using science and art to create experiences that help learners fulfill the learning outcomes they desire, in a user-centered and goal-directed way.1

Have you used Google? If so, then you have benefitted from Experience Design (XD): When you search for something, you rarely have to go past the first result.

With good XD, you don’t think about the design;  it “just works.”

With poor XD, your learners will disengage. They’ll say they “don’t have time.” What they are really saying is that they “don’t have time for the poor experience.”

Artificial Intelligence

Typically, when used in relation to L&D, AI actually means “machine learning.”

Machine learning algorithms learn from data and “get smarter” over time.

Have you used Netflix or Amazon recommendations? They are based on machine learning.

The algorithms look at a ton of data, including your past choices and choices made by others who are similar to you, to make predictions as to what you will want to watch or buy.

In L&D, machine learning principles are being integrated in much the same way: to provide recommended content for a learner to consume.

This reduces the burden on training administrators to try to predict or guess what is relevant for each learner. It also provides a more personalized experience for each learner.

Imagine that you are a salesperson, and your training mix subtly and automatically shifts, based on the nature of opportunities in your sales pipeline. You are offered training only on available products that you have not already mastered. That would be a training program that is driven by machine learning.

Learning Analytics

An algorithm determines each learner’s knowledge gaps and feeds them practice activities to close those gaps.

Use learning analytics to make better decisions by converting data into insights.
The true value is not just in providing more data, more charts, and more graphs. The value is in leveraging AI to search for and surface insights that you’d never think to look for.

Combine the analytics from learners’ performance with key KPIs for the outcomes you desire, and have the analytics engine generate predictions such as, “Learners who reach mastery in the Objection Handling module will close 3.4 percent more deals.”

Now that’s actionable intel.

1 learningexperiencedesign.com

14% of organizations are experimenting with artificial intelligence tools such as machine learning and live chat (up from 6% in 2016)
30% of organizations are using games and simulations (up from 20% in 2016)
Fastest growth segments include continuous learning, Artificial Intelligence (AI), Augmented Reality (AR)
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  • Spanish
The Cognitive Science Behind OttoLearn - OttoLearn Adaptive MicrolearningThe Cognitive Science Behind OttoLearn - OttoLearn Microlearning

Hi Josh,

About a week before I began getting my Ottolearn Mastery Moments, I had a popup window from Adobe appear on my screen as I was working on another project, prompting me to update my version of Flash. We do use Flash, so like an idiot, I clicked on the popup and asked it to start the update—and only then noticed that the url was not an adobe address. Of course, I closed the popup window using the X in the upper corner, which didn’t solve anything. Our IT guys did the best they could for me, but my computer is still compromised, and is being replaced.

Fast forward to Ottolearn and your Online Security for Employees course. After completing several mastery moments, I have now learned what to do with popups like that. This morning, as I restarted my computer again, that same Adobe popup appeared and this time I was ready! I opened task manager and killed that little $%^&^ dead in its tracks.

I know the point of letting us try out OttoLearn as participants was for us to experience the power of this platform from the learner’s point of view. I can tell you that I personally am very grateful for the training you provided to me, and the fact that I was able to let others in my company know how to kill off those nasty virus-carrying popups. Yes, it works. Yes, it’s fun! And yes, I have a true feeling of accomplishment.

I can’t wait for the point at which we can talk more about developing courses for our clients.

Thank you!

Experience

Exp.

High

New accounting rules

Workplace violence & harassment prevention

Low

Framing a basement

Changing a tire

High

Low

Perceived Relevance

No items found.

Retrieval practice is the key to retention.

Your brain wants to be as efficient as possible. Why would it try to encode information for long term storage if it thinks you don’t need it? You need to actually practice retrieving memories (information) in order to have your brain store it in long-term memory.

Spaced retrieval radically improves learning efficiency.

You not only need to practice retrieving information from memory, but you need to wait until you’re on the edge of forgetting it. This is why cramming is so ineffective at generating long-term retention.

Interleaved learning feels strange at first, but dramatically improves retention and skill.

Interleaved learning—mixing up material while learning and practicing, such as mixing up practice activities while learning WHMIS and supervisory skills, will improve your retention of both.

Option

Pros

Cons

User-based
(Seats)

  • Cost predictability. Each seat costs you $x/month
  • Typically more expensive than a usage-based license

Usage-based

  • Typically less expensive than a seats license
  • Cost variability tempered by pre-purchasing usage credits that never expire and consume them over time

Engagement Factors

Experience

Exp.

High

  • Best possible quadrant for engagement 
  • Will overcome learning obstacles
  • Will find a way to learn, even if materials are poor  
  • Won’t need nudging or incentives
  • Text is great
  • Can easily learn something
  • May need to work up the energy to engage in low quality materials  
  • May procrastinate, so incentives can help motivate.
  • Text is great

Low

  • Wants to learn
  • Has little experience so can benefit from more instructional quality
  • Greatest benefit of video and other rich media
  • Worst possible quadrant  
  • May not have experience in the topic
  • May not really care about it
  • Will require a lot of motivation to see engagement
  • Video can help

High

Low

Perceived Relevance

Neovation Learning Solutions Team - OttoLearn Microlearning is a product of Neovation Learning Solutions

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