bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Visualization and Data Summary
Authors: Cerrito Patricia
Published: May 2010

Patients in a clinic or geographic area are very heterogeneous. Therefore, the distribution of patient factors will not have a normal distribution. Generally, the distribution will have a heavy tail since every patient population will have those extreme patients who need extraordinary care; there will be more patients who need considerable care than those whose treatment can be discontinued early. Thus, unlike the normal distribution assumption, distributions of patient populations will not be symmetric. Therefore, great care must be used when considering a model that assumes normality, or even symmetry. We will look at alternative methods of analysis and visualization that do not depend upon the assumption of normality.
Text Mining and Patient Severity Clusters
Authors: Cerrito Patricia
Published: May 2010

Text mining diagnosis codes takes advantage of the linkage across patient conditions instead of trying to force the assumption of independence. Combinations of diagnoses are used to define groups of patients. For example, patients with diabetes have a high probability of heart disease and kidney failure compared to the general population. Instead of relying on these three conditions and assuming that the general population is just as likely to acquire them in combination, text mining examines the combinations of diabetes, diabetes with kidney failure, diabetes with heart failure, and diabetes with both conditions.
Rare Association Rule Mining
Authors: Koh Yun Sing , Rountree Nathan
Published: May 2010

The notion of finding rare association rules is like finding precious gems in an open field; it is a daunting task but, if successful, it is very rewarding. Association rule mining systems, such as Apriori, generally employ an exhaustive search algorithm. While these algorithms are in theory capable of finding rare association rules, they become intractable if the minimum level of support is set low enough to find rare rules. Such algorithms are therefore inadequate for finding rare associations, and also suffer from the rare item problem. Research to solve this problem has become more prevalent in recent times. The main goal of rare association rule mining is to discover relationships among sets of items in a transactional database that occur infrequently. This chapter presents a survey on the current trends and approaches in the area of rare association rule mining.
Replacing Support in Association Rule Mining
Authors: Meo Rosa , Ienco Dino
Published: May 2010

Association rules are an intuitive descriptive paradigm that has been used extensively in different application domains with the purpose to identify the regularities and correlation in a set of observed objects. However, association rules’ statistical measures (support and confidence) have been criticized because in some cases they have shown to fail in their primary goal: that is to select the most relevant and significant association rules. In this chapter the authors propose a new model that replaces the support measure. The new model, like support, is a tool for the identification of reliable rules and is used also to reduce the traversal of the itemsets’ search space. The proposed model adopts new criteria in order to establish the reliability of the information extracted from the database. These criteria are based on Bayes’ Theorem and on an estimate of the probability density function of each itemset. According to our criteria, the information that we have obtained from the database on an itemset is reliable if and only if the confidence interval of the estimated probability is low compared with the most likely value of it. We will see how this method can be computed in an approximate but satisfactory way, with the same algorithms that are usually adopted to select itemsets on support threshold.
Mining Rare Association Rules by Discovering Quasi-Functional Dependencies
Authors: Bruno Giulia , Garza Paolo , Quintarelli Elisa
Published: May 2010

In the context of anomaly detection, the data mining technique of extracting association rules can be used to identify rare rules which represent infrequent situations. A method to detect rare rules is to first infer the normal behavior of objects in the form of quasi-functional dependencies (i.e. functional dependencies that frequently hold), and then analyzing rare violations with respect to them. The quasi-functional dependencies are usually inferred from the current instance of a database. However, in several applications, the database is not static, but new data are added or deleted continuously. Thus, the anomalies have to be updated because they change over time. In this chapter, we propose an incremental algorithm to efficiently maintain up-to-date rules (i.e., functional and quasi-functional dependencies). The impact of the cardinality of the data set and the number of new tuples on the execution time is evaluated through a set of experiments on synthetic and real databases, whose results are here reported.
Creating Risk-Scores in Very Imbalanced Datasets
Authors: Breitenbach Markus , Dieterich William , Brennan Tim , Fan Adrian
Published: May 2010

In this chapter, the authors explore Area under Curve (AUC) as an error-metric suitable for imbalanced data, as well as survey methods of optimizing this metric directly. We also address the issue of cut-point thresholds for practical decision-making. The techniques will be illustrated by a study that examines predictive rule development and validation procedures for establishing risk levels for violent felony crimes committed when criminal offenders are released from prison in the USA. The “violent felony” category was selected as the key outcome since these crimes are a major public safety concern, have a low base-rate (around 7%), and represent the most extreme forms of violence. The authors compare the performance of different algorithms on the dataset and validate using survival analysis whether the risk scores produced by these techniques are computing reasonable estimates of the true risk.
ChunkSim
Authors: Furtado Pedro
Published: May 2010

