Overview

This book is devoted to the Educational Data Mining 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: ·     Profile: 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. ·     Student modeling: 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. ·     Assessment: 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. ·     Trends: 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. This 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.

Full Product Details

Author:   Alejandro Peña-Ayala
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   Softcover reprint of the original 1st ed. 2014
Volume:   524
Dimensions:   Width: 15.50cm , Height: 2.50cm , Length: 23.50cm
Weight:   7.314kg
ISBN:  

9783319344997

ISBN 10:   3319344994
Pages:   468
Publication Date:   23 August 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Part I: Profile 1 Which Contribution Does EDM Provide to Computer Based Learning Environments?     Nabila Bousbia, Idriss Belamri 2 A Survey on Pre-processing Educational Data     Cristóbal Romero, José Raúl Romero, Sebastián Ventura 3 How Educational Data Mining Empowers Government Policies to Re-form Education: The Mexican Case Study     Alejandro Peña-Ayala, Leonor Cárdenas   Part II: Student Modeling 4 Modeling Student Performance in Higher Education Using Data Mining     Huseyin Guruler, Ayhan Istanbullu 5 Using Data Mining Techniques to Detect the Personality of Players in an Educational Game     Fazel Keshtkar, Candice Burkett, Haiying Li, Arthur C. Graesser 6 Students’ Performance Prediction using Multi-Channel Decision Fusion     H. Moradi, S. Abbas Moradi, L. Kashani 7 Predicting Student Performance from Combined Data Sources     Annika Wolff, Zdenek Zdrahal, Drahomira Herrmannova, Petr Knoth 8 Predicting Learner Answers Correctness Through Eye Movements With Random Forest     Alper Bayazit, Petek Askar, Erdal Cosgun   Part III: Assessment 9 Mining Domain Knowledge for CoherenceAssessment of Students Proposal Drafts     Samuel González López, Aurelio López-López 10 Adaptive Testing in Programming Courses Based on Educational Data Mining Techniques      Vladimir Ivančević, Marko Knežević, Bojan Pušić, Ivan Luković 11 Plan Recognition and Visualization in Exploratory Learning Environments       Ofra Amir, Kobi Gal, David Yaron, Michael Karabinos, Robert Bel-ford 12 Dependency of Test Items from Students' Response Data       Xiaoxun Sun   Part IV : Trends 13 Mining Texts, Learner Productions and Strategies with ReaderBench       Mihai Dascalu, Philippe Dessus, Maryse Bianco, Stefan Trausan-Matu, Aurélie Nardy 14 Maximizing the Value of Student Ratings Through Data Mining       Kathryn Gates, Dawn Wilkins, Sumali Conlon, Susan Mossing, Mau-rice Eftink 15 Data Mining and Social Network Analysis in the Educational Field: An Application for Non-expert Users       Diego García-Saiz, Camilo Palazuelos, Marta Zorrilla 16 Collaborative Learning of Students in Online Discussion Forums: A Social Network Analysis Perspective       Reihaneh Rabbany, Samira ElAtia, Mansoureh Takaffoli, Osmar R. Zaïane

Reviews

From the book reviews: This book delivers on its promise to bring together the essence of educational data mining, both in terms of principle and practice. It deserves a place on the reading shelf of any researcher interested in advancing educational goals using advanced techniques and methodologies. (Computing Reviews, July, 2014)

From the book reviews: This book delivers on its promise to bring together the essence of educational data mining, both in terms of principle and practice. It deserves a place on the reading shelf of any researcher interested in advancing educational goals using advanced techniques and methodologies. (Computing Reviews, July, 2014)

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