Computer Science Education Research


Book Description

This book provides an overview of how to approach computer science education research from a pragmatic perspective. It represents the diversity of traditions and approaches inherent in this interdisciplinary area, while also providing a structure within which to make sense of that diversity. It provides multiple 'entry points'- to literature, to methods, to topics Part One, 'The Field and the Endeavor', frames the nature and conduct of research in computer science education. Part Two, 'Perspectives and Approaches', provides a number of grounded chapters on particular topics or themes, written by experts in each domain. These chapters cover the following topics: * design * novice misconceptions * programming environments for novices * algorithm visualisation * a schema theory view on learning to program * critical theory as a theoretical approach to computer science education research Juxtaposed and taken together, these chapters indicate just how varied the perspectives and research approaches can be. These chapters, too, act as entry points, with illustrations drawn from published work.




Learner-Centered Design of Computing Education


Book Description

Computing education is in enormous demand. Many students (both children and adult) are realizing that they will need programming in the future. This book presents the argument that they are not all going to use programming in the same way and for the same purposes. What do we mean when we talk about teaching everyone to program? When we target a broad audience, should we have the same goals as computer science education for professional software developers? How do we design computing education that works for everyone? This book proposes use of a learner-centered design approach to create computing education for a broad audience. It considers several reasons for teaching computing to everyone and how the different reasons lead to different choices about learning goals and teaching methods. The book reviews the history of the idea that programming isn't just for the professional software developer. It uses research studies on teaching computing in liberal arts programs, to graphic designers, to high school teachers, in order to explore the idea that computer science for everyone requires us to re-think how we teach and what we teach. The conclusion describes how we might create computing education for everyone.







Agent-Based Tutoring Systems by Cognitive and Affective Modeling


Book Description

"This book presents a modern view of intelligent tutoring, focusing mainly on the conception of these systems according to a multi-agent approach and on the affective and cognitive modeling of the student in this kind of educational environment"--Provided by publisher.







Intelligent Tutoring Systems


Book Description

This book constitutes the refereed proceedings of the 6th International Conference on Intelligent Tutoring Systems, ITS 2002, held in Biarritz, France, and San Sebastian, Spain, in June 2002 The 93 revised full papers presented together with 5 invited papers and 16 posters were carefully reviewed and selected from 167 full paper submissions. The papers address all current issues in the interdisciplinary field of intelligent tutoring systems. The book offers topical sections on agents, architectures, Web, authoring, learning, dialogue, evaluation, narrative, and motivation and emotions.




Data Clustering


Book Description

Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results. The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Readers also learn how to perform cluster analysis with the C/C++ and MATLAB programming languages.