Affiliations: [a]
Yunnan Technology and Business University, Kunming Yunnan, China
| [b] Department of Environmental Engineering, University of Management and Technology, USA
Correspondence:
[*]
Corresponding author. Xinzhen Yin, Yunnan Technology and Business University, Kunming Yunnan, 651700, China. E-mail: [email protected] and Baker Dylan, Department of Environmental Engineering, University of Management and Technology, USA. E-mail: [email protected].
Abstract: At present, most of the comparative education research concentrated in the macro education field such as international education, which has a significantly influenced the future education. Under this circumstances, this paper studied the development choices of comparative education in colleges and universities in the era of big data. Firstly, a new recommendation algorithm is proposed based on the characteristics of education big data. The comparative evaluation of the matching mode of colleges and universities is studied. Subsequently, we designed a new corresponding differential classification teaching mode on the basis of the naive Bayesian algorithm of comparative education in colleges and universities. At last, we designed a set of experiments to evaluate the proposed classification system. By comparing the development of comparative education platforms in colleges and universities, the optimal utilization combination of colleges and universities in the era of big data is realized to select the best development direction.
Keywords: Big data, colleges and universities, comparative education, development
choice
