{"product_id":"9783319344997","title":"Studies in Computational Intelligence: Applications and Trends","description":"\u003ch1\u003eStudies in Computational Intelligence: Applications and Trends\u003c\/h1\u003e \u003ch2\u003ePeña-Ayala, Alejandro\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis book is devoted to the \u003ci\u003eEducational Data Mining\u003c\/i\u003e arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows:\u003c\/p\u003e\u003cp\u003e·     \u003ci\u003eProfile\u003c\/i\u003e: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education.\u003c\/p\u003e\u003cp\u003e·     \u003ci\u003eStudent modeling\u003c\/i\u003e: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click.\u003c\/p\u003e\u003cp\u003e·     \u003ci\u003eAssessment\u003c\/i\u003e: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data.\u003c\/p\u003e\u003cp\u003e·     \u003ci\u003eTrends\u003c\/i\u003e: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks.\u003c\/p\u003e\u003cp\u003eThis volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledgeand find targets for future work in the field of educational data mining. \u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2016-08-23\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9783319344997\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-319-02738-8\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 468\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":45378804383884,"sku":"9783319344997","price":152.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783319344997.jpg?v=1775007515","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783319344997","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}