The Perpetual Super-Novice
Published: December 3, 2007
In this column, I want to further explore one of the issues I mentioned in my inaugural column. I call it the problem of the perpetual super-novice. What is this? Simply put, it’s the tendency of people to stop learning about a digital product—whether it’s an operating system, desktop application, Web site, or hardware device.
After initially becoming somewhat familiar with a system, people often continue using the same inefficient, time-consuming styles of interaction they first learned. For example, they fail to discover shortcuts and accelerators in the applications they use. Other people learn only a small portion of a product’s capabilities and, as a result, don’t realize the full benefits the product offers. Why? What can operating systems, applications, Web sites, and devices do to better facilitate a person’s progression from novice to expert usage?
First, I’ll take a moment to define some terms. Here are three classifications for levels of user expertise I typically employ when discussing this issue:
- beginner—The beginning user has never before or rarely used a particular digital product. For beginners, almost every interaction with a system is exploratory. Their physical movements—and the on-screen representations of their movements—are mostly explicit and thoughtful. During this phase, users are trying to figure out what a product does and how they can use it. They are actively acquiring knowledge and creating and modifying their mental models.
- novice—The novice user has ascended the learning curve somewhat. Novice users have committed certain basic operations of a system to memory—either cognitive or muscle memory. They are comfortable within a circumscribed portion of a system’s total functionality. Their mental models of how and why a system behaves as it does are by no means complete—and in fact, might be quite inaccurate. But their limited knowledge has no adverse effects, so long as novice users stay within their comfort zones. If novice users need to learn some new area of functionality, their behavior reverts to that of a beginner while learning.
- expert—The expert user not only has mastery over many aspects of a system, the user’s mental model of the system is complete and accurate enough that learning a new area of functionality occurs rapidly and easily. Expert users not only know a product; they know how to learn more about the product.
Certainly, people become experts when there is a strong extrinsic motivation to do so. For example, you might learn how to do a mail merge in your word processing application, because, well, the boss just asked you to do a mail merge. But in the absence of extrinsic motivation, it seems that many people stay novices or, at most, become a form of knowledgeable novice that I call the super-novice. Super-novices know a lot about the limited parts of a system they use regularly and almost nothing about the other parts.
The thing is, people’s mastery of systems in other domains tends to expand naturally as people become more and more experienced with the systems. For example, a novice bicycle rider at first sticks to the basics—mount the bike, pedal, brake, turn, dismount. As new riders gain more experience, they tend naturally to explore the capabilities and performance characteristics of a bicycle. Can I hop a curb? What happens if I lock the brakes? How easily can I pop a wheelie?
Most desktop and Web applications do a so-so job of encouraging users’ exploration and mastery of the application. Can we do a better job of helping people ascend the learning curve? If so, how? These questions become especially interesting in light of the fact that many systems can easily track where, how, and in what order people perform certain interactions. Are there teachable moments that UX designers can exploit to encourage exploration and help turn novices into experts? Taking this approach would seem to blur the traditional hard line of demarcation between the application itself and its associated user assistance. But maybe it’s time that line should get blurred!
Defining Learning Goals
To encourage exploration and mastery, I suggest that designers more explicitly define their users’ learning goals, so they can address these goals during creation of a product’s workflows or information architecture and when designing features and functionality. And what better place for this information than in your personas or user profiles? (What? You’re not creating personas before doing design? For shame…)
For example, imagine, if you will, that you’ve been asked to create a persona for a statistical analysis application that your company produces. Let’s call the system Statistiphilia and our persona Harriet:
Harriet the Statistical Analyst
Background: Harriet has just finished her Masters in Psychology, with an emphasis on statistical methods and experimental design. She is looking forward to taking a position as a researcher at the State of Texas Department of Behavioral Sciences Research, where she will be evaluating program efficacy across time for various state-funded and state-run programs that provide low-income teenagers and young adults with job market preparation and life skills.
She has solid knowledge of many basic and a number of intermediate statistical analysis methods as well as research design. For her thesis, she designed a study that evaluated the efficacy of a job-training program that is run by a local charity, using a combination of survey data and objective measures of participants’ performance on various tests and evaluations.
Overall Learning Goals: Harriet is motivated to learn more sophisticated analysis techniques, because her job entails performing meta-analyses across multiple programs and program types, as well as using longitudinal evaluation methods with which she is not presently familiar.
System Experience Learning Goals: Harriet is familiar with other statistical analysis applications, having used both SPSS and SAS extensively during her graduate program. She has never used Statistiphilia before. However, she must use it in her current job, because that’s what her department has purchased for all ten of their statistical analysts. Her goal is to learn how to use Statistiphilia to perform each and every statistical analysis method she knows from SPSS and SAS, as well as new methods she knows she’ll need to learn to do her job.
She would also like to learn how to do a better job of managing large data sets, as well as efficiently publishing her analyses to the department’s intranet site, without exporting them to a Web authoring application.
Helping Users Learn
Once we’ve defined users’ learning goals, what then? Can we design user assistance that harnesses users’ intrinsic motivations and better supports users’ knowledge acquisition without making it more intrusive and annoying? It’s here that we run up against a conflict: When people make use of a product, their main goal is almost always to complete a task, not learn more about the product itself. And when they are of a mind to learn about the product, they often aren’t using it, or don’t even have access to it.
But maybe there are ways of activating intrinsic motivation from within a system. First, let’s think about what kinds of learning goals people have for digital products. They typically have one of these goals:
- They want to learn how to automate a task or accomplish something they’ve never done before.
- They want to learn how to do something they’re already doing in some other way, and do it either more efficiently, in a more expert manner, or with more fine-grained control.
Now let’s think about how people behave when they’re intrinsically motivated to learn more about how something works. What do they do? They do things like
- asking other people
- searching reference content
- searching the Web
- browsing forums and other archival sources of information
Knowing this, can UX designers do anything to leverage these types of behaviors? I recommend the following ways of helping users learn:
- Provide contextual user assistance. Within a system, provide the means for people to explore ways to do new things or to do better things that they’re already accomplishing in some way. Consider devoting a portion of each screen or module of an application to providing people with user assistance that has the aim of increasing their acquisition of system knowledge. Update this information frequently and dynamically. This kind of knowledge-acquisition content is distinct from classic procedural Help, which as Mike Hughes has pointed out in his UXmatters column is usually not very helpful anyway.
- Record users’ interactions to discover teachable moments. Encourage your interaction and information designers to discover what people need in order to learn—by, among other techniques, measuring what people do in an application and profiling their usage patterns. This will provide you with some insight into where people spend their time and what—as well as where—the teachable moments might be. This could be as simple as building an RSS feed reader directly into your application.
- Crowd-source content. If your company can’t afford to have a content development team create and manage all the necessary content, an alternative is to crowd-source your knowledge-acquisition content. Let people in the user community create content, so you can amass a repository of expertise-acquisition content for your application. Then let users share such information with other users by publishing it online. (You’ll probably want to authenticate users and do some level of content vetting.) Finally, other users can tag the information, rate it, share it with others, and so on. Of course, you should provide people with useful means of managing all this content. In this way, information regarding what people are learning about and what content is useful to them makes it into the application itself.
Are these recommendations different from those you might have seen elsewhere? Not really. I’m suggesting that, among other techniques, application providers leverage community building and crowd-sourcing to provide a means for people to become more proficient users. The real difference lies in the degree to which I advocate for explicitly focusing on learning.