 Welcome to this module on quality without exclusivity, a set of lectures on open and distance learning. In this module, we will learn about learning analytics. We have already seen process issues related to a MOOC, technology and platforms, a small segment on MOOCs. We are going to talk of standards and a roadmap to MOOCs in subsequent talks. So, what is learning analytics? It is all about measurement and analyzing the data that you have collected. The objective of course, is to improve effectiveness and optimize the learning and the environment in which it occurs. So, I have taken this definition from a conference which has been held in 2011. The first learning analytics conference happened in 2011. So, you can see it is the whole area is quite new, but it is very, very active at this point of time, because this is expected to give a handle on improving our quality of teaching and learning. So, this learning analytics is nothing new actually. We all know about it. We used to take feedback during the course, like we would monitor the attendance, how many students are coming or not, the participation in the class. We do not record it, but mentally we know who is active and who is not. We have access to information like data from the library. If I put a book in the textbook section, I can go and check if students are checking the book out and reading or not. That is another example of the kind of feedback we take. And of course, performance in the exams is the ultimate feedback which will tell me whether the students are learning what is being taught or not. We also take feedback at the end of the course. Typically, the popular question and most important question as the instructor taught well. So, this is all part of analytics. The problem with this is the data collected is not comprehensive. It is not complete. Very often we miss out monitoring certain aspects of the course. It is not taken seriously by the student or the teacher. And often it comes late in the course to make any mid course corrections. So, what does learning analytics do? The situation is when the teaching is and learning is online, we have more opportunities. Because the student is interacting with the system is logging into the learning management system, let us say. And listening to the videos and you can figure out how many times he is watching the video. You can figure out whether he has watched the video at all or not and at what frequency he is watching the video. So, these are the kind of opportunities you get when you have the ability to monitor the interaction between the student and the content. So, what are the objectives of learning exercise of a learning analytics module? Essentially, we want to improve teaching. We want teaching to be more effective. And we would like to retain the student. Retain the student not just in terms of interest in the particular course, but over a degree program the student may show signs of dropping off and we need to be aware to that. We would like the student to complete the program. So, what the analytics module will help us do is basically notify the instructor before the situation gets worse. So, one assumes that the student gets disinterested or got into some problems somewhere along the line. And it reflects in his interaction in the class. Now, the class is online mind you. And so, I should be able to keep track of the decreasing interest or decreasing interaction in the class and the program per se. There are multiple courses then one can actually see the deterioration in the in the connect with the program. And then the software possibly can predict look this trend is alarming be careful. So, that is what analytics is all about. So, for whom is this learning analytics? It is for the teacher, it is for the student and of course, for the institute. What are the kind of measurements that are made? The time spent by the student in engaging with the content number of times he logs in the mouse clicks. This is an indication of how active the student is as he turned the video play on and has gone to sleep or not is possibly can be checked out with this how active is the student. The kind of resources that are there that are being accessed the number of artifacts produced in terms of assignments that are done submitted by the student and in terms of quizzes that are attempted and extra reading that the student has done and so on. And of course, the number of finished assignments. These are the typical measurements that one does and one can do quite easily if your analytics is online. So, a case study for learning analytics which is turned out to be very very successful in terms of its effectiveness is the module called course signals which was started at Purdue University. It was essentially to detect early warning signs that may appear in the in the course. Of a student study and it provides real time feedback to the instructor and to the administrators monitoring starts quite early in the program as soon as in the second week of the course. So, right from the very beginning of the semester the instructor and the teacher is tracking the student. And of course, the feedback is frequent and ongoing and it is said this program by Purdue University has been actually very effective and it has helped reduce dropout rates in the program. So, that is all about analytics essentially it is all about tracking the student. It is a known thing, but now we have been doing it all along, but now since the whole interaction is automated we can do it better and we can use technologies like big data which will do mining and association discovery and then make some predictions of an impending unacceptable situation. Thank you.