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Educational Evaluation Models in the Big Data Era and their Paradigm Construction

Social Sciences in China (Chinese Edition)

No.12, 2019

 

Educational Evaluation Models in the Big Data Era and their Paradigm Construction

(Abstract)

 

Fan Yongfeng and Song Naiqing

 

In the era of big data in education, the question of fully exploiting the value of big data for educational practice, decision-making, evaluation and research while avoiding the concurrent risks is important for current education reform and development. By making quantitative descriptions and value judgments on the key elements of educational phenomena and their interrelationships, the education evaluation model enables one to obtain effective primary information from massive data and to turn “big data” into “small data.” It constitutes a strategic tool for China’s education reform and development, offers strong support for scientific decision-making in education, and is an important breakthrough in making education research more scientific. The construction of a paradigm for an education evaluation model involves a set of norms and a methodological basis. Its main contents are determining the model’s value orientation, clarifying the operational definition of the subjects of educational evaluation, constructing a system of educational evaluation indicators, determining the weighting of those indicators, generating an educational evaluation model and testing and correcting the model. A series of models set up by applying this paradigm at the macro, meso and micro levels will have a beneficial effect on research, decision-making, practice and evaluation in related fields.