Effect of an inservice on the teachers' knowledge of general school law, Section 504, and the Meta Consent Decree

It is generally assumed by educators that inservice training will make a significant difference in teacher knowledge of topics related to education. This investigation addressed that assumption by examining the effects of various factors, e.g., amount and timing of inservice training, upon teacher knowledge of educational law. Of special interest was teacher knowledge of the law as it pertained to ethnic and other characteristics of students in urban school settings. This study was deliberately designed to determine which factors should be later investigated in a more deterministic form, e.g., an experimental design.^ The investigation built upon that of Ogletree (1985), Osborne (1996) and others who focused on the importance of teacher development as a method to enhance professional abilities. The main question addressed in this study was, "How knowledgeable are teachers of school law, especially with regard to general school law, the Meta Consent Decree and Section 504 of the Rehabilitation Act of 1973."^ The study participants (N = 302) were from the Dade County School System, the fourth largest in the U.S. The survey design (approved by the System), specified participants from all levels and types of schools and geographic representations. A survey instrument was created, pilot tested, revised and approved for use by the district official representatives. After administration of the instrument, the resultant data was treated by several appropriate tests, e.g., multivariate analysis of variance (ANOVA).^ Several findings emerged from the analysis of the data: in general, teachers did not have sufficient knowledge of school law; factors, such as amount and level of education, and status and position were positively correlated with increased knowledge; factors such as years of experience, gender, race and ethnicity were not correlated with higher levels of knowledge. The most significant, however, was that when teachers had participated in several inservice training experiences, typically workshops, and, when combined with other factors noted above, their knowledge of school law was significantly higher. Specific recommendations for future studies were made. ^

Towards simulation and emulation of large-scale computer networks

Developing analytical models that can accurately describe behaviors of Internet-scale networks is difficult. This is due, in part, to the heterogeneous structure, immense size and rapidly changing properties of today's networks. The lack of analytical models makes large-scale network simulation an indispensable tool for studying immense networks. However, large-scale network simulation has not been commonly used to study networks of Internet-scale. This can be attributed to three factors: 1) current large-scale network simulators are geared towards simulation research and not network research, 2) the memory required to execute an Internet-scale model is exorbitant, and 3) large-scale network models are difficult to validate. This dissertation tackles each of these problems. ^ First, this work presents a method for automatically enabling real-time interaction, monitoring, and control of large-scale network models. Network researchers need tools that allow them to focus on creating realistic models and conducting experiments. However, this should not increase the complexity of developing a large-scale network simulator. This work presents a systematic approach to separating the concerns of running large-scale network models on parallel computers and the user facing concerns of configuring and interacting with large-scale network models. ^ Second, this work deals with reducing memory consumption of network models. As network models become larger, so does the amount of memory needed to simulate them. This work presents a comprehensive approach to exploiting structural duplications in network models to dramatically reduce the memory required to execute large-scale network experiments. ^ Lastly, this work addresses the issue of validating large-scale simulations by integrating real protocols and applications into the simulation. With an emulation extension, a network simulator operating in real-time can run together with real-world distributed applications and services. As such, real-time network simulation not only alleviates the burden of developing separate models for applications in simulation, but as real systems are included in the network model, it also increases the confidence level of network simulation. This work presents a scalable and flexible framework to integrate real-world applications with real-time simulation.^