By Alexandra Urban
Nail It
At its core, every technology company should be leveraging data to improve its services and help users reach their goals. At Coursera, we’re doubling down on the importance of data, machine learning, and artificial intelligence to propel our partners and platform towards the future of higher education. A crucial piece of the data puzzle is understanding who our learners are, their actions on the platform, their likes, dislikes, aspirations, and patterns of engagement. At this year’s Partners Conference, we unveiled completely overhauled Course, Specialization, and Institution Data Dashboards. Ensuring our instructors and course teams have accurate, up-to-date, and actionable data is our top priority. Before diving into further innovation, we want to nail the essentials. With that in mind, these new dashboards provide reach, satisfaction, payment, and retention data for our content.
Scale It
Much of the research that Coursera and our partners are conducting investigates the challenge of scaling high-quality teaching. How can we better visualize the different paths learners take through online content? Irene Kalkanis at Imperial College London delved into data visualization to answer this. Her work helps instructional designers by highlighting, for example, the items learners return to after failing an assessment. If, for instance, it’s a video that the majority of these learners are returning to, how can we ensure it explains the concepts in a clear, engaging way? Matt Reynolds at Yale University is studying the impact of animation on learning outcomes: early results suggest that learners who watch videos with animated explanations score higher and need fewer attempts to pass than peers who watched a video on the same topics without animations.
But what about setting learners up for success at the very start of a course? Maria Janelli at the American Museum of Natural History explored the power of pre-tests. She found that while they can deter some learners (possibly due to the extra work), pre-tested learners who attempt the course’s last assessment earned significantly higher final grades. As we explore research questions, often the most interesting results are those that spark further questions. In this case, the question is: how can we achieve the benefits of pre-testing without the downside of the extra burden placed on students?
Another way we are supporting learners at the beginning of a course is through active goal setting, in which learners can choose a small but meaningful goal to get started. By implementing interventions based in pedagogy research, such as the principles of emphasizing social proof and creating achievable challenges, we can help our learners stick with the courses they’ve started. As we begin to see which interventions are most helpful for whom, we can start to personalize the messages and nugdes so they help each learner as much as possible.
And Beyond
Through the innovative Skills Graph, Coursera can now pull out specific skills from our courses and surface them for learners. If you want to learn a specific library in the Python programming language, or you’re looking for a “softer” skill to enhance your career, for example, you can search for these directly in our catalogue by typing in “SciPy” or “confidence.” This skills-level search is powered by a hierarchy of knowledge beneath our platform, combining the power of our in-house Data Science team building a robust Skills Graph, instructors tagging skills to their courses, and learners verifying what each course has taught them. This same data architecture also helps employers identify the best employees to upskill into new open roles by surfacing those with the right prerequisites to become, for example, a Machine Learning specialist. Coursera can now track skill patterns across countries and industries to help identify gaps for further learning investments, as showcased by our Global Skills Index.
Throughout Data Track at Conference, and by combining our insights with those from our partners, we’re able to broaden our knowledge of how learners gain new skills. With this deeper understanding, we’re able to better support our millions of learners around the world!
The post Nail It, Then Scale It: Doubling Down on Data to Achieve Platform Success appeared first on Coursera Blog.
Source:
https://blog.coursera.org/doubling-down-on-data-to-achieve-platform-success/