Self-tuning physical database organization involves tools that determine automatically the best solution concerning partitioning, placement, creation and tuning of auxiliary structures (e.g. indexes), based on the workload. To the best of our knowledge, no tool has focused on a relevant issue in parallel databases and in particular data warehouses running on common off-the-shelf hardware in a sharednothing configuration: determining the adequate tradeoff for balancing load and availability with costs (storage and loading costs). In previous work, we argued that effective load and availability balancing over partitioned datasets can be obtained through chunk-wise placement and replication, together with on-demand processing. In this work, we propose ChunkSim, a simulator for system size planning, performance analysis against replication degree and availability analysis. We apply the tool to illustrate the kind of results that can be obtained by it. The whole discussion in the chapter provides very important insight into data allocation and query processing over shared-nothing data warehouses and how a good simulation analysis tool can be built to predict and analyze actual systems and intended deployments.
Data Warehouse Maintenance, Evolution and Versioning
Authors: Eder Johann , Wiggisser Karl
Published: May 2010

Data Warehouses typically are building blocks of decision support systems in companies and public administration. The data contained in a data warehouse is analyzed by means of OnLine Analytical Processing tools, which provide sophisticated features for aggregating and comparing data. Decision support applications depend on the reliability and accuracy of the contained data. Typically, a data warehouse does not only comprise the current snapshot data but also historical data to enable, for instance, analysis over several years. And, as we live in a changing world, one criterion for the reliability and accuracy of the results of such long period queries is their comparability. Whereas data warehouse systems are well prepared for changes in the transactional data, they are, surprisingly, not able to deal with changes in the master data. Nonetheless, such changes do frequently occur. The crucial point for supporting changes is, first of all, being aware of their existence. Second, once you know that a change took place, it is important to know which change (i.e., knowing about differences between versions and relations between the elements of different versions). For data warehouses this means that changes are identified and represented, validity of data and structures are recorded and this knowledge is used for computing correct results for OLAP queries. This chapter is intended to motivate the need for powerful maintenance mechanisms for data warehouse cubes. It presents some basic terms and definitions for the common understanding and introduces the different aspects of data warehouse maintenance. Furthermore, several approaches addressing the problem are presented and classified by their capabilities.
Computer Aided Learning and Multimedia
Authors: Sidhu Manjit Singh
Published: May 2010

In general, Computer Aided Learning (CAL) is the term given to software applications in which a computer is used to partially replace the function of a human instructor in the education or training of a learner/student. CAL is not limited to a particular field in education or constraint to a specific subject matter. The primary goal of CAL is to convey pre-defined theory/concepts to student so as to allow him/ her to understand and apply gained knowledge at work place. A CAL application offers the student a structured method of obtaining information as well as using the computer as navigational and information retrieval medium. CAL can therefore be thought of as a front end to a large information database. Early CAL packages offered the user information in the form of pages of text only. As technology evolved, applications started to present information using a wide range of media formats, including high-resolution graphics, narration, and even interactive video (Marshall, 1988). Hence the combination of one or more electronic media is subsequently known as multimedia.
Development and Usage of TAPS Packages in the Mechanical Engineering Course
Authors: Sidhu Manjit Singh
Published: May 2010

The Mechanical Engineering course is largely based on practical skills and requires the acquisition of basic skills and domain knowledge before applying them on real problems. In order to design and develop a technology assisted problem solving (TAPS) package particularly to guide students in learning and solving engineering problems, it is necessary to be acquainted with its development and its process of realization in practical terms in computer software. User interface design has been applied in learning environments as discussed in previous Chapter 3. Therefore it is informative to discover the extent to which they help engineering students in their learning and thereby be incorporated in TAPS packages. This examination includes an overview of good practice in the positioning and operation of navigational features, visual screen presentation, the nature of presentation, help and feedback and views on the role of the learner in using the TAPS packages. This Chapter discusses the need to learn practical Mechanical Engineering skills and reviews the tutorial and situational learning approaches. Additionally the Chapter provides an overview of TAPS packages and the approach adopted for problem solving and student learning.
Evaluation of Interactive Multimedia Packages
Authors: Sidhu Manjit Singh
Published: May 2010

