Learning experience designers, or instructional designers, have and will continue to play a critical role in the rise and efficacy of online learning at scale. At edX, our learning experience design team is central to our success, helping to build experiences and curriculum that result in learning that translates into “doing.”
In this interview, we talk with edX learning experience designer Ben Piscopo to learn more about the field of instructional design, the value learning designers bring to online learning, and insights for effectively building and scaling your own learning programs.
What is a learning experience designer?
Designing the order, format, and activities that lead to successful learning has become a big field, a big industry in and of itself. This discipline, which combines learning science and technology, has really existed since the dawn of recordable media, but more recently has exploded in the personal computing age.
In higher education, traditionally, schools leaned on the subject matter expertise of faculty, like a professor of physics, to drive and shape a learning experience. But — while a professor may know a lot about physics, they might not have all of the tools, techniques, and strategies required to make a successful experience for learners. For example, sometimes, a professor is just really good on stage and that person is very memorable. A learner may interpret that as ‘that was a really good learning experience,’ but if it’s just lecture with not much room for creating or doing, making mistakes and learning from them, then there's a gap. Students don't always realize that.
When it comes to reformatting or creating a new learning experience online with new tools and technology, that's where this whole big need for an instructional designer and learning designer has come in. It may be about a professor not being trained in the skills and strategies and tools of learning design or in many cases they just don't have the time to do that work, so it can come down to the lowest common denominator which is ‘record myself giving hours of lecture and throw it online.’
There can be that sort of haphazard approach where online learning just becomes a photocopy experience of the in-person course. That's where instructional designers come in and predominantly in online learning. That's my description at 20,000 feet.
Zooming in a few thousand feet: Describe your day-to-day work at edX.
My job is to primarily serve as a consultant for course teams at our partner organizations, including universities, corporations, and nonprofits. I support and communicate best practices for learning at scale throughout the course development life cycle.
This work, which we call “partner enablement,” requires experience in various aspects of learning design: learner-centered design, instructional systems design, Bloom’s taxonomy, backward design, cognitive load theory, etc., plus the skill sets specific to consulting: strong communication and the ability to work with multiple partners simultaneously to ensure best practices for learning at scale are being utilized.
So we've got some traditional instructional design expertise plus the learning at scale piece, which edX is an expert in, and we communicate that out to our 140+ partners. That involves working directly with instructional design teams, having conversations with instructors who are on the fence about learning at scale, and supporting champions who are trying to get buy-in on campus. We have a lot of really good resources, strategies, and tools that can help them create their own workshops at their campuses to continue to drive forward their MOOC and online degree efforts.
At the end of the day, if a partner successfully delivers a course or program on our platform, and it's following our best practices for learning, then I know I’ve done my job right.
What does learning at scale look like? How do you help universities deliver content at scale?
Without examples, “learning at scale” can easily be construed as a buzzword. What we mean by learning at scale is better defined as: strategies and tactics educators use to support large-scale learning events. It’s about adjusting your lesson plans for an audience of 30 or 40 learners to 1,000 or 10,000 learners. Educators will need to be comfortable dealing with aggregate numbers of students and still creating instructor presence throughout a course run.
One example of learning at scale would be the peer learning tool developed by the University of British Columbia for the edX platform. It recreates Eric Mazur’s Peer Instruction technique, but for any number of learners. It works like this: 1) Learners are given a problem or scenario, along with multiple answer choices and an opportunity to explain their choice; 2) Upon submitting their choice and reason, they can review a set of responses by peers; 3) After reviewing their peer’s responses, they get a second chance to submit an answer; and 4) Ultimately, the learner is presented with two bar charts comparing first submissions with second submissions. A grade is given for participation only.
This learning experience helps clarify those grey concepts that do not have a “correct” answer all the time, although the course team can set one. It also ensures that multiple perspectives are presented to learners so that they can mentally chew on the problem or scenario. This is much like how a class-wide poll (or clickers) would work in a synchronous, on-campus class.
How does data inform and improve learning experiences on edX?
Most conversations I have with instructors and course teams incorporates what we have learned in the last 10-15 years about how learning happens online. When you pull in the data from millions of learners taking actions within edX courses and say ‘this is what the behavior is telling us,’ it starts breathing more legitimacy into the recommendations that you provide.
Many of the resources we share with instructional designers and faculty are based on existing learning science and documented techniques and strategies. I think that the unique perspective from edX comes from our massive amount of data. We can pull from many data points on learner behaviors collected through our Open edX platform which tell us certain things that could improve the learning experience.
For example: What should that first week of content really be focused on? How should you approach filming video content? Should they be full-length lectures or under 10 minutes (spoiler: 6-9 minutes is the sweet spot)? These are the kinds of advice we give partners and they are backed up by real learner behavior data.
What tips or advice would you give learning and development professionals responsible for building and scaling learning programs?
Whether within a corporate or academic context, according to Michael Allen’s Guide to e-Learning, powerful learning experiences should be these three things, at least: meaningful, memorable, and motivational.
Meaningful learning experiences are directly applicable to your life or the work you’re responsible for doing. Adult learners can smell a useless learning module from a mile away, so make sure it matters to them. Interview a prospective learner about the work they are doing and find out how this new learning experience will matter to them.
Memorable learning experiences leave a lasting impression, which leads to more durable learning. No one wants to read a dump of text or watch video lectures that go on seemingly forever. Design activities and interactions that keep the learning active. Engage learners in ways to require them to use their new knowledge or skills.
And finally, motivational learning experiences maximize curiosity, engagement, and rewards. For example, design learning that lands within your audience’s relative zone of proximal development (ZPD). What does this mean? Skills and knowledge build upon previously learned or mastered concepts. If you make successive lessons too difficult, or too easy, then learners might feel hopeless about their prospects in this course. They might give up prematurely in extremely difficult courses that they don’t feel prepared for.
If you as the learning designer find yourself in little or no control over planning the difficulty level across a curriculum, then think about other ways to scaffold learning. What prerequisites would be appropriate for a learner entering the course? Are there outside resources that could be leveraged to support novices taking this course? What about stretch goals for those who may find the course too easy?
I’ve found that if you can get these three M’s right, your program is much more likely to be successful and result in meaningful learning gains.
Learn More About Designing and Delivering Effective Corporate Learning
Looking for more insights into designing and delivering learning that "sticks"? Watch our webinar, The Science of "Doing": Corporate Learning that Sticks, to hear expert Dr. Nina Huntemann discuss deep learning methods that enable real capability-building and how Mercer, in partnership with edX, is experimenting with non-traditional types of just-in-time and deep learning to build lifelong learning habits and new skills.