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

Decentralized information flow control for databases

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 177-194).Privacy and integrity concerns have been mounting in recent years as sensitive data such as medical records, social network records, and corporate and government secrets are increasingly being stored in online systems. The rate of high-profile breaches has illustrated that current techniques are inadequate for protecting sensitive information. Many of these breaches involve databases that handle information for a multitude of individuals, but databases don't provide practical tools to protect those individuals from each other, so that task is relegated to the application. This dissertation describes a system that improves security in a principled way by extending the database system and the application platform to support information flow control. Information flow control has been gaining traction as a practical way to protect information in the contexts of programming languages and operating systems. Recent research advocates the decentralized model for information flow control (DIFC), since it provides the necessary expressiveness to protect data for many individuals with varied security concerns.However, despite the fact that most applications implicated in breaches rely on relational databases, there have been no prior comprehensive attempts to extend DIFC to a database system. This dissertation introduces IFDB, which is a database management system that supports DIFC with minimal overhead. IFDB pioneers the Query by Label model, which provides applications with a simple way to delineate constraints on the confidentiality and integrity of the data they obtain from the database. This dissertation also defines new abstractions for managing information flows in a database and proposes new ways to address covert channels. Finally, the IFDB implementation and case studies with real applications demonstrate that database support for DIFC improves security, is easy for developers to use, and has good performance.by David Andrew Schultz.Ph.D