Research on an early warning model of effectiveness evaluation in ideological and political teaching based on big data

Abstract

Ideological and political (IAP) education is an important part of higher education, which plays a fundamental role in all-round education mechanisms and other fields. Under the vigorous development of big data technology, the crisis of IAP teaching effectiveness in colleges and universities is restricted by the non-linear development path, incomplete information collection, irregular data distribution, difficulty in quantifying index design and so on. Therefore, by analysing the application foundation of big data in IAP teaching evaluation, this paper puts forward an early warning model of IAP teaching effectiveness based on SVM algorithm design and decision analysis of a BP neural network and quantifies the quality of IAP teaching by constructing an index system of IAP evaluation, early warning evaluation value and early warning limit value, which is helpful to realise all-round dynamic early warning of IAP education in colleges and universities.

Keywords

• big data
• iap teaching
• early warning model