Monitoring of Abnormal Score in Provincial Academic Degrees Dissertation and Thesis through Double-Blind Review: A Case on Shanghai

摘要

Aimed at abnormal score from evaluation experts, real data from Shanghai double-blind sampling system of graduate dissertation and thesis between 2013 and 2014 have been in depth analysis and mining. Some basic judgment rules of abnormal score are summed up, and monitoring model for abnormal score is proposed. By the least squares method and the multiple regression models, the equation of monitoring model for abnormal score is constructed. Finally, the abnormal monitoring coefficient of five evaluation indicators on dissertation and thesis, including topic selection, innovativeness, academic nature, applicability and accuracy, are generated by real data from Shanghai double-blind sampling system of graduate dissertation and thesis between 2013 and 2014. The goodness fit test of error range constant on monitoring model for abnormal score is operated by real data from double-blind review on graduate dissertation of Master of Engineering in Shanghai Jiao Tong University between 2013 and 2014. It is strengthened the association between items and sub-items of double-blind review, and provided effective data resource for Shanghai Degree & Graduate Education Informatization Platform to construct a re-evaluation system.