While many desk-shackled students may wish they were napping rather than enduring yet another monotonous lecture, learning is by no means confined within the classroom. In fact, we engage in focused learning activities every day. Think of the last time you ordered a book, booked a flight, or bought a car. How did you choose which book to read, where to go for vacation, or which car was best for you? You may have searched online, read reviews, or asked others for advice to help you make an informed decision. In a word, you learned.
Learning is a complex process with distinct stages, each with corresponding tasks and emotions. Understanding how users learn can help us design experiences that support the user throughout the entire process. So let’s learn a thing or two about learning itself.
A hierarchy of learning
According to Benjamin Bloom’s landmark 1956 study, we can classify learning in a hierarchy of six levels, where each level forms the foundation for the next. At the base of Bloom’s Taxonomy lies knowledge and comprehension—the plain facts and figures we were quizzed on at school. Once the learner has knowledge and comprehends it, the learner can begin to apply her knowledge experientially as one might do when driving a car for first time. The highest levels of learning involve deeply analyzing ideas and combining them into something new—the realm of the expert.
Fig. 1: Bloom’s Taxonomy of Learning.
Learning as a process
While Bloom’s Taxonomy reveals the many levels of learning, understanding how these levels flow together in practice is crucial. Carol Kuhlthau, a professor at Rutgers University, studied how students researched topics for term paper assignments.. While roughly consistent with Bloom’s Taxonomy, her research yielded much greater insight into the sequential nature of learning and its implications on the digital environment. Let’s look at Carol’s key findings and see how we can apply them to design for learnability.
Fig. 2: A representation of the learning process from Carol Kuhlthau’s paper “Inside the Search Process.”
Initiation is the phase where you become aware that you need information. It’s often accompanied by uncertainty and apprehension. For example, my wife recently told me that she’s tired of taking the bus and wants a car. Hesitant at first, I eventually came around and agreed. Now I have a need to research vehicles.
The selection phase involves committing to constraints that narrow the information search. In our case, we quickly threw out motorcycles, vans, and SUVs, deciding to look only at small, family cars. This phase tends to produce a spike in optimism once the learner makes the selection.
The optimism of selection usually gives way once more to confusion, uncertainty, and doubt as one realizes the many options still left to explore. Even though we had decided on small family cars, we still had to sift through dozens of makes and models, each with advantages and disadvantages. Kuhlthau’s study found that about half of her students never made it past this stage.
Formulation is the turning point where all the information encountered thus far is formulated into a specific, tangible requirement. In our car hunt we reached formulation when we decided that a four-six-year-old five-door Nissan Almera hatchback with 30,000–50,000 miles was the best fit for our needs and budget. The formulation stage is marked by less anxiety and increased confidence.
Once the problem has been clearly articulated in the formulation phase, the next step is to evaluate the available solutions. Once we had a clear of idea of the model we wanted, we used automotive websites to search for cars in our area matching our criteria. Confidence continues to increase throughout the collection process.
The final stage of the process is to perform an action based on the newly acquired knowledge. For Kuhlthau’s students, this meant actually writing the term paper. For me, it will mean going to the dealership, paying, and driving home a new car.
Designing for learnability
Most websites invest the majority of their effort into streamlining the very last stage of this process: the action phase. It’s understandable: businesses make money through conversions. However, the company that best supports the user throughout the entire learning process has the upper hand in converting that loyal user into a paying customer. With that in mind, let’s look at digital solutions to seven learning-oriented tasks.
“Unknown unknowns” characterize the beginning of the learning process. Often, users have no idea what’s out there. Rather than expect the user to search for a precise make and model at this point, we must help the user explore. Browsing and flexible filtering options can expose users to serendipitous discovery, while personalized suggestions can help users set off on the right foot.
Fig. 3: Last.fm keeps track of the music you listen to and recommends new artists based on how your musical tastes compare with others.
Fig. 4:TravelMatch.co.uk doesn’t force you to fill in a date or a destination like most travel websites. Instead, they help users explore holiday options by providing flexible filtering, such as the destination’s temperature.
Learning can be a long-term activity. Saving a page or item—whether in the browser, a shopping basket, or in a wish list—can help users return to something they found earlier. Showing a list of recently viewed items can also provide a more passive means for helping users re-find.
Fig. 5: Nutshell CRM shows a list of recently viewed items when the user focuses on the search box, but before they start typing.
While simple bookmarking helps users re-find, a higher-level task is to actually understand the information encountered thus far and how it fits together. Often this simply occurs in the mind; other times we may jot ideas down on paper. Whatever the medium, organizing items and ideas into categories is key to the learning process.
Fig. 6: Foodily not only allow users to save their favorite recipes, but to organize them into meal plans.
In addition to organizing items into categories, being able to view a side-by-side comparison aids in the analysis process, especially during the collection phase.
Fig. 7: Canon’s website allows users to compare up to three cameras side-by-side.
An extension of organize and compare, annotation enables users to enrich collected items with their own notes and ratings.
Fig. 8: Globrix allow users to rate and write notes on each property that they’ve bookmarked.
Toward the end of processing learning, the user typically has a decent understanding of what they want. And yet that ideal job, house, or car may still be elusive. The ability to save a search and receive an alert when something new appears can be priceless.
Fig. 9: Primelocation allows users to save a search, as well as to receive a daily email with any new properties matching the user’s criteria.
We don’t often make decisions in a vacuum. Friends, colleagues, and spouses often get their say as well. Unfortunately, the collaborative learning process is very poorly supported on the web today. During my car search, my wife and I often sent links back and forth to one another through email, a less-than-perfect solution. Shared bookmarks and collaborative annotations and ratings would go a long way in making learning on the web more social.
Fig. 10: Google Bookmarks allows users to create lists of bookmarks, share those lists with others, and comment both on individual bookmarks, as well as on the list as a whole.
From the classroom to the computer screen
Far from being monopolized by schools, learning is an essential human activity. Empathizing with and supporting users as they traverse the many stages of learning fosters happier users and a more profitable business. We could all benefit from psychologist Carl Rogers’s wise advice to educators: