Here’s What To Do Differently…

Leaderboards are commonly used by educators to engage students in many educational contexts. But most implementations fail to truly unlock the benefits for learner engagement by making the same mistakes, time and again. This article highlights why leaderboards work, tackles the common misconceptions around leaderboards and student engagement, and provides a new mental model for thinking about how to implement leaderboards in eLearning platforms.

What Makes Leaderboards So Effective

Leaderboards create effective social interaction and competition in eLearning platforms by comparing students with their peers. By ranking students in accordance with metrics closely aligned with their learning outcomes, educators create an effective motivational tool to push students to perform their best.

By ranking students alongside others in a similar position, leaderboards not only motivate students to achieve better results but also remind them that they are not alone. This is particularly important for eLearning providers that primarily facilitate learning where in-person learning may not be possible. Self-study can be a lonely journey, and leaderboards address some of the space left by a lack of a classroom-based environment.

Why Most Leaderboards Fail

Here are the core reasons that most leaderboard implementations fail to engage learners effectively.

Disproportionate Size

At their core, leaderboards are actually very simple: rank students in order by a particular metric that is closely related to their success. The trouble starts when educators think this basic approach that works for classroom-size cohorts will work for large eLearning platforms that operate at a significantly higher scale.

As the number of learners in a leaderboard increases, engagement usually drops proportionally. This is a natural consequence of larger leaderboards leaving students feeling less connected to their peers, causing disassociation with the concept of the leaderboard itself. What’s more, larger and larger leaderboards become an increasingly daunting experience for new learners, causing a “cold start” problem where new learners who join leaderboards later than other students have a delayed engagement rate than those who had a head start.

The “All Time” Leaderboard Problem

New learners are equally disincentivized to try to move up the rankings by “all time” leaderboards with no fixed end date. This makes the “cold start” problem worse as time goes on, extending it not just to new learners but even regular learners who may just have different levels of available time to commit to studying. Leaderboards that never end eventually only engage students in the top 1%, leaving most feeling left out.

Balancing Issues

eLearning providers often use leaderboards to rank users by a combination of factors that take into account their collective progress using the platform. Viewing notes, watching lessons, and answering questions are some of the student interactions that eLearning platforms aim to capture within leaderboard logic.

Issues start when the assumptions built-into the calculations that rank users aren’t balanced with reality. For example an eLearning provider might decide to give equal weighting to watching a video as compared with viewing notes. However in practice, video content can be far more engaging and lead to a better understanding of topics than written notes.

The outcome is that students that watch more videos than others feel like they have a better understanding than those who don’t, but the leaderboard doesn’t reflect that. Meanwhile students who have quickly read through their notes multiple times without detail progress much faster through the rankings. Such imbalances in leaderboard rankings can cause students on both sides to disassociate, making them seem superfluous.

A Better Approach

Segmentation

A lot of the leaderboard problems addressed in this article can be resolved at least in part with a proper student segmentation strategy. Segmentation is about finding something that a “reasonable” number of students have in common, and grouping them up into smaller, more socially-interconnected leaderboards that resolve the problems or disproportionate leaderboard size. The questions then become, what is a “reasonable” size for a leaderboard? And what should determine how we group students?

The answers largely depend on the context. In schools and institutions that support thousands of learners a good segmentation strategy could be grouping students by course or subject matter. For larger eLearning platforms supporting hundreds of thousands or millions of learners globally, an effective segmentation strategy is likely more complex.

In a typical eLearning platform, even a single subject or course could support tens of thousands of students. In these cases consider grouping students by grade or proficiency to create smaller leaderboards that feel more relevant to each learner.

A crucial part of segmenting by proficiency level is allowing users the opportunity to move up to a new leaderboard as they improve. Similarly, assessing students’ progress regularly and transitioning them to lower leaderboards is important to maintain an effective peer group.

Natural Reset Periods

Resetting leaderboard rankings in accordance with a natural schedule is also important for maintaining engagement. The choice of a daily, weekly or monthly schedule should be predicated on the level of activity that educators expect.

If students are able to progress quickly, with students able to participate multiple times a day, a daily leaderboard might be justified. However, for most platforms, a weekly or monthly cadence allows enough time for all students to make meaningful progress and see that reflected in their rankings. Crucially, resetting leaderboards on a defined schedule prevents gaps in rankings from appearing over time which cause disengagement.

Balance Testing

Before releasing a leaderboards feature it’s important to test the weights of the interactions that you’ve decided to make up the ranking logic for your leaderboards. Be aware of your student’s learning patterns and ensure that in all scenarios, no subset of students will be able to unfairly outperform others in a manner that could materially affect the engagement of other students.

Using One-Off Leaderboards

Alongside your regular leaderboards, experiment with time-limited one-off leaderboards around special events such as Halloween, Christmas, or important calendar dates in the context of your students’ learning journey. This not only increases engagement during these periods but prevents your regular leaderboards from becoming stale.

Conclusion

I hope this discussion has helped educators and e-learning providers rethink their approach to implementing leaderboards and guides them towards creating a new mental model for more engaging student experiences.