The literature shows that many different evaluation methodologies for computer aided learning (CAL) packages have been proposed based on different philosophical views (Worthen and Sanders, 1973; Popham, 1974; Stephen and Stanley, 1985). The evaluation may be used for a variety of purposes such as refining goals, defining products or programs, and estimating costs, usability and effectiveness (Reeves, 1993). This involves the systematic review of the content, design, and instructional value and worth of computer aided learning packages. In general, any instructional software package should be evaluated before it is delivered or used in the classroom or research laboratory. This Chapter provides some general evaluation techniques used in the evaluation of such packages.
Conclusion and Further Work
Authors: Sidhu Manjit Singh
Published: May 2010

Mechanical engineering course subjects such as Mechanics Dynamics, combine a mix use of mathematics, schematic diagrams, and text descriptions. Frequently, students are unclear of basic principles of Engineering Mechanics Dynamics, and as such they do not know which mathematical relationships are to be applied in solving a particular problem. Additionally, as the name “dynamics” implies, the very nature of this subject is not “static” and thus requires learners to visualize motion; for example, in a given time period, a particle may be moving in a straight line and after some seconds the particle may experience a curvilinear motion. If the learner fails to see this, the learner will not be able to employ the right equations to solve the problem. As such, an effort was made to evaluate the feasibility and effectiveness of employing technologies such as multimedia and desktop virtual reality to enhance the problem solving skills and learning of students. In this book, the development of computer-aided learning software termed as technology assisted problem solving (TAPS) packages is demonstrated in Chapter 7. The book provided an overview of developing TAPS packages using multi design approaches. The work is one of the pioneering efforts to address the need for computer based problem solving software packages for the domain of engineering. The development processes of TAPS packages are shown in (Figure 1). More specifically, the conclusions of the study are as follows.
Artificial Immune Systems for Anomaly Detection
Authors: Plett Eduard , Das Sanjoy , Li Dapeng , Panigrahi Bijaya K.
Published: May 2010

This chapter introduces anomaly detection algorithms analogous to methods employed by the vertebrate immune system, with an emphasis on engineering applications. The basic negative selection approach, as well as its major extensions, is introduced. The chapter next proposes a novel scheme to classify all algorithmic extensions of negative selection into three basic classes: self-organization, evolution, and proliferation. In order to illustrate the effectiveness of negative selection based algorithms, one recent algorithm, the proliferating V-detectors method, is taken up for further study. It is applied to a real world anomaly detection problem in engineering, that of automatic testing of bearing machines. As anomaly detection can be considered as a binary classification problem, in order to further show the usefulness of negative selection, this algorithm is then modified to address a four-category problem, namely the classification of power signals based on the type of disturbance.
Locally Recurrent Neural Networks and Their Applications
Authors: Ganchev Todor D.
Published: May 2010

In this chapter we review various computational models of locally recurrent neurons and deliberate the architecture of some archetypal locally recurrent neural networks (LRNNs) that are based on them. Generalizations of these structures are discussed as well. Furthermore, we point at a number of realworld applications of LRNNs that have been reported in past and recent publications. These applications involve classification or prediction of temporal sequences, discovering and modeling of spatial and temporal correlations, process identification and control, etc. Validation experiments reported in these developments provide evidence that locally recurrent architectures are capable of identifying and exploiting temporal and spatial correlations (i.e., the context in which events occur), which is the main reason for their advantageous performance when compared with the one of their non-recurrent counterparts or other reasonable machine learning techniques.
Transfer Learning
Authors: Torrey Lisa , Shavlik Jude
Published: May 2010

Transfer learning is the improvement of learning in a new task through the transfer of knowledge from a related task that has already been learned. While most machine learning algorithms are designed to address single tasks, the development of algorithms that facilitate transfer learning is a topic of ongoing interest in the machine-learning community. This chapter provides an introduction to the goals, settings, and challenges of transfer learning. It surveys current research in this area, giving an overview of the state of the art and outlining the open problems. The survey covers transfer in both inductive learning and reinforcement learning, and discusses the issues of negative transfer and task mapping.
FOL Learning for Knowledge Discovery in Documents
Authors: Ferilli Stefano , Esposito Floriana , Biba Marenglen , Basile Teresa M.A. , Di Mauro Nicola
Published: May 2010

This chapter proposes the application of machine learning techniques, based on first-order logic as a representation language, to the real-world application domain of document processing. First, the tasks and problems involved in document processing are presented, along with the prototypical system DOMINUS and its architecture, whose components are aimed at facing these issues. Then, a closer look is provided for the learning component of the system, and the two sub-systems that are in charge of performing supervised and unsupervised learning as a support to the system performance. Finally, some experiments are reported that assess the quality of the learning performance. This is intended to prove to researchers and practitioners of the field that first-order logic learning can be a viable solution to tackle the domain complexity, and to solve problems such as incremental evolution of the document repository.
Machine Learning and Financial Investing
Authors: Du Jie , Rada Roy
Published: May 2010

