Yannis A. Dimitriadis

Grid Characteristics and Uses: A Grid Definition

This paper discusses the concept of grid towards achieving a complete definition using main grid characteristics and uses found in literature. Ten definitions extracted from main literature sources have been studied allowing the extraction of grid characteristics while grid uses are defined in terms of the different types of application support provided by grids. A grid definition is proposed using these characteristics and uses. This definition may be very useful to determine the limits of the grid concept as well as to explore new application fields in grid computing. In this sense, the extracted characteristics are employed to determine the potential benefits a grid infrastructure may provide to Computer Supported Collaborative Learning applications.

Ink, Improvisation, and Interactive Engagement: Learning with Tablets

Instructional models that reflective educators develop and share with their peers can primarily drive advances in the use of tablets in education. Communities that form around platforms such as Classroom Presenter and Group Scribbles should provide an excellent forum for such advances.

IMS learning design support for the formalization of collaborative learning patterns

Collaborative learning patterns (CLPs) are detailed descriptions of best practices in collaborative learning. These patterns provide a way for a representation of key aspects of CSCL (computer-supported collaborative learning) that is easy to understand by software developers. To formalize these CLPs we have focused our attention on IMS learning design (IMS-LD). IMS-LD provides a means of expressing many different pedagogical approaches (including collaborative learning), however we have found some limitations in reflecting learning experiences that are group-based. Although this specification supports multiple roles in a learning activity, it is not possible to specify how they are going to interact. This paper points out this deficiency and proposes an extension of IMS-LD. The process that can be followed in order to obtain a unit of learning based on a CLP is illustrated with an example.

MicroARTMAP: use of mutual information for category reduction in fuzzy ARTMAP

A new architecture, called MicroARTMAP, is proposed to impact the category proliferation problem present in Fuzzy ARTMAP. It handles probabilistic information through the optimization of the mutual information between the input and output spaces, but allowing a small training error, thus avoiding overfitting. While reducing the number of categories used by Fuzzy ARTMAP, it holds several desirable properties, such as a correct treatment of exceptions and a fast algorithm, as opposed to other approaches like BARTMAP. In addition, it is shown that MicroARTMAP is less sensitive than Fuzzy ARTMAP with respect to the the pattern presentation order, and that it degrades less if the training set is noisy.

Studying participation networks in collaboration using mixed methods

This paper describes the application of a mixed-evaluation method, published elsewhere, to three different learning scenarios. The method defines how to combine social network analysis with qualitative and quantitative analysis in order to study participatory aspects of learning in CSCL contexts. The three case studies include a course-long, blended learning experience evaluated as the course develops; a course-long, distance learning experience evaluated at the end of the course; and a synchronous experience of a few hours duration. These scenarios show that the analysis techniques and data collection and processing tools are flexible enough to be applied in different conditions. In particular, SAMSA, a tool that processes interaction data to allow social network analysis, is useful with different types of interactions (indirect asynchronous or direct synchronous interactions) and different data representations. Furthermore, the predefined types of social networks and indexes selected are shown to be appropriate for measuring structural aspects of interaction in these CSCL scenarios. These elements are usable and their results comprehensible by education practitioners. Finally, the experiments show that the mixed-evaluation method and its computational tools allow researchers to efficiently achieve a deeper and more reliable evaluation through complementarity and the triangulation of different data sources. The three experiments described show the particular benefits of each of the data sources and analysis techniques.

Multiple case studies to enhance project-based learning in a computer architecture course

The IEEE/Association for Computing Machinery (ACM) Computing Curricula and the Accreditation Board of Engineering and Technology (ABET) Evaluation Criteria 2000 emphasize the use of recurrent concepts and system design/evaluation through projects and case studies in the curriculum of Computer and Electrical Engineering. In addition, efficient teamwork, autonomy, and initiative are commonly required qualifications for a professional in this field. Project-based learning approaches that require the students to handle realistic case studies are adequate to pursue these objectives. However, these pedagogical approaches tend to be rejected because they promote deep learning but focus on a restricted set of concepts, whereas many engineering curricula require a broad range of concepts to be covered in each course. The introduction of multiple case studies carried out simultaneously in the same course by different teams of students can broaden the set of concepts studied, but collaboration at different levels must be strongly enforced to achieve effective learning. This paper describes a multiple-case-study project design that has been applied to a computer architecture course for four years. After systematically evaluating the experience, the authors conclude that students achieve a deep learning of the concepts required in their own case study, while they are able to generalize their knowledge to case studies of different characteristics from those considered during the course. Furthermore, a number of collaborative skills and attitudes are developed as a consequence of the proposed environment based on multiple levels of collaboration.

Learning from noisy information in FasArt and FasBack neuro-fuzzy systems

Neuro-fuzzy systems have been in the focus of recent research as a solution to jointly exploit the main features of fuzzy logic systems and neural networks. Within the application literature, neuro-fuzzy systems can be found as methods for function identification. This approach is supported by theorems that guarantee the possibility of representing arbitrary functions by fuzzy systems. However, due to the fact that real data are often noisy, generation of accurate identifiers is presented as an important problem. Within the Adaptive Resonance Theory (ART), PROBART architecture has been proposed as a solution to this problem. After a detailed comparison of these architectures based on their design principles, the FasArt and FasBack models are proposed. They are neuro-fuzzy identifiers that offer a dual interpretation, as fuzzy logic systems or neural networks. FasArt and FasBack can be trained on noisy data without need of change in their structure or data preprocessing. In the simulation work, a comparative study is carried out on the performances of Fuzzy ARTMAP, PROBART, FasArt and FasBack, focusing on prediction error and network complexity. Results show that FasArt and FasBack clearly enhance the performance of other models in this important problem.

Eliciting design patterns for e-learning systems

Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching – learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

TOWARDS AN ART BASED MATHEMATICAL EDITOR, THAT USES ON-LINE HANDWRITTEN SYMBOL RECOGNITION

A new mathematical editor, based on the recognition of run-on discrete handwritten symbols, is proposed. The tested laboratory prototype of the system, modular and adaptable to the user habits and site requirements, uses a natural handwriting interface as well as human gestures. Two methods were used for symbol recognition, namely the state-of-the-art elastic matching algorithm and an Adaptive Resonance Theory neural architecture. The neural solution is proved to be better adapted to the cognitive nature of the problem and faster in both learning and test phases. Finally a novel attribute grammar permits the detection and subsequent correction of errors in the mathematical expressions.

Studying social aspects of computer-supported collaboration with a mixed evaluation approach

Studying and evaluating real experiences that promote active and collaborative learning is a crucial field in CSCL. Major issues that remain unsolved deal with the merging of qualitative and quantitative methods and data, especially in educational settings that involve direct as well as computer-supported collaboration. In this paper we present an evaluation methodology and its application to a university course that took place during the last two academic years. We have developed EL2AM, a tool that allows an automatic processing of computer logs using social network analysis. It has been used jointly with a commercial qualitative research tool in order to support the evaluation process. Experimental results allow us to reflect and draw conclusions on the changes of attitudes towards collaboration experimented by the students along the course.