 In this week we will discuss about data collection and ethics and privacy in learning ethics. As I mentioned in my first class, this course we are offering using learner centric MOOC model. You might be wondering what is learner centric MOOC model or why you do not get two and a half hours of video to watch in a first week, because we are not only delivering the videos in this course, instead each activity or each video lecture is called the learning deluxe. This is the only place you will watch video and you will do some activity. Apart from this, you will learn from answering focus questions that is asked in the MOOC and also discussion in the forums. So we expect you to actively participate in this focus questions and the activities listed in the forums in every week and discuss with your peers and learn from your peers. Let us begin with activity. In last class, we mentioned that you are assessed to data. Consider you are a teacher or researcher in a classroom environment, similar to the example we given in the last class. What data will you like to collect and how do you want to collect data in a classroom environment? You can pause this video, write down your answer, after completing your activity, you can resume this video to continue. You might have thought you can collect the performance data, profile data like mentioned in the last classes. Then performance data, what are the performance data you are compiling? It is like a mid-term data or semester exam data. If it is a semester exam data, you might be able to collect, say scores and students a response in each question. What is the score in each questions? Also in a mid-term data that you have access to it and you have access to it in the question paper setup and also you all know what response the student expected. You can collect more richer data saying that which question the student responded, which questions the students had a difficult to in it. So you can collect data in the performance from mid-term and exam scores. Also the attendance to make sure that how many students attend in the class. If this course have associated lab activity, you can also collect the performance in the lab, whether the student able to complete the lab assignments in time or they take more time. Also the engagement in the class, it is not just attendance, how much the students actively participating in the class, is he discussing with his peers, is he able to engage in the class as doubts and interact with the teachers. Apart from this, if you have given a course assignment or course projection in your course, you can access the student's performance in the projects. Also if your university or college have a LCM like Moodle or Blackboard, you can access the data in Moodle or Blackboard also. Students submit assignments in Moodle and you can check the participation in Moodle chat forums and forum data. Apart from this, these data you can collect from the students interaction with some system like the performance in the exam or engagement in the class or activity in the Moodle. Apart from this you can also collect data by human observation. Studying like a student's motivation and effect. If your class length is say minimum like 40 to 50, then you can observe what is the overall effect of this class. If lot of students get confused when you teach, then you can change your teaching approach. If the lot of students got bored, you might give some other assignments to make them active. Or the students look less motivated or not interested to learn, then you can change the activity. So you can collect these kind of information also for the learning analytics.