This chapter presents the case for knowledge-based machine learning in financial investing. Machine learning here, while it will exploit knowledge, will also rely heavily on the evolutionary computation paradigm of learning, namely reproduction with change and selection of the fit. The chapter will begin with a model for financial investing and then review what has been reported in the literature as regards knowledge-based and machine-learning-based methods for financial investing. Finally, a design of a financial investing system is described which incorporates the key features identified through the literature review. The emerging trend of incorporating knowledge-based methods into evolutionary methods for financial investing suggests opportunities for future researchers.
Application of Neural Networks in Animal Science
Authors: Soria Emilio , Fernández Carlos , Serrano Antonio J. , Martínez Marcelino , Magdalena José R. , Guerrero Juan F.
Published: May 2010

Stock breeding has been one of the most important sources of food and labour throughout human history. Every advance in this field has always led to important and beneficial impacts on human society. These innovations have mainly taken place in machines or genetics, but data analysis has been somewhat ignored. Most of the published works in data analysis use linear models, and there are few works in the literature that use non-linear methods for data processing in stock breeding where these methods have proven to obtain better results and performance than linear, classical methods. This chapter demonstrates the use of non-linear methods by presenting two practical applications: milk yield production in goats, and analysis of farming production systems.
Current Practices in Select Healthcare Systems
Authors: Sadanand Venkat
Published: May 2010

In this chapter, current practices of healthcare delivery in three economically advanced countries will be reviewed. Is healthcare delivery commensurate with economic prosperity? Countries with technological and economic advantages may be better poised to deliver healthcare efficiently. However, this is not the case in fact. The following review will show that medico-legal and technological prowess may not translate into a healthier life and better healthcare delivery. It will be argued that poor allocation of ample resources is tantamount to resource insufficiency. The chapter will cite anonymous but true cases of patients to illustrate the salient points.
Agency in Health Care System Modeling and Analysis
Authors: Paranjape Raman , Gill Simerjit
Published: May 2010

This chapter examines the paradigm that a health care system’s behavior may be examined using an agent simulation in order to illuminate its macroscopic characteristics and the effects of policy on its over all operation. Further, if the individual components are well articulated, the component behavior may be also studied. Health care systems in North America are generally regulated by various processes and mechanisms in order to provide orderly access to, and control of, the health care system. While all processes are designed to be fair and equitable, in many ways the system can not be examined or optimized because the risk, that making changes to the system might result in degraded services, is too great to permit making even simple changes. In this context we propose the development of a health care system model in which agents mimic the behavior of the key components of the system. These components interact and engage each other in a manor analogous to the operation of the health care system. The formulation of such a system is, by its very nature, an extremely complex process, and necessitates development in components or units. In this chapter we present the first components of such a system. Each component has unique and complex behaviors. These components will, with additional development, form the basic structure of a health care system model. Specifically we present results from the development of a diabetic patient agent model, the development of an agent-based neurosurgery ward bed allocation system, and the development of an agent-based scheduling system that may be used to allocate resources within the health care system.
An Agent-Based Modeling System for Wellness
Authors: Benedicenti Luigi , Soomlek Chitsutha
Published: May 2010

This chapter introduces an agent-based wellness visualization system. The visualization system integrates and analyzes health information collected from existing portable health monitoring devices, users, and other existing health information resources (e.g. hospital’s databases). It can be used as a single wellness indicator for an individual and a one-station examination for health care professionals. The single wellness indicator provides a simplified view of health information of an individual. Thus, the individual will have a better understanding in personal wellness and will be encouraged to be aware of both personal and public’s health. The one-station examination assists healthcare professional to have rapid evaluation and boosts healthcare services. Initial result indicates that the proof of concept of the research will provide direct benefits to the public, research communities, and enterprises.
Using Probabilistic Neural Network to Select a Medical Specialist Agent
Authors: Mago Vijay Kumar , Devi M. Syamala , Bhatia Ajay , Mehta Ravinder
Published: May 2010

