The field of computer science has a problem of representation-many groups are not represented in our classroom at levels approaching their composition in society. Unfortunately, the representation issue is a larger societal issue and begins well before students enter our institutions. Though we acknowledge that building inclusive and equitable classroom environments cannot increase representation by itself, it can have an impact on retention and inclusion for members of marginalized communities.

As proposed by Linda B. Nilson in Specifications Grading: Restoring Rigor, Motivating Students, and Saving Faculty Time, Specifications Grading is an assessment paradigm that relies on pass/fail grading of assignments and assessments, the structuring of course content into modules linked to learning outcomes, and the bundling of assignments and assessments within those modules. One intention of this type of course grading construct is to align assessment more closely with student attainment of intended learning outcomes. Many of the features of Specifications Grading make it more equitable. While there has been very visible work in incorporating Specifications Grading in some academic areas (e.g., in mathematics), examples of the use of Specifications Grading in computer science courses are less common. The goal of this workshop is to introduce the concepts of Specifications Grading and explain how to apply these concepts to a wide range of computing courses and class sizes. Each participant should leave the workshop with the ability to revise their course syllabus and assignments to incorporate Specifications Grading. Access to many examples and resources will be provided.

As proposed by Linda B. Nilson in Specifications Grading: Restoring Rigor, Motivating Students, and Saving Faculty Time, Specifications Grading is an assessment paradigm that relies on pass/fail grading of assignments and assessments, the structuring of course content into modules linked to learning outcomes, and the bundling of assignments and assessments within those modules. One intention of this type of course grading construct is to align assessment more closely with student attainment of intended learning outcomes. Many of the features of Specifications Grading make it more equitable. While there has been very visible work in incorporating Specifications Grading in some academic areas (e.g., in mathematics), examples of the use of Specifications Grading in computer science courses are less common. The goal of this workshop is to introduce the concepts of Specifications Grading and explain how to apply these concepts to a wide range of computing courses and class sizes. Each participant should leave the workshop with the ability to revise their course syllabus and assignments to incorporate Specifications Grading. The workshop presenters, having more than twenty-five years of combined experience implementing Specification Grading, will provide access to many examples and resources.

The field of computer science has a problem of representation - many groups are not represented in our classroom at levels approaching their composition in society. Unfortunately, the representation issue is a larger societal issue and begins well before students enter our institutions. Though we acknowledge that building inclusive and equitable classroom environments cannot increase representation by itself, it can have an impact on retention and inclusion for members of marginalized communities.

As proposed by Linda B. Nilson in Specifications Grading: Restoring Rigor, Motivating Students, and Saving Faculty Time, Specifications Grading is an assessment paradigm that relies on pass/fail grading of assignments and assessments, the structuring of course content into modules linked to learning outcomes, and the bundling of assignments and assessments within those modules. One intention of this type of course grading construct is to align assessment more closely with student attainment of intended learning outcomes. While there has been very visible work in incorporating Specifications Grading in some academic areas (e.g., in mathematics), examples of the use of Specifications Grading in computer science courses are less common. The goal of this workshop is to introduce the concepts of Specifications Grading and explain how to apply these concepts to a wide range of computing courses and class sizes. Each participant should leave the workshop with the ability to revise their course syllabus and assignments to incorporate Specifications Grading. Access to many examples and resources will be provided.

Presents the welcome message from the conference proceedings.

The paper presents the basic ideas behind the use of software agent technology for distributed simulation and data assimilation. A software agent is an autonomous computer program that operates on behalf of someone or something. A mobile agent has the ability to migrate during execution from machine to machine in a heterogeneous network, while a stationary agent executes only on the system on which it began execution. To understand the role of agents in distributed simulation, note that simulations often operate on static datasets and data sources. Many simulations would produce more accurate results if they could access dynamically changing data from other sources, such as sensors or even other simulations. From the perspective of one simulation, other simulations are data resources, producing information possibly relevant to the past, present, or future of the system being modeled. Software agents allow dynamic linking between distributed simulations and efficient monitoring of and access to remote data resources. Specifically, they conserve bandwidth, provide custom operations without precompiling or preloading, and adapt to support disconnected operations. The paper describes the development of a software agent based framework for dynamically linking distributed simulations and other remote data resources. The framework called ABELS (Agent-Based Environment for Linking Simulations) allows independently designed simulations to communicate seamlessly with no a priori knowledge of the details of other simulations and data sources. We discuss our architecture and current implementation developed using the D'Agents mobile agent system.

This paper describes experiences gained during the process of implementing a standard serial bench-mark (SLALOM) on a distributed computing system (Pleiades running ESP). The purpose of the authors experiments has been to maximize the speedup of a distributed implementation of SLALOM when compared to its serial implementation.>