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The paper reviews works where these techniques solve specific educational issues and provides a classification across the scenarios in which they are applied.",{"@graph":14,"@context":72},[15,34,55],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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purpose of Educational Data Mining (EDM)?","Question",{"text":62,"@type":63},"EDM aims to develop methods to analyze large educational datasets to better understand students’ behavior, interests, and results, supporting improved learning and decision-making.","Answer",{"name":65,"@type":60,"acceptedAnswer":66},"What stages are commonly used to implement a data mining project in this paper?",{"text":67,"@type":63},"The paper describes four phases: filtering data, selecting variables, extracting knowledge, and interpreting and evaluating results.",{"name":69,"@type":60,"acceptedAnswer":70},"Which techniques does the paper mention for education-related data analysis?",{"text":71,"@type":63},"It highlights data mining methods such as clustering and decision trees, as part of knowledge discovery for educational 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\n[andres13@gmail.com](andres13@gmail.com)  \nInstitución Universitaria Politécnico Grancolombiano  \nLuis Gabriel Moreno Sandoval  \n[gabrielmoreno10@gmail.com](gabrielmoreno10@gmail.com)  \nInstitución Universitaria Politécnico Grancolombiano  \nMartha Janneth Salinas Suárez  \n[majasalinas@gmail.com](majasalinas@gmail.com)  \nCorporación Universitaria Minuto de Dios  \nAbstract  \nEducational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students’behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this to address different educational problems have been used. The aim of this paper is to present a review of the works in which data mining techniques were used to solve specific problems of education and to do a classification associated to diverse scenarios in which they have been applied.  \nKeywords  \nEducational data mining; Data mining; Clustering; Decision trees; Knowledge discovery.  \nA. Villanueva, L.G. Moreno & M.J. Salinas  \nDigital Education Review-Number 33, June 2018-[http://greav.ub.edu/der/](http://greav.ub.edu/der/)  \n235  \nI. Introduction  \nDue to the great contributions that technology offers to all disciplines today, it could be explained that all stages of life are changing, especially the way we communicate and the barriers that have collapsed thanks to Internet and the amount of generated and stored data in different information systems . Because of all of this, is not wrong to say that the world evolves adaptively. In this change making decisions is an activity that is not expected, especially when these decisions are determinant for the future of organizations .  \nIn all educational environments, one of the main objectives is to ensure that learning processes allow to understand students and their learning paths. This is where Data Mining Educational or Educational Data Mining (EDM) for its acronym in English, provide a fundamental value to educational institutions and to all entities that support different processes in learning activities .  \nThis work seeks to present in a general way the major components of EDM, as well as to illustrate the context of EDM and its growth since 2008; Moreover it will present the current state of the use of data mining techniques in the resolution or analysis of problems that occur in educational settings . We also present which of them has been used in particular domains of education; Finally, the paper analyzes how was the behavior of the different techniques of data mining in the past two decades and what are the current trends of EDM, looking for providing elements to support decision-making what techniques of data mining can be used in particular situations .  \nII. Data Mining  \nData mining is a set of techniques and procedures that can be developed from various data sources such as data warehouses or relational databases, to flat files without formats that are made from this predictive analysis using statistical study techniques to predict or anticipate statistical measures of certainty based on existing facts . According to Fayyad, data mining \"is a non-trivial process of valid identification novel, potentially useful and understandable of comprehensible patterns that are hidden in the data\" (R, Sánchez-Guzmán A, & García, 2013) . Data mining is also seen as the evolution of information technology (Jiawei & Kamber, 2001), this largely leveraged by the growth that internet has taken great importance in recent years (Society, 2014)(MINTIC, 2015) .  \nData mining is a multidisciplinary field that allows to obtain relevant information from large amounts of data at the confluence among other areas: artificial intelligence, statistics, databasesand info","cbCaigS6Z8oZ3OnM","https://ap.wps.com/l/cbCaigS6Z8oZ3OnM","pdf",895713,32,"English","# Introduction\n# Data Mining\n# Implementing a Data Mining Project\n# Educational Data Mining","[{\"question\":\"What is the purpose of Educational Data Mining (EDM)?\",\"answer\":\"EDM aims to develop methods to analyze large educational datasets to better understand students’ behavior, interests, and results, supporting improved learning and decision-making.\"},{\"question\":\"What stages are commonly used to implement a data mining project in this paper?\",\"answer\":\"The paper describes four phases: filtering data, selecting variables, extracting knowledge, and interpreting and evaluating results.\"},{\"question\":\"Which techniques does the paper mention for education-related data analysis?\",\"answer\":\"It highlights data mining methods such as clustering and decision trees, as part of knowledge discovery for educational settings.\"}]","Data mining techniques applied in educational environments - Literature review | PDF",81]