The authors aim to design the Multi-agent system, in which the software agents interact with each other to diagnose a disease and decide the treatment plan(s). In this chapter, the authors present a novel approach of applying Probabilistic Neural Network (PNN) to classify the childhood disease and their respective medical specialist. Normally this classification is performed by the pediatricians. The system that has been presented here, imitates the behavior of a pediatrician while selecting super specialist doctor. This decision making mechanism will be embedded in an agent called Intelligent Pediatric Agent. To design the PNN, a database consisting of 104 records has been gathered. It includes 17 different sign symptoms and based on their values, one of the five super specialists is selected. A Back propagation Neural Network (BPNN) has also been designed to compare the results produced by the PNN and it is found that PNN is more promising.
Role of Multi-Agents System in Creation of Collaborative Environments within Mental Health Domain
Authors: Hadzic Maja , Dillon Darshan S.
Published: May 2010

Mental illness is becoming one of the major problems of our society. The World Health Organization predicted that depression would be the world’s leading cause of disability by 2020. The exact causes of many mental illnesses are still unknown, mainly due to the complex nature of mental health. In this paper, the authors propose a multi-agent system designed to assist in effective and efficient management, retrieval and analysis of mental health information. They utilize the TICSA approach to define different agent Types, their Intelligence, Collaboration paths, address Security problems and Assemble individual agents. They use UML 2.1 Sequence and Composite diagrams to model social and goal-driven nature of the multi-agent system. The proposed multi-agent system has the potential to provide and expose the knowledge that will increase our understanding and control over mental health and help in development of effective prevention and intervention strategies.
Understanding Time and its Relationship to Individual Time Management
Authors: Wu Dezhi
Published: May 2010

Time never has been an easy concept, since each of us has different time perceptions and experiences. Individual time management stories can vary dramatically because of a variety of reasons, such as different backgrounds, professions, social roles, cultures, gender and so on. The main focus of this book is on socially-constructed time, which demonstrates how humans interact with time in their social contexts. This perspective of time provides a good basis to understand how individuals experience time and furthermore manage their time. This chapter introduces the concept of time based on prior time research and its related concepts. First, it describes how difficult it is to interpret what time is and how scientists in different disciplines explain the nature of time.
Calendar Tools
Authors: Wu Dezhi
Published: May 2010

The focus of this chapter is to review electronic time management or calendar tools. This review is presented to support the underlying motivation for this book, which is to improve time management by providing better electronic time management or calendar tools that incorporate more types of temporal structures than those being managed with existing tools. The chapter begins with a discussion of paper-based calendars, which have served as the primary structure for representing time usage for all subsequent time management aids. This discussion relates time management practices to the types of temporal structures the paper calendar manipulates and to the paper calendar successor, the electronic calendar. A comparison is made between the advantages of paper-based tools and electronic tools to illustrate the types of advantages that were moving to electronic means. This comparison is also made to illustrate that the advantages developed for the electronic time manager are simplistic and somewhat obvious, such as simplifying repeated entries and announcing time-based events.
Who are Effective Time Managers? Bivariate Correlation Analysis and Hypotheses Testing
Authors: Wu Dezhi
Published: May 2010

This chapter presents the bivariate analysis results, and compares the differences between effective time managers and ineffective time managers on their temporal structure knowledge, usage, and relationship understanding. The hypotheses to compare effective time managers and ineffective time managers developed for this research are examined in this chapter.
Input from Users
Authors: Wu Dezhi
Published: May 2010

The main objectives of this chapter are to present useful and practical time management hints from users that were surveyed and to identify user difficulties with the current electronic time management or calendar tools and users’ desired calendar features. Consistent with the main findings from our large survey with students, faculty, and staff members in a U.S. public research university (see Chapter 10), additional data collected from open-ended questions with the same user population also reflect the reality that users are experiencing dynamic time management demands, and demonstrate how they respond to these demands and problems of meeting deadlines. Users’ input on time management hints indicate again that an effective time manager is also a good temporal structure manipulator. The key strategies offered by the users for effective time management are (1) plan in advance, (2) prioritize tasks, (3) control time, (4) stop procrastination, (5) understand temporal structure relationships, and (6) communicate and coordinate time with others. These strategies are interpreted from a temporal structure point of view respectively in this chapter.
Relationship between Calendar Tool Design and Temporal Structure Usage
Authors: Wu Dezhi
Published: May 2010

