by Dr. Page Chen, President and CIO
There is more and more talk these days about the impact of brain science on digital learning design. In an ongoing effort to learn more about how learners engage with online learning, researchers are continually capturing data to turn into insights about learner behavior. Designers often then seek to use those insights to trigger events that influence behavior change that they hope will lead to increased engagement and mastery.
The challenge I often have with the insights gained from many data and analytics systems is that while we all agree that not all learners are created the same, we seem to forget that not all digital learning experiences are designed the same. Therefore, as an industry, our analysis of the data about learner behavior becomes fundamentally flawed when we are comparing learner behavior in what potentially may be poorly designed learning experiences. In short, the design might be the issue, not the learner’s intrinsic motivations.
So, how do we avoid this? It all needs to begin with the intent of the designer of the learning experience. This ensures that every interaction a learner has when visiting a digital learning environment has been designed to place that learner in the right learning state of mind.
Imagine this scenario:
It’s your first day of class for school or your first day of training for your job. You arrive at the building where the class is located, park and walk up to the building. Looking at the door, you realize it has a keypad that requires you to enter a security code to allow you to open the door.
You quickly search back through the information about your course but can’t find the key-code for the door. You notice a sign that says if you’re having trouble getting in, go to another building for help. Off you go to the other building, hoping that it’s easy to figure out who can help you get the key-code. After a while, you return to the building where your course is located, new key-code in hand, and open the door.
You’re finally in the building, and you look around to find your classroom. There aren’t any clear directions to the classrooms, but there are a lot of doors available. After searching through a few of them, you find a door that leads to a hallway full of classrooms. Finally, you find the door to your class and you head inside.
If this was your experience, would you recommend this school or training facility to anyone else? Would you be in a learning state of mind? Unfortunately, this is a common experience in digital learning environments. The key-code for the front door is the password, and learners who need help are often sent to a completely different site. Once they are finally logged in, most sites lack clear instructions or navigation to help them understand where they need to go next.
If you were forced to go through all this effort when doing your online holiday shopping would you fight through it, or would you head over to Amazon and use the “OneClick” feature combined with free shipping?
Now imagine this scenario:
You’re enrolled in an online course. You’re struggling to complete an assignment before midnight. Maybe you’re a college student with a deadline, or a corporate employee who has to renew some essential job certification. You know the information you need is on your training site, but the interface is dense and confusing. You click through the site, but get lost searching for your assignment details. There’s no indication that you’re on the right path, or how far you have to go. At times like this, when there are no instructors or fellow learners to turn to for advice, it can feel like you’re lost in the woods.
In this scenario, the design of the site and the course is prohibiting you from learning. If this was your experience, would you want to come back to this site again to learn something else?
The Origins of Persuasive Design Strategy (PDS)
It all comes down to realizing that designing digital learning is about more than just great courses. It is critical to design the full digital learning environment to be an active participant in the learning process. Many other industries have already developed techniques for how to persuade online visitors to behave in the ways they designed for them to engage with digital content and to keep returning. This led to the question of what can we learn from these other industries in how they design their digital spaces, and how can we apply those principles to the design of digital learning environments?
My research led me to develop what we call Persuasive Design Strategies or PDS. PDS is an offshoot of Persuasive Technology or CAPTOLOGY (Computers as Persuasive Technology) which was first articulated by B.J. Fogg, a behavioral scientist and director of Stanford University’s Persuasive Technology Lab. Fogg looked at how different mediums of digital communication such as marketing sites, eCommerce, or mobile apps use persuasive techniques to persuade visitors to buy, lose weight, or keep playing a game. While I by no means invented persuasive design, I did spend the last decade researching and testing how Fogg’s techniques can be aligned to proven instructional design strategies and user experience design methodology. The result is the development of a set of design strategies we use every day in building out digital learning environments. We believe the design of the overall learning environment is just as important as the information it contains and have adopted these seven strategies of PDS as our guiding principles.
The term persuasion can feel out of place when discussing instructional endeavors, but it is important to note that persuasion is not coercion, and, in fact, has played a role in education since the days of Socrates. Persuasive Design is about the intent of the designer, and that intent is guided by two overarching concepts first suggested by Fogg: Ethos and Kairos, which boil down to trust and timing.
Seven Strategies of PDS
Before I walk through PDS, it is worth mentioning that it is not about a particular platform or some new technology that requires fancy algorithms, it is about the intent of the designer, or more importantly, designing with the intent to persuade behaviors in the learning environment to reduce frustration and increase engagement, and thus, positively improve mastery. While some of my examples may stem from the open-source platforms we commonly use, the strategies themselves should be seen as universal.
One of the most important strategies. Learners often are required to jump through several hoops just to get to their course. Navigating a site and parsing the content shouldn’t be a chore. Reducing the cognitive load on a learner is vital. If you make something simple to do, learners are more likely to do it (like the Amazon OneClick example).
