Adapting Collaborative Learning Tools to Support Group Peer Mentorship

Group peer mentorship is a relatively new addition to the area of collaborative learning. We see an untapped potential in supporting this model of mentorship with the existing collaborative learning tools like peer review and wiki. Therefore, we proposed to use a modified peer review system and a modified wiki system. From our preliminary studies using both peer review and wiki systems, we found that participants preferred the peer-review system to the wiki system in supporting them for mentorship. Therefore, this dissertation specifically addresses how to adapt the peer review system to support group peer mentorship. We proposed a modified peer review system, which comprises seven stages – initial submission of the first draft of the paper by the author, the review of author’s paper by peer reviewers, release of review feedback to the author, back-evaluation of their reviews by the authors, modification of the paper by the author, submission of the final paper and the final stage where both authors and reviewers provide an evaluation of the peer review process with respect to their learning, their perception of the helpfulness of the process, and their satisfaction with the process. We also proposed to use our group matching algorithm, based on some constraints and the principles of the Hungarian algorithm, to achieve a diversified grouping of peers for each peer review session. With these, we conducted six peer review studies with the graduate and undergraduate students at the University of Saskatchewan and teachers in Chile. This dissertation reports on the findings from these studies. We found that peer review, with some modifications, is a good tool to facilitate group peer mentorship. An evaluation of the performance of our group matching algorithm showed an improvement over three other algorithms, with respect to three metrics – knowledge gain of peers, time and space consumption of the algorithm. Finally, this dissertation also shows that wiki has the potential to support group peer mentorship, but needs further research

Evolutionary framework for DNA Microarry Cluster Analysis

En esta investigación se propone un framework evolutivo donde se fusionan un método de clustering jerárquico basado en un modelo evolutivo, un conjunto de medidas de validación de agrupamientos (clusters) de datos y una herramienta de visualización de clusterings. El objetivo es crear un marco apropiado para la extracción de conocimiento a partir de datos provenientes de DNA-microarrays. Por una parte, el modelo evolutivo de clustering de nuestro framework es una alternativa novedosa que intenta resolver algunos de los problemas presentes en los métodos de clustering existentes. Por otra parte, nuestra alternativa de visualización de clusterings, materializada en una herramienta, incorpora nuevas propiedades y nuevos componentes de visualización, lo cual permite validar y analizar los resultados de la tarea de clustering. De este modo, la integración del modelo evolutivo de clustering con el modelo visual de clustering, convierta a nuestro framework evolutivo en una aplicación novedosa de minería de datos frente a los métodos convencionales