This chapter supports the argument that began in Chapter 4 for the need to design and implement electronic time management/calendar tools that incorporate more temporal structures than the limited ones that are now being used. The support is based upon the survey data analysis, upon the pilot interviews, and upon a small longitudinal study that was conducted. This chapter first describes the correlations between perceived time management tool usefulness and individual time management quality. It also documents a few significant correlations that occurred between perceived time management tool usefulness and the four temporal structure constructs investigated in this research. The longitudinal study is presented in this chapter. It examines whether capturing and utilizing temporal structures in an electronic time management tool improves individual time management quality. This chapter also summarizes and extrapolates the results presented and combines this data with salient results from the interviews presented in this book. The results that are used and summarized are those that apply to the arguments being made that designing better electronic time management tools that make it easier for people to capture a wider range of temporal structures will lead to better time management. Explicit suggestions are made for design opportunities that would capture currently unavailable or difficult to capture temporal structures.
Conclusion, Contribution and Implications to Future Electronic Calendar Tool Design
Authors: Wu Dezhi
Published: May 2010

The key findings for this research are summarized in Chapter 13. Overall, this research shows there is a strong relationship between the quality of individual time management and the use and understanding of various temporal structures based upon three different population samples (student, faculty and staff). Based on these results, it is argued that current time management tools (e.g., calendars) do not provide sufficient support for people to easily capture and use the wide range of temporal structures that constrain their lives. This chapter also demonstrates how this work is closely related to the fields of information systems, computer science and human-computer interaction. It discusses the limitations of this research and then describes future research directions that arise from the results of this research.
Teacher Professional Development Practices
Authors: Pachler Norbert , Daly Caroline , Turvey Anne
Published: May 2010

This chapter discusses the need for new models of teachers’ professional development in the context of established and emerging technologies and socio-constructivist theories of teacher learning within online and other communities. The authors present the current contexts affecting professional development in England and discuss the significance of the shift towards collaborative and community approaches to teachers’ learning. The authors argue that transformation is a key, though troublesome, concept in considering the aims of professional development for teachers’ use of technologies in their everyday practice. They explore these ideas by presenting the case of the Transformation Teachers Programme (TTP), a wide-scale teachers’ development project carried out in a London borough by Haringey City Learning Centre (CLC), and they examine how this project has implemented new approaches to Information and Communications Technology (ICT) and teachers’ professional development, based on collaborative experimentation, enquiry and risk-taking within online and other community-based arrangements.
Realising the Potential of Virtual Environments
Authors: Wilson Alastair , Christie Donald
Published: May 2010

A national schools intranet is currently being developed in Scotland with universal access anticipated in late 2009. This new technology will provide teachers with access to a variety of tools with which to develop their teaching and learning. Drawing on the experience of the Applied Educational Research Scheme (AERS), a five year research programme funded to build research capacity in Scottish Education, this chapter seeks to explore the potential for teachers in Scotland to realise effective use of this new technology in their professional learning. The chapter uses current research literature on teacher professionalism and professional learning in Scotland to establish the context in which Scottish teachers are currently working. It then draws on three vignettes drawn from research within AERS to argue that the development of virtual environments to support professional learning in Scotland requires further, significant collaborative working between the practitioner, policy and research communities.
Teacher Professional Development through Knowledge Management in Educational Organisations
Authors: Gairin-Sallán J. , Rodriguez-Gómez D.
Published: May 2010

Professional development has mainly centered around training processes that involve updating knowledge, yet it has made little headway as a construct that includes both the professional and personal characteristics and working conditions. It has also focused more on developing training programmes than on analysing the tools for continuous training. This chapter analyses the relationships between professional development, organisational development and the creation and management of collective knowledge. These three concepts can be interrelated and contribute to change when we place ourselves within the framework of autonomous organisations with collective projects focused on lifelong learning. It also outlines the Accelera experience of knowledge creation and management in communities, describing the model and process used. This article examines some of the findings and future prospects of the methodology presented.
Game Informed Virtual Patients
Authors: Begg Michael , Dewhurst David , Ross Michael
Published: May 2010

Modern medical education necessitates a complex interleaving of issues relating to practice, professional and personal development, teaching and learning. This complexity has led, in part, to medical education being persistently located in the vanguard of eLearning development. Here, the authors describe our approach to the development of virtual patient resources and in particular how this iterative dialogue arising from the allied processes of practice, reflection and pedagogy required to create new learning tools and resources has contributed to professional development of those engaged in teaching medical students and in building online learning communities at the University of Edinburgh.
Online Pedagogy Design and Development
Authors: Whitehouse Pamela , McCloskey Erin , Ketelhut Diane Jass
Published: May 2010

