Abstract
Current Learning Management Systems generically provide online forums for interactions between students and educators. In this article we propose a tool, the iGraph, that can be embedded in Learning Management Systems that feature hierarchical forums. The iGraph is capable of depicting and analyzing online interactions in an easy to understand graph. The positioning algorithm is based on social network analysis statistics, taken from the collected interactions, and is able to smoothly present temporal evolution in order to find communicational patterns and report them to the educator.

Abstract
Learning environments where all participants can present their ideas, where all contribute to discuss and assess those ideas are in our opinion essential to improve the learning process. Grading peers is also important to the development of motivation and sense of responsibility. The Moodle's Workshop module seems to address this issues. However, this module is rarely used and, is planned to be removed from the next release. We run a set of tests and inquiries that led us to conclude that its usability is very low, its interface is generically pour-understandable and the final grades for the activity are usually surprising. In this work we present a reformulation of the workshop in which concerns the configuration interface, the administration module, and the final grades page. The preliminary results indicate an improvement of more than 300% of the usability. Future development plans include full integration of the code in the Moodle LMS and testing the new module for improvement and measuring of real usefulness. ©2009 IEEE.

Abstract
Self and peer-evaluation allow the development of learning environments which provide students with the means to consider upon their own (and of their colleagues) current learning skills. However, if each student in a class performs an evaluation of two of his(her) peers, which in turn will have to be assessed by the teacher/educator, then the additional work will certainly double. Hence, when considering large classes, this methodology is clearly infeasible due to the overload of work. In this article we describe a solution to provide educators with better conditions to implement self and peer-evaluation by using a web-based tool that can be coupled with general open-source learning management systems. Our tool, based on the Moodle Workshop module, features an automatic online distribution of the students' submitted assignments for peer-evaluation, and an automatic assessment of the evaluations. The criteria for evaluating student submissions can be set to meet the teacher/educator objectives as it comprises a several templates ranging from open questions graded over a topic-match table, to multiple choice questions, calculated questions, and even full text graded over sets of error-banded answer statements. The system, throughout comparison of every criteria item in the student's submitted assessment with the teacher's assessment, or with the considered best assessment by the system (depending on configuration), automatically computes a grade which reflects the quality of the student's assessment. It is also flexible enough to allow configuration of evaluation parameters as: number of criteria and topics to use as the evaluation table; weights assigned to criteria; scales used in each evaluation topic; degree of rigidness for assessment (from very lax to very strict), and the number of peers to evaluate. The configuration interface allows overlapping of activity phases (evaluation of examples from the teacher, own work submissions, peer-review, review assessment and display of results) - it is possible to have students reviewing their peers, even if not all the students in the class have already submitted their work. To present the final grades, including information from the peer-review and correspondent assessments, we created a dynamic page with sliding panes which follow a minimum information display principle: specific (student) information is accessible from the general (class) information pane with a single click. We also implemented a system of graphical 'alerts' to the teacher/evaluator for problematic situations in which manual intervention is recommended.

Abstract
The interactions that occur among participants in online forums frequently are an important criteria in evaluating learning methodologies practiced in e-learning contexts. Not only are the interactions between peers an important resource of information, but also, the way the teacher interacts with students. However, apart from general statistics available in common online learning platforms, this type of information is difficult to retrieve. A graphical mapping based on social network analysis theory, of such interactions that occur in online environments, is proposed as a possible solution for automatically depicting and analyzing relations that are established between participants in online forums. In this paper we present a system which provides learning management systems with an additional tool for graphically mapping and analyzing student-student and teacher-student interactions. The system represents both current network interactions and a historical graphical slideshow of online interactions between participants.

Abstract
Complex networks from domains like Biology or Sociology are present in many e-Science data sets. Dealing with networks can often form a workflow bottleneck as several related algorithms are computationally hard. One example is detecting characteristic patterns or "network motifs" - a problem involving subgraph mining and graph isomorphism. This paper provides a review and runtime comparison of current motif detection algorithms in the field. We present the strategies and the corresponding algorithms in pseudo-code yielding a framework for comparison. We categorize the algorithms outlining the main differences and advantages of each strategy. We finally implement all strategies in a common platform to allow a fair and objective efficiency comparison using a set of benchmark networks.We hope to inform the choice of strategy and critically discuss future improvements in motif detection. © 2009 IEEE.

Abstract
We present a new, efficient and scalable tool, named BIORED, for pattern discovery in proteomic and genomic sequences. It uses a genetic algorithm to find interesting patterns in the form of regular expressions, and a new efficient pattern matching procedure to count pattern occurrences. We studied the performance, scalability and usefulness of BIORED using several databases of biosequences. The results show that BIORED was successful in finding previously known patterns, thus an excellent indicator for its potential. BIORED is available for download under the GNU Public License at http://www.dcc.fc.up.pt/bi-ored/. An online demo is available at the same address.