- Shopping Bag ( 0 items )
Other sellers (Hardcover)
-
All (5) from $74.09
-
New (3) from $112.61
-
Used (2) from $74.09
More About This Textbook
Overview
Researchers at the Forefront of the Field Discuss Essential Topics and the Latest Advances
Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed.
With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It brings the educational and data mining communities together, helping education experts understand what types of questions EDM can address and helping data miners understand what types of questions are important to educational design and educational decision making.
Features
Covers novel EDM methods, including those that link psychometrics with EDM
Presents detailed case studies that show how the methods are applied using real educational data
Discusses the influence of open data repositories
Includes contributions from a wide variety of prominent international researchers
Encouraging readers to integrate EDM into their research and practice, this timely handbook offers a broad, accessible treatment of essential EDM techniques and applications. It provides an excellent first step for newcomers to the EDM community and for active researchers to keep abreast of recent developments in the field.
Editorial Reviews
From the Publisher
Computer scientists review the current state in using large-scale educational data sets to understand learning better and to provide information about the learning process. …—SciTech Book News, February 2011
Product Details
Meet the Author
Cristóbal Romero is an associate professor in the Department of Computer Science at the University of Córdoba in Spain. Dr. Romero is a member of the International Working Group on Educational Data Mining and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests include the application of artificial intelligence and data mining techniques to education and e-learning systems.
Sebastián Ventura is an associate professor in the Department of Computer Science at the University of Córdoba in Spain. Dr. Ventura has been a reviewer for User Modelling and User Adapted Interaction, Information Sciences, and Soft Computing and was conference co-chair of the Second International Conference on Educational Data Mining. His research interests encompass machine learning, data mining, and their applications as well as the application of KDD techniques to e-learning.
Mykola Pechenizkiy is an assistant professor in the Department of Computer Science at Eindhoven University of Technology in the Netherlands. Dr. Pechenizkiy has been involved in the organization of workshops, special tracks, and conferences on applications of data mining in medicine, industry, and education. He is conference co-chair of the Fourth International Conference on Educational Data Mining. His research is focused on knowledge discovery, data mining, machine learning, and their applications.
Ryan Baker is an assistant professor of psychology and the learning sciences in the Department of Social Science and Policy Studies, with a collaborative appointment in computer science, at Worcester Polytechnic Institute in Massachusetts. An associate editor of the Journal of Educational Data Mining, Dr. Baker was program co-chair of the First International Conference on Educational Data Mining and conference chair of the Third International Conference on Educational Data Mining. His research is at the intersection of educational data mining, machine learning, human–computer interaction, and educational psychology.
Table of Contents
Preface xi
Editors xv
Contributors xvii
1 Introduction Cristóbal Romero Sebastián Ventura Mykola Pechenizkiy Ryan S. J. d. Baker 1
Part I Basic Techniques, Surveys and Tutorials
2 Visualization in Educational Environments Riccardo Mazza 9
3 Basics of Statistical Analysis of Interactions Data from Web-Based Learning Environments Judy Sheard 27
4 A Data Repository for the EDM Community: The PSLC DataShop Kenneth R. Koedinger Ryan S. J. d. Baker Kyle Cunningham Alida Skogsholm Brett Leber John Stamper 43
5 Classifiers for Educational Data Mining Wilhelmiina Hämäläinen Mikko Vinni 57
6 Clustering Educational Data Alfredo Vellido Félix Castro Àngela Nebot 75
7 Association Rule Mining in Learning Management Systems Enrique García Cristóbal Romero Sebastián Ventura Carlos de Castro Toon Calders 93
8 Sequential Pattern Analysis of Learning Logs: Methodology and Applications Mingming Zhou Yabo Xu John C. Nesbit Philip H. Winne 107
9 Process Mining from Educational Data Nikola Trcka Mykola Pechenizkiy Wil van der Aalst 123
10 Modeling Hierarchy and Dependence among Task Responses in Educational Data Mining Brian W. Junker 143
Part II Case Studies
11 Novel Derivation and Application of Skill Matrices: The q-Matrix Method Tiffany Barnes 159
12 Educational Data Mining to Support Group Work in Software Development Projects Judy Kay Irena Koprinska Kalina Yacef 173
13 Multi-Instance Learning versus Single-Instance Learning for Predicting the Student's Performance Amelia Zafra Cristóbal Romero Sebastián Ventura 187
14 A Response-Time Model for Bottom-Out Hints as Worked Examples Benjamin Shih Kenneth R. Koedinger Richard Scheines 201
15 Automatic Recognition of Learner Types in Exploratory Learning Environments Saleema Amershi Cristina Conati 213
16 Modeling Affect by Mining Students' Interactions within Learning Environments Manolis Mavrikis Sidney D'Mello Kaska Porayska-Pomsta Mihaela Cocea Art Graesser 231
17 Measuring Correlation of Strong Symmetric Association Rules in Educational Data Agathe Merceron Kalina Yacef 245
18 Data Mining for Contextual Educational Recommendation and Evaluation Strategies Tiffany Y. Tang Gordon G. McCalla 257
19 Link Recommendation in E-Learning Systems Based on Content-Based Student Profiles Daniela Godoy Analía Amandi 273
20 Log-Based Assessment of Motivation in Online Learning Arnon Hershkovitz Rafi Nachmias 287
21 Mining Student Discussions for Profiling Participation and Scaffolding Learning Jihie Kim Erin Shaw Sujith Ravi 299
22 Analysis of Log Data from a Web-Based Learning Environment: A Case Study Judy Sheard 311
23 Bayesian Networks and Linear Regression Models of Students' Goals, Moods, and Emotions Ivon Arroyo David G. Cooper Winslow Burleson Beverly P. Woolf 323
24 Capturing and Analyzing Student Behavior in a Virtual Learning Environment: A Case Study on Usage of Library Resources David Masip Julià Minguillón Enric Mor 339
25 Anticipating Students' Failure As Soon As Possible Cláudia Antunes 353
26 Using Decision Trees for Improving AEH Courses Javier Bravo César Vialardi Alvaro Ortigosa 365
27 Validation Issues in Educational Data Mining: The Case of HTML-Tutor and iHelp Mihaela Cocea Stephan Weibelzahl 377
28 Lessons from Project LISTEN's Session Browser Jack Mostow Joseph E. Beck Andrew Cuneo Evandro Gouvea Cecily Heiner Octavio Juarez 389
29 Using Fine-Grained Skill Models to Fit Student Performance with Bayesian Networks Zachary A. Pardos Neil T. Heffernan Brigham S. Anderson Cristina L. Heffernan 417
30 Mining for Patterns of Incorrect Response in Diagnostic Assessment Data Tara M. Madhyastha Earl Hunt 427
31 Machine-Learning Assessment of Students' Behavior within Interactive Learning Environments Manolis Mavrikis 441
32 Learning Procedural Knowledge from User Solutions to III-Defined Tasks in a Simulated Robotic Manipulator Philippe Fournier-Viger Roger Nkambou Engelbert Mephu Nguifo 451
33 Using Markov Decision Processes for Automatic Hint Generation Tiffany Barnes John Stamper Marvin Croy 467
34 Data Mining Learning Objects Manuel E. Prieto Alfredo Zapata Victor H. Menendez 481
35 An Adaptive Bayesian Student Model for Discovering the Student's Learning Style and Preferences Cristina Carmona Gladys Castillo Eva Millán 493
Index 505