If you’ve taken a MOOC (Massive Open Online Course) recently, you’ve probably participated in the forums. And you’ve probably noticed a voting mechanism, not unlike Facebook “Likes” or Reddit votes.
“Whenever someone posts something they think is interesting on Reddit, an up arrow, a down arrow, and a point tally appear next to that post. Then, if the Reddit community thinks it’s funny, interesting, or informative, they click the up arrow to give it an upvote. If they think it’s boring, stupid, or simply not worth their time, they click the down arrow to give it a downvote. Posts with a high upvote score are displayed more prominently on the website, and the best of the best show up on the coveted front page. Posts with a lot of downvotes are buried somewhere on subsequent pages, much like irrelevant Google search results.”
While the voting system is useful for helping students find posts that other students like, it doesn’t necessarily help identify posts with the best educational value.
- On one of the Coursera MOOCs earlier this year, the top-voted post was one that complained about the video introductions being slightly too long.
- A recent top-voted FutureLearn forum post discussed how the different accents of the lecturers impacted the learning experience.
Coursera forums are perhaps the best at this point. They do at least offer more sophisticated sorting choices and some rudimentary gamification to rank ‘forum reputations’ of prolific posters.
The following shares two ideas for enhancing FutureLearn forum posts to help students more easily find the most useful posts.
The “Like” link within forum posts is a useful function to indicate student preference, but the current implementation doesn’t provide enough richness to indicate why someone liked a post.
Students might like a post for a variety of reasons:
- entertainment value
- resonance with a student’s preferences or opinions
- usefulness in the context of course content
- insightfulness or unique student experiences
Suggestion #1: Add a “Recommend” category to the current system.
In addition to “Liking” posts for any reason that resonates, students could also identify posts that they would personally recommend other students to read—in order to benefit from the educational value or unique perspective.
Suggestion #2: Implement a star-based rating system.
People are familiar with the use and purpose of this type of system from numerous other sites like Amazon, Netflix, and TripAdvisor.
In conclusion, MOOC providers can make changes to forums that not only help students identify valuable forum discussions, but also increase the all-important engagement that could make high dropout rates a thing of the past.