Campus Websites' Information Quality Measurement Model and Potential Students' Interest Prediction
Campus Websites' Information Quality Measurement Model and Potential Students' Interest Prediction

Summary/Abstract: The importance of search engine features on campus websites will affect how prospective students can be interested in determining where to study. Although the evaluation has been widely discussed and has so far produced positive results, the indicators are too general, so there is no deep enough focus on the influence of interest. Therefore, to develop an evaluation model, The model for assessing and forecasting potential students' interests was created by fusing linear regression with the critical performance analysis paradigm. Six university websites are used as objects. Two categories of independent variables (X) use 24 questions, while (Y) dependent uses 15 questions. The reliability score of X is 0.832, while Y is 0.731. The important performance analysis (IPA) is divided into three quadrant results by importance performance analysis: information quality in quadrant A, use of information technology in quadrant B, and user experience in quadrant A. The findings of the regression-based prediction test indicate that all variables can function as models for prediction, and the test results have high significance. From these results, it is stated that the quality of information managed by good technology will have an influence on prospective students.

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