[Music] welcome back to learning antics course what is data mining data mining refers to the process of transforming raw data into useful information there will be a lot of data as I mentioned in the first video the users have started creating lot of data in a social media or in the entertainment industry or health industry how to use this lot of data and transform that data into useful informations so that the company can give you recommendations or meaningful advertisements to you so to do that it's actually the data mining data mining is done by analyzing the data using pattern mining or process mining or predicting something or doing correlations regressions or developing some algorithms to predict which product you buy nest or which move you would like to watch nest for example this data mining is used in marketing for e-commerce it supports you which product to buy or it toys or add attachments like the targeted address based on your such behavior so your behavior in the browser or the content email can be used to provide your targeted advertisements or in a credit risk management for example whether based on the user's previous past behavior of how much loan yard or whether the user has paid loan on time all this data can be used to assess the credit rating and then week whether we should give out loan to the user or not the banks can take decisions using the data analysis or data mining and also that at our mining can be useful to analyze our students interact in a discussion forum for example in a MOOC course there'll be like thousands of users registered and a lot of them will be discussing in the MOOC forum can you use these discussions in the MOOC classrooms the data from the discussion forums to give a meaningful feedback to the learners this also can be done by data mining reminding the useful patterns in the discussion forums so what is educational data mining idiom or education data mining is you can put it very simply it's applying data mining algorithms on education from data from education domain or learners data for example data mining and you apply data mining on education data it's can be called as idiom very simple asset so idiom actually refers to the process designed for analysis of data from the learners environment to better understand students in the learning environment in which Taylor so here it's not talking about measuring collecting data reporting installed it stops or both process design for the analysis of data from the environment the learning environment can be classroom or a MOOC or technology enhanced learning environment to understand the students in that particular learning environment and to provide a adaptable content provide a better feedback in so that they can learn better so you would see that idiom as almost kind of a subset of learning analytics for example developing a learner model that includes students cognitive states to understand where the student will able to perform the test correctly where the student is able to complete this course this kind of information can go into a EDM fora using the learners data or which pedagogical support is most effective for example if a teacher teachers particular course using two different teaching strategies which pedagogical strategy or the teaching strategies most effective for example collecting in the pretest and the teaching method lot of data interaction data during the class this data can be useful to give the support and feedback to the learners for Institute's if you talk about EDM for the Institute's we can use the data like students usage of resources how much student used resources like books available or LMS is like a Moodle the student uploaded assignments on time students engagement in the class all this data can be collected and we can apply data mining on that and we can model the students interaction behavior in that particular video resources or the Institute resources and Institute can take decision whether we should put more money on the particular source or not so EDM in the sense applying a data mining on educational data also can be useful to develop the learner model to understand the students learning in the learning environment to provide some feedback or to make some decisions at a different levels where is this other world called academic context so if academic analytics helps Institute's address the student success and accountability while fulfilling their academic missions academic analytics help institutions to address student success and accountability with while fulfilling their academic missions or simply academic ethics is learning analytics are played at institutional level or the university level or the regional level or the national level for example analyzing the data from learner management system like a model for the Institute level saying that how teachers interact with the students whether the teachers present in the class all the time or the store the teacher students interaction in Moodle all these details can be used by Institute to make a decision about the teaching strategy they are the hiring principles or the LMS data can be useful to predict whether to run a course nice chill or not so the academic analytics is similar to business intelligence so what happens and lasts for years back from 2000 say 16 onwards how people don't use the word academic analytics instead they call it as a business intelligence as they use it in other domains like business intelligence is a very common and popular word another popular word in other domains like health finance now they call the same word business indigence in academic Institute's also called academic context previously academic antics you can think of applying data not just you know city level also the district level the government officials can use this data predict whether particular school is doing good or bad all these things can be done for example which course will get enough registrations this is for the Institute or which school in the district needs more attention like the school is not performing well and why it's not performing well and what are the factors is affecting its performance so do we need more attention or can you predict which school will not perform in nest public exam those kind of information can be looked at academic antics or business integers so let's start with the activity for this video you learned about what is academic antics so which of the below is least important for academic antics or which of the below is not considered as academic ionics for example attendance of teachers or past percentage of student in a course s or performance of school a in a city be like school in a particular city our graduation rate of students in a particular University you can pass this video think about your answer write down your answer after I didn't done you can resume the video to continue past percentage of a particular course is important for teachers than Institute's it can be considered academic context for the Institute's also but given other three options like attendance of teachers which means the teachers of all the courses or performance of a school day in a city be like we are comparing school performance among all other schools our graduation rate for students in a particular course over the years we think first percentage is not as much as important for academia antics compared to it is important for the teacher so we can classify this also learning antics so if I put past percentage of a student in a Cosi X it's definitely a learning analytics but given these other three options even this can be considered with learning antics so what is the difference between academic analytics and learning analytics so academic analytics provides support to operation and financial decision-making for the stakeholders such as management executives the focus is so on business of the institution like business of the institutions our focus is on how to improve the education develop a particular district what are the new methods to implement to improve the education of the country or something like that focus is very high level whereas the learning analytics the achievement of a specific learning goal or the students performance in a particular score students completing the particular goal is very very important here the focus is on student the student who is learning whether the student learns or not so the stakeholders are can be students instructors also the searchers also can be the Institute management but mostly it is for instructors and learner's so the pup the primary purpose the focus is on student and out help how can we help them to learn better how can we help them to achieve the learning goal so for us over take about a lien a diem is this so we can't see la an idiom of interrelated over windows cause we will use the term learning antics for all this EDM and la related topics so we use one word called learning analytics for us the academic analytics is a area which we don't touch it's a kind of gray area we might talk about that field very rarely but the focus of this course is only on learning analytics and we might call the techniques algorithms an idiom also as Elliot this is our tech for this course so in this video we talked about what is educational data mining also what is academic analytics and you might have understood the difference between LA and academic antics in this course as I mentioned EDM on LA or same for us and also we used the term called la going forward and you not talk or focus on academic antics in this course thank you [Music]