The expectation that educators will use data in the service of school improvement and planning is a major feature of national and local reform agendas. Prior research has found that the principal plays a critical role in making policymakers' visions for data use a reality at the school and classroom levels. Most prior studies, however, have not fleshed out how the principal functions as a key agent in influencing other key players in data use. This article will illustrate the actions of the principal, teachers, students, and district personnel through simulation models of principal leadership that we developed based on a case study of a high school implementing this reform. We use these models both as a framework for understanding our findings and as a way to enhance understanding of the processes by which educational reform is co-constructed through the simultaneous mediation of the multiple agents involved in the system.

We describe a new way of classifying uses of educational technologies, based on a four-part division suggested years ago by John Dewey: inquiry, communication, construction, and expression. This taxonomy is compared to previous taxonomies of educational technologies, and is found to cover a wider range of uses, including many of the cutting-edge uses of educational technologies. We have tested the utility of this taxonomy by using it to classify a set of "advanced applications" of educational technologies supported by the National Science Foundation, and we use the taxonomy to point to new potential uses of technologies to support learning.

Education is a complex system, which has conceptual and methodological implications for education research and policy. In this article, an overview is first provided of the Complex Systems Conceptual Framework for Learning (CSCFL), which consists of a set of conceptual perspectives that are generally shared by educational complex systems, organized into two focus areas: collective behaviors of a system, and behaviors of individual agents in a system. Complexity and research methodologies for education are then considered, and it is observed that commonly used quantitative and qualitative techniques are generally appropriate for studying linear dynamics of educational systems. However, it is proposed that computational modeling approaches, being extensively used for studying nonlinear characteristics of complex systems in other fields, can provide a methodological complement to quantitative and qualitative education research approaches. Two research case studies of this approach are discussed. We conclude with a consideration of how viewing education as a complex system using complex systems’ conceptual and methodological tools can help advance education research and also inform policy.

This paper is about networking failures as well as networking successes. A research strategy for comparing educational activities conducted across electronic networks was employed to examine the critical features of successes as well as failures in designing electronic communities. The analysis provides a set of guidelines for those who plan to use telecommunications as a tool for creating global communities.

This study identifies student variables that predict persistence and success in an undergraduate engineering program. Three logistic models were developed that predicted the probability of persisting successfully. Significant predictors included both cognitive and noncognitive variables; students who did well in science and mathematics courses and who were genuinely interested in engineering were more likely to persist and succeed. Predictor variables were not constant over time but changed as students progressed through the first two years of study, with performance in prerequisite science and mathematics courses emerging as the best predictors. The authors briefly discuss academic advising implications.