The decisions made for user authentication is often one area that is overlooked but can make a huge impact. As the first task a learner is required to complete, making it simple means that a learner won’t be frustrated before they can even enter the site.
Another mistake that many digital learning sites often make is to try to provide all the options that a learner might need on every page. The result is that the learner is overwhelmed and unsure of what their next step should be. A clean and simple interface that uses reduction will easily show them where they need to go for all their needs.
Tunneling refers to the practice of directed guidance through an experience. Ideally, this structure of guidance should be almost invisible to the learner. This is much like the process of updating software on your computer. The system walks you through informed steps, but provides structure along the way. This is not a new strategy to educators. However, tunneling, if overused, can have the opposite desired effect.
A common misuse of tunneling is when a learner is forced into a never-ending loop of review and “try again” prompts in an effort to complete a lesson. If the desired behavior is for learners to review material and achieve mastery, reviewing the material should not feel punitive.
Suggestion is a strategy that is all about the kairos, where information is presented to learners at the right time to be most effective in changing their behavior. In other arenas, this can be seen in the use of recommendation engines that often require complex algorithms. As a design strategy, a simpler approach can be taken and produce similar results. In short, suggestions are triggers placed in the path of motivated learners used to persuade behavior and keep them engaged.
For example, if your learners are allowed to self enroll in courses, having a list of recommended courses would be a gentle push to encourage ongoing utilization. This information could be based on information stored in their profile or based on the courses they’ve already completed.
Tailoring is a strategy that allows for an experience to be tailored to the individual learner. Choice and personalizing the environment are the two main ways to do this. Often combined with suggestion, we see examples of this in providing multiple suggestions and allowing learners to select the one that interests them. We’ve all seen the “You may also like one of these top three items purchased together” types of messages. Why not suggest options and let learners make a choice when possible?
Tailoring can also be done by the platform, creating a more personal experience for each individual in ways as simple as calling them by name or remembering what they have recently viewed. Small changes like a personal greeting when they log in can transform the site into a social actor that participates in their learning process.
Showing content or instructions that pertain to an individual’s needs creates a feeling of connection to the environment that translates into increased engagement. A common way we combine reduction, suggestion, and tailoring is seen in our approach to designing feedback. An example: suggesting a learner review content they have gotten incorrect in a quiz and placing a link in the feedback for where to go to review combined with offering them the option to simply move on to the next question. This simple combination of strategies makes a suggestion to review, provides learner choice, and makes accepting either path simple and easy to do.
With self-Monitoring, learners are made aware of their progress as a way to persuade them to complete their goals. We’ve already seen examples throughout our industry about the use of gamification as a way to pull in techniques used in app and game design. And progress bars and checklists are a common occurrence in web design today and are often used to monitor a user’s task completion. But the strategy behind when and how do we decide to use them in the design of a digital learning experience can make all the difference.
Badges and certificates are another way to persuade learners to complete tasks or courses. Again the real power of PDS is seen when we think through the different strategies for when and how they are used. For example, certificates might be awarded for completion of a task or course. So any learner that completes a course with a passing grade can earn a certificate. However, a badge could be awarded for learners that complete the course with a grade of 95 or higher. The trick is letting them know in advance what potential badges are available, this is how you persuade the behavior for them to do what is necessary to earn them.
This is a simple but powerful strategy that is all about how to encourage and reinforce targeted behaviors. When it comes to conditioning there is a lot we can learn from digital game design to apply to designing digital learning: from when and how to use rewards to avoid reward fatigue to consistent design choices and the use of course templates that build trust and help to create good habits.
A great example of conditioning can be shown with a user profile. Learners are given instructions to complete their profile. The learners that follow the directions and the behavior you want to encourage are rewarded with access to the rest of the site. Learners that do not follow the directions could be limited to a few areas of information and cannot access areas they need or want. Remembering that to condition behavior change you’ll want to let them know why their access is limited.
Surveillance refers to the collection of data about learner behavior and performance results. If information is power, then giving that power to learners can be one of the most persuasive strategies of all. If the government asked all citizens to submit a DNA sample to a database I doubt many of us would comply, yet many of us will pay for a pretty colorful graph that tells us all about our family history based on sending in our DNA sample.
The use of the term surveillance is intentionally provocative, especially when we are talking about learning environments, but remember surveillance is only creepy if you don’t share your findings with the ones you are surveilling.
People can be very competitive and tapping into that competitiveness can in many cases be a good motivator. Leaderboards are a type of surveillance strategy that uses gamification to award points for specific behaviors. It’s also a great way to combine conditioning and reward positive behavior.
A few key points to recap:
- First, Persuasive Design Strategies do not, and in fact should not, be used as stand-alone strategies. They work best when combined together in meaningful ways.
- Second, PDS is about the purposeful intent of the designer and not about the tools or products they use. Although I will say that platforms designed to support the use of PDS, like we use at Remote-Learner, can produce more consistent results.
- And finally, PDS is about thinking and designing holistically the entire digital learning environment to persuade learners to be in the optimum learning state of mind.