Appropriate experiences for the gifted science student

Gifted/talented education is slowly expanding as more funds for programs are provided by states and more universities off er graduate programs.     

Public purpose and the preparation of teachers for rural schools

Abstract

Rural communities need rural teachers who can “ground” traditional school subjects in local realities and dilemmas and at the same time fashion instructional approaches consonant with larger intellectual, ethical, and social purposes. Such teachers are assets rather than burdens to their communities. Only such teachers can cultivate an ethic of responsibility for the health and vitality of the communities of which they and their students are critical components.

This essay examines the role of the university in professionalizing rural teachers. It contends that narrowly utilitarian ends prevail in teacher education programs, and that, in the absence of a substantive definition of educations public purpose, this instrumentalism creates teachers who are ill‐prepared to contribute in meaningful ways to the intellectual life of the communities in which they work. Teacher preparation programs should abandon the instrumental focus. Programs that prepare rural teachers, in fact, confront unique challenges and opportunities to include three themes at their centers: Sustainability, Social Justice, and Democracy.     

SPREAD: A Distributed Simulation Toolkit

This article describes “SPREAD”, a simulation toolkit, and its use in building “Virtual Robots”, a simulation of multiple mobile robot vehicles used in the teaching of computer science at university level. A novel aspect of the simulator is the use of PVM (Parallel Virtual Machine) to achieve high performance at low cost by using spare CPU cycles on large numbers of networked workstations.     

Application of the Levenshtein Distance Metric for the Construction of Longitudinal Data Files

The analysis of longitudinal data in education is becoming more prevalent given the nature of testing systems constructed for No Child Left Behind Act (NCLB). However, constructing the longitudinal data files remains a significant challenge. Students move into new schools, but in many cases the unique identifiers (ID) that should remain constant for each student change. As a result, different students frequently share the same ID, and merging records for an ID that is erroneously assigned to different students clearly becomes problematic. In small data sets, quality assurance of the merge can proceed through human reviews of the data to ensure all merged records are properly joined. However, in data sets with hundreds of thousands of cases, quality assurance via human review is impossible. While the record linkage literature has many applications in other disciplines, the educational measurement literature lacks details of formal protocols that can be used for quality assurance procedures for longitudinal data files. This article presents an empirical quality assurance procedure that may be used to verify the integrity of the merges performed for longitudinal analysis. We also discuss possible extensions that would permit merges to occur even when unique identifiers are not available.