 In this learning data, we will discuss MOOCs analytics dashboard, IIT Bombay X or IIT Bombay online platform to offer the MOOCs, it is called IIT Bombay X, it is the platform by edX. Last week, we saw the data from IIT Bombay X platform, we saw the raw data we had collected. This week, we will see how this data is used for the dashboard analytics. The edX platform also offers open edX insights that provides the analytics based on the data collected from edX platform MOOCs and it reduces the insights by using open edX insights platform. Before showing the MOOCs analytics dashboard, I would like you to think about this activity. So, what data important to show in the dashboard from the IIT Bombay X MOOC and how do you represent? You can pass this video, I will answer these questions. After that, you can resume the video to continue. Based on the data we collected, we shown in the last class, we can talk about following set of data. Please remember, this following data of data is for the edX platform. If you are talking about Coursera platform or NPTEL platform, the collection, data collection, the data you collect might be totally different. You can collect even more data. But these are the general data collected in a MOOC platforms. One is enrolment. How many users enrol in your course? What is the enrolment status over the weeks? Are they continuing or are they dropping out? The next one is engagement. Are they engaged or how they engage with the video? And the performance in the LEDs, LBDs or some other forums or the post-test, pre-test or certificate course or assignments. Also, the engagement is the learner engagement is more or less. We look at the MOOCs insights from the insights.ITBombayX.in. This side, I have restricted access. So, I am going to log into my email ID, then I will show the insights from the ITBombayX MOOC courses. We are looking at the ITBombay edX insights webpage. We are talking about a course called Pedagogy for Effective Use of ICT for School Teachers. This analytics is only for this particular course. There are four type of things like enrolments, engagement, performance and learners. If you talk about engagement, enrolments, you will have the value like activity, demographics and good geography. So, daily learner enrolment over the period of time. The enrolment is less just because the students do not enrol and they can take a course directly. It is shown using the stack chart. Here you can see the users age, the education, the gender. However, this data is optional. If the user enters this data, then only it will be displayed. Otherwise, it will not be displayed. The more importantly, the eye open edX insights offers you also the tabular form of data. Data visualization is not just showing the data in a graphics. Also, you should have a data so that users can use those data. When you look at the geography, there are most participants from India or there are few participants from Tanzania and there are one participant from United States. Let us look at the engagement. Here you can see there are lot of active users initially. The course is only offered for four weeks. So, there are lot of active users on a first week and the active users was reduced and there are some active users continued. Then number of active users dropped after fourth week gradually. So, the active learners is shown in this card chart. Also, this chart indicates how many problems they tried, how many problems they tried to answer it. And this green color indicates they watched the video. Active users, they logged into video, they looked at the page or combination of these two. This represents the active users. But really speaking, how many videos they watched. The students who are watching the video is gradually reduced over the weeks. If you look at the weeks video data, how many videos has been watched by the user for over the week. For the module one, average completion time is 73 percent of participants or the students enrolled in the course completed watching the video. It is a very good retention rate. So, this shows that for each module, that is a four weeks module, this is a pre-course module. For each module, what is the percentage of users watched this particular video? As I mentioned, in order to collect this kind of data, we need to collect each users watching time. Then we need to compute the average, then represent the data in such a format, a stack chart format. Let us look at the performance. There is only one performance, knowledge quiz and reflection quiz and assimilation quiz and resource creation assignment. There are like a four different performance and each performance has the own weightage of marks. And the students performance in each of this is shown here. Here, we have seen the data. We have seen the data of the learners, the lead of who is doing the course and how they interact with the video and things. From this, you can ask a lot of these questions. So, many learners are in my course. This can be answered by looking at the particular chart. So, these are the questions you want to ask from the data which can be viewed directly from the graphs. So, the researchers first start with lot of data. Then they want to ask how many users my course, how many users watched this particular video. If the video retention rate is less for particular module, you want to introspect to why that particular video has less number of retention rate. That means, why that particular module or particular video has less people completing full video, why they drop out in between. The topic may be easy or the content is too tough, we do not know. We need to understand what happened in that particular video content. In order to do that, we need to introspect and look at the data and why the users are dropping there or which many they drop, what is the many they dropped, how far they watched. This will give you the diagnostic analytics to understand the data why the student is dropping. So, the first step in data analytics is that trying to collect data, then show the data in a visualization or data visualization.