Open edX® components

Open edX® includes multiple components all based on the driving principle of being scalable. The following are some of the important components to get started with the Open edX:

LMS (Learning Management System)

It is one of the most visible parts of Open edX with which the students interact. It displays content, run quizzes, discussion forum, and interactive apps. LMS also provides instructor dashboards. It uses several data stores. Courses are stored in MongoDB along with the videos served from YouTube and Amazon CDN and the student data is stored in MySQL.

CMS (Content Management System) or Studio or course authoring tool

It is the course authoring environment. edX Studio lets you weave your content together in a way that reinforces learning, insert videos, discussions, and a wide variety of exercises over a friendly graphical user interface. There is no limit to producing and customizing your training material with Open edX.

Open edX integrates the LTI components, customized Javascript as well as tools such as Google Instant Hangout and even a Molecule Editor and much more.

Discern allows anyone to use machine-learning-based automated textual classification as an API service.

This is an API wrapper for a service to grade arbitrary free-text responses. The goal is to provide a high-performance, scalable solution that can effectively help students learn. Feedback is a major part of this process.

Discussion forum

It’s a fairly simple discussion service that interacts with MongoDB. A server-side RoR application that supports the voting, nested comments, and instructors’ endorsements.

X-blocks

X-blocks are the fundamental units of the Open edX learning components. Any third party can write and develop a pristine kind of X-block that would enhance the Open edX learning functionality.

In addition to the ones discussed above, the DRC systems encapsulate all the other additional components that allow you to design the Avant-garde MOOC courses that may add value to your organization.

XQueue Service

It establishes an interface for the LMS to communicate with the external grader services. For example, when a learner submits a problem in the LMS, it is sent to XQueue in order for it to be processed further.

XServer

XServer accepts the student code submissions from the LMS and runs the code in AppArmor/Sandbox. This is to be used with the edX-platform and Xqueue.

edX ORA2

It allows for the assessment of open response problems on the edX platform. This is to be used with the edX-platform and Xqueue.

Discern

Discern allows anyone to use machine-learning-based automated textual classification as an API service. This is an API wrapper for a service to grade arbitrary free-text responses. The goal is to provide a high-performance, scalable solution that can effectively help students learn. Feedback is a major part of this process.

EASE

EASE (Enhanced AI Scoring Engine) is a library that allows for machine learning-based classification of textual content. This is useful for tasks such as scoring student essays. It provides functions that can score arbitrary free text and numeric predictors. The goal here is to provide a high-performance, scalable solution that can predict targets from the arbitrary values.

Edinsights

Open edX Insights is a complementary application to the Open edX platform that assists the authors in adjusting their content and making it dynamic for future iterations of the course to maintain an excellent learning experience over time.

Notifier

Notifier sends the daily digests of new content to the subscribed forum’s users, with a goal of eventually supporting the real-time and batched notifications of various types of content across various channels.

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