The purpose of this chapter is to examine the shifting priorities of online teacher professional development design, particularly through the lens of online pedagogies. Whether one’s purpose is to design an online teacher learning community or formal professional development program, decisions about technology use will mediate how the learning communities or training programs function. Designers, when choosing communication tools or digital media for inclusion in their program, ideally draw from their technological pedagogical content knowledge, or TCPK – that is, their understanding of which technologies will support pedagogy appropriate for the content and learners being targeted. The model we offer for online teacher professional development program design makes visible the interaction between the technology, the content, the pedagogy and the learner.
Challenges for the Teacher's Role in Promoting Productive Knowledge Construction in Computer-Supported Collaborative Learning Contexts
Authors: Arvaja Maarit , Hämäläinen Raija , Rasku-Puttonen Helena
Published: May 2010

This chapter discusses challenges related to teachers’ pedagogical activities in facilitating productive discussions among students in Computer-Supported Collaborative Learning (CSCL) contexts. In the light of two different cases from secondary-level and higher education contexts, the authors examine how teachers’ pedagogical choices influenced the quality of students’ activity, namely Web-based discussion. The results of our studies indicated that rich moments of collaboration were rare and distributed unequally among the students. The obvious weakness from the perspective of teachers’ pedagogical activities was that in neither of the studies was the students’ interaction in the discussion forum supported in any way. A future challenge is, therefore, to develop both pedagogical and technological tools to support the monitoring and enhancement of students’ learning process during online learning. Furthermore, we discuss how teachers’ professional development (TPD) is challenged by new technological tools in formal learning environments.
Applications of Technology for Instruction and Assessment with Young Children
Authors: Allen Lee , Blake Sally
Published: May 2010

This chapter discusses the roles of technology in instruction and assessment of young children. The influx of technology in schools and homes has been rapid and wide spread. Most children today have seen or used a computer or other technological tool before they enter school. As the student-to-computer ratio has improved from 60-to-1 in 1983 (OTA, 1988) to an average 4-to-1 nationwide in 2007 (Nagel, 2007) the question is no longer whether computers can assist in early childhood learning in general, but rather how computers can and should be used and to what end (Johnson, 1998; Cuban, 2001).
Promoting Family Involvement through Using Technology
Authors: Morris Vivian Gunn , Izumi-Taylor Satomi , Smith Cheri Lewis , Winsor Denise L.
Published: May 2010

In this chapter the authors have provided an overview of some of the ideas about families and technology use in early childhood programs. The four authors are university faculty and provide their thinking and some experiences with family involvement and teacher training. The chapter is framed with the idea that families are the first teachers of children and play a major role in learning. There is a special introductory section written by Denise Winsor, who piloted the Family Builders and Family Preservation grants in the 1980’s. Winsor provides insight into the role of family in early childhood education. The next section explores technology that is used to facilitate family involvement and building family involvement through technology. The authors briefly discuss some of the issues, problems and solutions to technology within family relationships and the role you might play as a professional. They try to address the advantages and disadvantages of family/school communication approaches to developing technology relationships with caregivers. They have included some real world examples from practitioners and how they help our students conceptualize technology use with families. The last section includes helpful advice for families concerning appropriate use of technology with their child. The authors hope this chapter helps you think about the role of families in your classroom and how technology can work for the development of stronger relationships as well as academic support.
Technology Resources and Software Recommended for Young Children and Teachers and Evaluating Web Sites
Authors: Allen Lee , Blake Sally , Burkett Candice , Crow Rene , Gibbons Andrew Neil , Grant Michael M. , Izumi-Taylor Satomi , Lee Yu-Yuan , Lopez Jorge , López María Eugenia , McMurtry Zelda , Mims Clif , Morris Vivian Gunn , Smith Cheri Lewis , Winsor Denise
Published: May 2010

Technology is being designed for children of all ages, even as young as nine months (Morrison, 2007). The software market is growing rapidly for children from infant to preschool age, with programs for children under five representing the fastest-growing educational softwarea area (Morrison 2007). The Internet provides access to a great collection of resources available for young children and teachers. The following pages may be of interest to educators of young children. There are web sites included for software and articles of interest related to issues concerning technology and young children selected by all authors of our book.
Standardization in User Modeling and Learning Objects Retrieval
Authors: Botsios Sotirios , Georgiou Dimitrios
Published: May 2010

