Applying Statistical Analysis from Objective and Subjective Assessment Measures

August 13, 2015
Presented by Ainslie Nibert, Consultant, Nursing Leader, Evaluation and Assessment Expert in Healthcare, and Author. As an instructor, you spend a great deal of time and effort creating and administering tests to your students. But are you really getting the most out of your assessments? If you find yourself simply recording scores after each exam and telling yourself that you'll do a deeper dive into this test data later, you may be missing out on opportunities to improve students' performances on the very next exam, as well as to enhance your programmatic evaluation. Faculty should analyze several sources of data when making decisions about individual student knowledge and ability levels that relate to progression within a basic nursing or allied health program leading to licensure or certification. Among these sources, those which yield both subjective and objective data should be examined, both from a longitudinal perspective, as well as from an aggregate (cohort) perspective, particularly when program outcomes are being analyzed. Using both formative and summative data sources, faculty are equipped to conduct deeper statistical analyses of student performance. The focus of this presentation will center upon the value of these types of analyzes. Observing for statistically significant correlations of scores gathered across like content areas, as well as response patterns, can reveal a wealth of information about student competencies and programmatic effectiveness. In addition, careful scrutiny of variances seen with responses on one type of exam with the other may expose areas of concern with test construction that the faculty should address following a detailed review of item analysis information derived from these assessments. (Recorded on October 29, 2014, at 3pm ET)
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