An Intelligent Assessment System of Teaching Competency for Pre-service Teachers Based on AHP-BP Method

Abstract

The Education Informatization 2.0 Action Plan issued by the Chinese Ministry of Education calls for further improvement on teachers’ teaching competency in the era of "Internet+ Education", which also brings new requirement for the training of pre-service teachers who are enrolled in university teacher education courses. This study put forward three principles to construct a new framework to assess the teaching competency for university students majoring in teacher education. Developed on the basis of the Analytic Hierarchy Process (AHP) methods, the assessment system included six dimensions contributed by 21 indicators. This system is supported by Back Propagation (BP) neural network and data label technology to realize intelligent assessment of teaching competency. The trial results of real data samples showed that the system could meet the requirements of large-scale assessment for Pre-service students in higher education sectors. The assessment framework could well cover pre-service teachers’ qualification standards, facilitate the assessment of their teaching competency, and provide a clear guidance for effective trainings for the pre-service teachers to meet the requirement of future teaching supported by the Internet technology.