 In this learning dialogue, we will talk about descriptive analytics, descriptive analytics or data dashboard or dashboard analytics, data dashboard is representing the complex data in a user friendly graphics such as charts, graphs, pie charts or interactive graphs or some comparative graphs. The term dashboard is actually the pilot or the driver see when they drive the vehicle in front of them is called dashboard. In a data dashboard, we collect data from the students or the users or the employees based on the domain and we represent the data in a dashboard for the researchers, learners or teachers or the other stakeholders. So, in a learning analytics, we will talk about data dashboard and how this learning data is used to represent in dashboard. So, dashboard is very important for researchers to extract the influences, to extract the insights, to identify what happened is more important to look at the data and visually so that they can compare to data and get new influences from the data. So, this is the first step when you do the research on data that is collecting data and showing it in a digital format or graphics format. The dashboard is also used to communicate the insights or something findings the researchers found to the other stakeholders like a teachers or the students. In business intelligent tool, dashboard is very important key metric. The examples of dashboard can be seen everywhere. You might have seen the dashboard in Amazon rating of the product or in a movie reviews where in Amazon, you see number of users rated 5 star for a particular product, number of user rated 4 star then user complies to bar chart will be shown or in a movie reviews you can see how many users reviewed. This movie what is the ratings of this with the stars. Dashboard analytics is very important for marketing, health sector and finance. Also in learning analytics for researchers it is very important to understand what is their data. However, in dashboard analytics or descriptive analytics the main question is what data to show and why we need to show this data. So, what data you want to look at is that number of students passed in last year or what is the past percentage of students in last 3 years and what data you want to show and why you want to see also who is the audience are we showing this data to teacher then you need to find a grain data. If you are showing this data to a administrative of the university or college then you need a more coarse grain or abstract level data. Showing that there are like 30% of students passed all the exams few students did not pass the exam something like that. So, we should be considering these questions when we are thinking about creating a dashboard analytics or descriptive analytics that is what data show and why you have to show this data who is our audience and we decide what is the visualization technique you will be using it to show the data. In this activity consider you have a technology enhance learning environment like metal we saw in last class or online learning environment MOOC or YouTube videos you have a develop the environment also you have a lot of data collected from these environments what data is important in this environment to represent in the dashboard given that you have access to collect data in these two environments like a tell or online learning environment which data will collect to show it in a dashboard you can pass this video I will answer these questions after completing a task you can resume to continue in general for dashboard this data is very important for example performance in the test if you are talking about the students performance in a class or performance in the online environment or performance in the end semester performance in some other learning environment this performance in the test pre-test post-test or performance within the environment is very important to show the other important thing is time spent on each task is it the task within the learning environment is specific tasks like how much time a student spent on simulator or how much time students reading a particular page or what is the overall time spent on the task like the students spend 80 minutes for particular task and very less time for task 2 or you might say the student is focusing mostly reading chapter 1 and 2 lot of time compared to chapter 3 and 4 in the exams so time spent is important time spent can be observed from the finite end level to the course and higher level also you have to note note that what are the resource they use the are they using the simulator calculator or reading some resources which video they read which video they watch or how long they watch the video how many times they watch the video what is speed of the watching the video all this information can be collected it is important to show that the student is all the learner is actually using this resources to read multiple times and they are reading for this much time so if you have time and the resource use makes a good combination of data to represent in the dash bottlenecks and the other important point is the content developed by the users for example in a discussion forums how many posts the student is posting how many forums the student is creating or in a model is the student is submitting assignment on time how many assignments the student submitted or how many questions the student asked in the discussion forum so that you can identify that the student's engagement in the online learning environment so the question is okay we can collect all this information from the learning environments like online or the personalized learning environment but why we need visualization as you mentioned earlier this is the form to show a complex data in a user friendly manner or in a graphic manner like pictures graphs or line charts bar charts which is actually helping us to understand what is happened in the data what is happened in the learning environment so what questions can ask for example what is the student past percentage in a class over years so you can simply show a graph saying that the past percentage over years is this so that we can look at it over in the class up compared to last three years last year class past percentage might be less something like information can come out or you want to know what is the attendance in a class for last 30 working days is the attendance is reducing or is attendance is constant for last 30 days or there is a huge variance in the attendance if it is why time spent on each resource page is also another important key factor for example if you have five resources you can represent the average time spent by all students on each resource that makes a more insights for the researcher or you can simply present the student faculty ratio in a class a student faculty ratio is 1 is to 15 in class b it is 1 is to 10 something like that then you can compare if the class b student faculty ratio is better is the output of performance is better you can compare those things in a correlation or you can go ahead and see how many students enrolled in the course or how many students enrolled or downloaded the particular app those kind of information can be represented in the dashboard why these daily questions are important this course is important because this will help you to answer some research question for example student faculty ratio if there are two classes if the class b has a very better student faculty ratio we expert their learner performance is better than is it true or not we can do the correlation analysis the first step is looking at that data by showing this graph so that we can start asking questions if the performance is same you can understand there is no correlation so you may not ask this particular such question let us assume that you are collected data from a classroom for last few years this is same as the questions we are trying to answer for last two weeks so you are collected data from a classroom for last few years what research question would you like to answer from the data think of it also how will you present the data to answer your such questions so you have to come up with the one or two such questions you want to ask from the classroom data which was not listed in the previous slide and how do you want to represent you want to represent in a bar graph or pie chart or comparative chart or some other new methods if you have decided the question you should know from where we can collect this data the data to answer the question for example I want to know past percentage over three years the resource for this particular data is performance in a semester exams or the midterm exams or some other exams you conducted so similarly if you have decided a question first you should think from where I can collect data to answer this question listed down first then you have to clean up the data like is there any value missed or is there any outlayer most like out of under students there some data was like outlayer say very less mark or really high mark you might need to ignore them because they might be high performer we might need to look at the data which is where most students mark is distributed so you have to consider the outlayer or you have to also think about the missed values there are some students data might not have it so you can ignore that particular data or you can recollect the data if you want so data pre-processing is very important manually checking the data and make sure the data is correct