Kohonen Self-organizing Feature Maps as a Means to Benchmark College and University Websites

Abstract

Websites for colleges and universities have become the primary means for students to obtain information in the college search process. Consequently, institutions of higher education should target their websites toward prospective and current students’ needs, interests, and tastes. Numerous parameters must be determined in creating a school website (e.g. number of links, page size, use of graphics, utilization of dynamic elements, and menuing options). This research details a decision support framework based upon Kohonen self-organizing feature maps to determine students’ specific preferences for school websites. This research attempts to remove some of the subjectivity in designing a school website by finding the commonalities among websites that students find appealing and effective. Self-organizing feature maps are employed as a clustering method to compare the school’s current website to other sites that students find both appealing and effective.