Information Technology (IT) and Institutional Research (IR) units working together with planning, a focus on collaboration, and a willingness to create partnerships can help accelerate their institution's efforts to improve the data landscape. This chapter includes an overview of the challenges facing these two functional areas, the benefits of a…

The increasing data about institutions of higher education and the availability of this data are described and evaluated. The data bases need further development and coordination of standards, exchange guidelines, and accessing procedures to be most beneficial. (Author/LBH)

Interinstitutional researchers face a variety of complex issues that need to be understood and dealt with to ensure the benefits of their involvement. Some issues are reviewed and future concerns are addressed. (Author/LBH)

Success in exchanging data with other institutions depends on the purpose of the exchange, the complexity of the data involved, the effort required to participate, and the frequency with which responses are requested. Common sense, diplomacy, and selling the responding institution on the benefits of participating assure a successful exchange. (MLW)

Creative responses of the poorer higher education institutions to the demands of production under restraints of minimal resource allocation are described. It is suggested that similar cooperative arrangements and group efforts could help other institutions facing financial restraints. Sources for additional information are cited. (Author/SF)

Technology can be an obstacle or an advantage to cooperative data sharing within and between colleges and universities. Taking a technology-oriented approach before the technology is ripe for general use can be counterproductive. Many technical difficulties can be overcome by encouraging consortium staff to promote new methods of information…

Organizations, programs, and other resources for data sharing in higher education are listed and described, with addresses provided. They include existing data-exchange programs and consortia, survey programs and databases, and a list of papers presented at the 35th Forum of the Association for Institutional Research. (MSE)

A case study is presented of an institutionally-based project for resource allocation and planning. The University of Michigan uses interinstitutional data to address the problem of assessing the equitability of staffing and funding among its schools and colleges. (Author/LBH)

A consortium-based, student-oriented interinstitutional research project for educational assessment is described. The College Research Center (CRC) experience suggests that a consortium can be an effective vehicle but that there are difficulties in cultivating interest and long-term commitment. (Author/LBH)

The Council's history and the development of its research program provide insights into the evolutionary nature of its interinstitutional research activities. A case study of the program, which has both consortial and coordinating characteristics, is described. (Author/LBH)

Benefits and potential problems with formal college and university programs of Interinstitutional data sharing are examined from an institutional perspective and the perspective of the institutional researcher. Benefits include access to data, networking and consulting, efficiency, increased researcher visibility, and better understanding of…

The growth of statewide coordinating boards now requires their formal periodic assessment. Reviews cautions and complexities in evaluating statewide boards, evaluation of product and process, and suggested criteria for evaluating statewide boards. (Editor/PG)

Criteria for evaluation of coordinating agencies should include the sensitivity of their procedures for consulting the coordinated institutions, and the extent to which they encourage voluntary interinstitutional cooperation. (Editor/PG)

Discusses the ideas presented in this volume on statewide coordination, relates them to other evaluation efforts, and describes how best they can be implemented. (Editor/PG)

Models for college and university Interinstitutional data sharing are redefined by examining the organization and activities of existing data-sharing groups across 11 dimensions: data-sharing purpose; nature of data-sharing structures; definer of process; calendar; scope of surveys; participant characteristics; source of data-sharing initiative;…