The role of AI assisted socio-cultural frameworks in academic change and higher education growth
by Ying Pan; Pingyu Yang
International Journal of Technology Management (IJTM), Vol. 86, No. 2/3/4, 2021

Abstract: The 'growth' of academics in higher education is focused on quality improvements in teaching. However, the analysis has shown that the sense of academics significantly affects their practices that have been unaddressed due to inconsistent contextual conditions. This paper proposes a framework to study teachers' workplaces on the subjective factors that improve educational enhancement, supported by artificial intelligence (AI). Here, the administrative documents are analysed in the theory of history and culture framework, and it provides a technique for both traditional data analysis and modelling estimation of individual output in the feed-forward neural networks. A traditional statistical procedure is used to evaluate the variables that influence the success of students. Several differences in the teacher's socio-cultural context are identified based on the performance of the feed-forward neural network model, and it is measured by error rate reduction of 0.33, uncertainty matrix, the performance level of students. The feed-forward network model is the platform, and it is useful for predicting future academic achievement of students. Departmental teaching cultures and behavioural practices have affected both positive and negative behaviour in higher education teaching, which has been firmly addressed in this paper.

Online publication date: Wed, 20-Oct-2021

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