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Presentation 4K1. Statistics and the Practice of Institutional Research

Gerald W McLaughlin (USA)


Presentation Abstract
Training institutional research professionals to use statistics is a complex and challenging task. First one must develop a functional model of institutional research including its traditional and emerging roles. From these, one must determine the specific statistical and analytical tools required. Next the knowledge, skills and abilities required to use these tools to do effective institutional research must be understood. A final point discussed is IR professionals who are effective must be able to teach others to use and interpret statistical results.

The functional definition of IR is described from the tracks used to organize the professional activity of the association. These include activities in the areas of 1) Enrollment management and student affairs, 2) Institutional effectiveness, student learning, and outcomes assessment, 3) Academic program and faculty issues, 4) Resource management and quality improvement, and 5) Policy analysis, planning, and governance. In addition, several recent publications are used to describe what an IR professional does.

The specific tools or statistical methodologies that are important in IR depend greatly on the situation of the individual and the academic background of their audience. If the IR person is in the business side of the institution, then they will be more likely to need the analytical techniques found in the schools of commerce such as in cost accounting, finance and economics. If they are in the academic side, they are more likely to need the techniques from the social and behavioral sciences. The major types of methodologies discussed with examples include descriptive statistics, non-parametric statistics, multivariate statistics, regression/correlation, and comparative/ANOVA statistics. The need to know sampling and research design must also be taught.

The work done by Terenzini (1993) establishes that IR professionals need to operate with three types of intelligence. The first is the technical knowledge of the tool. This requires that the individual have the ability to use the tool, know the methodology, have software or other computational capability, and be familiar with the interpretation of results and the basic assumptions of the tool. This is the type of ability that one can anticipate from a statistics class from a statistics department. The second type of intelligence involves the skill with issues in higher education and knowing how these issues fit the statistic methodologies. This involves knowing when and how to apply the various techniques. What assumptions are met and how this meshes with the robustness of the techniques when various assumptions are violated? The third level of intelligence is contextual. This involves understanding the how business is done in the specific institution to include what individuals can learn from various levels of analysis and also the position in the decision process of the various individuals and the key issues.

The advanced IR professional will be challenged to have the ability to use the statistic, the skill to select when and why to use which statistic, and how to use the results to support decision-making and reduce organizational uncertainty. Do they follow steps to lead to organizational and student centered learning?


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