Adaptation and personalization of the information and instruction offered to the users -individuals or groups- in on-line e-learning environments are considered to be the turning point of recent research efforts. The “one-size-fits-all” approach has some important drawbacks, from the educational point of view. Adaptive educational hypermedia systems (AEHSs) in World Wide Web became a very active research field and the need of standardization of user assessment, instruction material and e-learning environments arose, as the continually augmenting research efforts lacked the interoperability dimension. The main objective of this chapter is to provide a classification of some basic assessment aspects (adaptivity parameters) of an AEHS user, extracted from research work that refers to commonly accepted e-learning standards, such as SCORM. Also, the authors provide a starting point for the development of a generic architecture for the retrieval of standardized learning objects (LOs) from disperse learning objects repositories (LORs) to an e-learning environment, which can support collaboration activities. The retrieved LOs will comply with user assessment stored in the user model.
Time-Shifted Online Collaboration
Authors: Brent Edward , Atkisson Curtis , Green Nathaniel
Published: May 2010

This chapter examines online collaboration in a distributed e-learning environment. The authors describe the emerging technology of Web-based automated essay grading that provides extensive real-time data for monitoring and enhancing e-learning activities. They examine data from student use of this software service in a large introductory social science class. Using information routinely collected by the system, the authors find that students take advantage of this learning environment to revise and resubmit essays, dramatically improving their final grade by an average of 20% or two letter grades. They conclude the essential components of this learning environment that makes it so successful are its ability to provide detailed, personalized feedback to students immediately after they submit their work along with the opportunity to revise and resubmit. This transforms an automated assessment tool into a powerful collaborative learning environment. Instead of waiting days or weeks for instructor comments, that feedback is time-shifted to occur at the time it can be most effective for students. Changing the timing of feedback creates a powerful teachable moment when students have motivation, information, opportunity, and feedback. They are motivated to improve their grade, they are told what they did right or wrong while the relevant information is fresh in their minds, and they have the opportunity to revise and resubmit. The chapter ends with consideration of how those same elements can be, and sometimes already are, used in other instructional strategies such as podcasting to create effective learning environments that take advantage of the teachable moment.
Expertiza
Authors: Gehringer Edward F.
Published: May 2010

Educators and accrediting agencies demonstrate a growing awareness that students learn better when they work in groups, and on projects that are more similar to those encountered on the job, where their contributions are used by others to add value to the operations of the enterprise. However, it is very time consuming to assess project work; the only scalable way to accomplish this is to have students assist in the assessment. Expertiza is a system for managing all kinds of communication that is involved in assessment: double-blind communications between authors and reviewers, assessment of teammate contributions, evaluations by course staff, and surveys of students to assess the assignment and the peer-review process. This chapter places Expertiza in context among other electronic peer-review systems, algorithms, and methodologies. It relates the results of three experiments showing that through the peer-review process, students are capable of producing work that can be used as teaching materials in later classes.
A Model for Monitoring and Evaluating CSCL
Authors: Persico Donatella , Pozzi Francesca , Sarti Luigi
Published: May 2010

This chapter tackles the issue of monitoring and evaluating CSCL (Computer Supported Collaborative Learning) processes. It starts from the awareness that most of the tasks carried out in managing, tutoring, fine tuning and evaluating online courses heavily rely on information drawn through monitoring. Information of this kind is usually needed for both the assessment of individual learning and the evaluation of a learning initiative. The development of a sound, general purpose model to organize this information serves a variety of purposes, since it makes the monitoring, assessment and evaluation processes more systematic and effective. By describing the model and providing concrete examples of its use, the goal of this chapter is to demonstrate its potential, flexibility and suitability to meet evaluators’ aims in a wide range of cases. The model gathers consolidated practices in the field and is based on the most recent findings of theoretical CSCL research.
Nonverbal Communication as a Means to Support Collaborative Interaction Assessment in 3D Virtual Environments for Learning
Authors: Peña Pérez Negrón Adriana , de Antonio Jiménez Angélica
Published: May 2010

In the classrooms at school, when a group of students is working in a predetermined task, the teacher or the tutor identifies some problems related to collaboration by observing the students’ behavior. While interacting, people interchange messages composed of speech, actions and gestures, as the wordless messages emphasize, support or even substitute speech. In 3D collaborative virtual environments (CVE), the user’s graphical representation, an avatar, is the means to express this nonverbal communication (NVC). The authors’ proposal is that, like in a real learning scenario, by the observation of specific NVC cues, indicators of collaborative interaction can be inferred to an extent that they can be used to foster collaboration, if necessary, in a learning task situation. The various NVC cues that have been selected for that purpose and their corresponding collaborative learning interaction indicators will be presented. An exploratory study that consisted in the analysis of a real life situation during a collaborative task accomplishment, directed to the development of an experimental 3D CVE desktop application that allows avatars’ display of NVC cues, will be discussed.