 Welcome back to learning analytics tool course. In this week, we will talk about test analytics. In last weeks, we saw what is three levels of analytics like a descriptive, diagnostics and pre-do analytics. This week we will talk about test analytics, it is not a type of one of them, but it is application of natural language processing on educational data. We will talk about that in this week. Next two weeks, we will talk about applications or advanced topics in learning analytics. So, the content for this weeks can be from Chapter 7 and 8 in the referral book in our course. So, mostly it is for content analytics, it is like a natural language processing is involved to analyze the test. And we have a lot of content in our learning environment, like our learning environment has content, the form of text or a video, a lot of content is available. Can we use natural language processing to do something? That is what about the content analytics. Let us see what is that. Before we go on to this week's course, when you hear the word natural language processing NLP, when you hear this word, what comes to your mind? Like what do you think about this? Do you know any applications of it? Have you heard this word? If you never hear the word, it is okay, please say you never hear the word, but if you have heard this word, what comes to your mind? Do you know where NLP is being applied? NLP is one of the key area of artificial intelligence, it tries to mimic, write and read sentences, understand sentences like a human do. So, what comes to your mind? Please write it down and after writing it down, let us in the video to continue. So, there are lot of things possible, lot of applications of NLP is there. Information extraction is the key, it is that you are given a lot of big chunk of test automatically identifying the information from the test. For example, the phone numbers, address, the person name, the person position, what are the characters in the particular book, everything information can be extracted. Once you have extracted the information, the key, subject, object, what is the relation between these things? We can construct a map or construct a new story, shorten the story, something is possible there. So, information extraction is the key, very important and challenging part two. And creating question and answer database, like based on chunk of data, like a lot of students interacting in forums, you can create a question and answers from that. A lot of customers is giving reviews or a lot of customers talking about particular product in the blogs, you can combine them and you can create a question and answer database, so that when a new customer wants to find the answer to something, they can check the question. This question can be easily picked up directly from the Q&A database, which is automatically curated from the existing content website. Or summarization, it is like, if you do not want to read a complete news article of say, it takes 5 minutes, you can summarize into a say, 10 sentences, takes only 30 seconds to read and understand the news article. So, here it is like information extraction and creating the sentences in a flow, logically flowing in a right sequence, right order. Translation, this we use a lot because we translate from English to other language or because a lot of native language we use. So, translation is very, very important application of NLP. You might have thought about chat board or personal assistance, nowadays any website, any service one website you open, there is a chat board coming in, you type something, it answers something. So, it is basically based on your keyword you are entering, automatically picks up the equivalent answer, something like that. This chat board is even getting more, nowadays say more intelligent nowadays, so that you can interact with the assistant like a CV or Alex Kortan or something like that. And speech to test, it is a very important part, the YouTube videos you might be watching or the videos you watch, their captions automatically coming out. It is all from speech to test. So, and there are a lot of training is happening for native language speakers, they are training on the person who is speaking. So, a lot of things are happening now to convert speech to test in English language. In social media, also in e-commerce media, if there is a product published, product is released in the e-commerce or product is launched. And a lot of people have comments like reviews, comments, the comment is positive or negative can be identified from the post. So, sentiment analysis possible. Suppose a movie is releasing, lot of tweets, a lot of people will tweet about that, a lot of tweets on about that movie is going, is the sentiment is positive or negative can be identified automatically by natural language processing, by identifying the polarity of the words, what the words means. Also, if you type a word, it automatically completes the sentence. You might have seen in a Google Gmail, when it start typing the word, it automatically completes the list of the word. So, that is also application of NLP and AI. So, let us see what is NLP application in education domain. So, why we are talking about NLP? So, we know NLP exist in the newspaper, news article, characterization or the G-Mates, spam filters. We saw the chat boards, speech to test, translations. But why we are talking about NLP in learning analytics? It is because the content we are giving is still text format. We are not like, we are not giving content in some other format. All the formats, contents is test or video. So, we need NLP. Can we use NLP to do some adaptation there? What we saw till now is log data, students interaction with the system. We never cared about the content we are giving to a student. What we thought till now is, based on the students interaction, the clicks, the traces, the answers, the performance to questions, performance to service, these data we are used to predict something to darkness or something is happening there. But can we use the content? Can we apply some analytics on the content? That is how the test analytics is for education. Let us talk about that in this link. Thank you.