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“We aim at providing pedagogical innovation on a daily basis”- Coursera

In a one on one with PC Quest, Richard Wong, VP of Engineering at Coursera Shares the tech platforms being used to deliver courseware.

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Jyoti Bhagat
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Coursera

In a one on one with PC Quest, Richard Wong, VP of Engineering at
Coursera Shares the tech platforms being used to deliver courseware.

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What are the tech platforms being used by Coursera
to deliver courseware?
Coursera builds its own proprietary platform to deliver courses. We aim at providing pedagogical innovation on a daily basis in various parts of the learning experience, including video, assessments,
discussions, group projects, authoring and analytics dashboards, etc. This is only possible with the platform that we design and create.
What are the video platforms & web interfaces
being used by Coursera?

Please describe the technology behind them. Coursera infrastructure is hosted on Amazon AWS. We used various cutting edge technologies to power the platform/application, including Cassandra, Kafka, Solr, Scala, React, Swift, Kotlin, etc. We also use various
CDNs to accelerate the video delivery to different parts of the world.
What in your opinion are the most critical technologies being adopted today by the education sector? What is the role of analytic usage?
The world is evolving fast. In the past, most of the edtech websites only focused simply on the homogenous video delivery experience; but not much on assessments or personalization, which left a big gap in the learning experience for most learners. At Coursera, in the last few years, we’ve invested heavily in technology to solve the assessment problem at scale. It ranges from scaling peer review
to Automatic Grading, and interactive feedback with Executable Code Block. The other big tool we use is big data. Every day, we track millions of interaction of our learners with our product. With this huge amount of data, we continuously run A/B experiments to validate the behaviors of learning and improve our platform on a
daily basis. We have seen many significant improvements
in learners’ course completion as the outcome of these experiments. By analyzing these data, we can also provide very specific feedback to the instructors to improve their content (e.g. if 90% of students
fail to answer specific quiz questions, it may indicate an issue with the content, or quiz question, etc. I expect artificial intelligence and big data are going to be the dominant force for the next few years
for major breakthroughs in the learning experience.

coursera richard-wong tech-platforms
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