Empowering Digital Education Monitoring and Evaluation with Big Data:Concepts,Models,and Pathways
The monitoring and evaluation of digital education is an important step in promoting and deepening the digital transformation of education.As a new generation of information technology,big data can deeply present the essential characteristics and structural relationships of digital education,providing technical support for achieving multidimensional and fine-grained education monitoring and evaluation.The monitoring and evaluation of digital education has gone through an advancement of concept from measuring teaching performance,data-driven evaluation to innovating certification models and enhancing value-added benefits.It has formed a diversified value orientation supported by the needs of subject development,dynamically generating data,intelligent integration analysis,and enhancing management efficiency.The monitoring and evaluation of digital education is based on scenarioized data,with classroom big data,online big data,and dual line blended big data as application scenarios.It monitors teaching phenomena,human-computer interaction,and activity events through physical perception,digital perception,and situational perception.In terms of evaluation methods,digital education evaluation has evolved into summative education evaluation based on centralized mathematical statistics,process education evaluation based on adjoint data mining,and predictive education evaluation based on generative artificial intelligence.The practical path of big data-driven education monitoring and evaluation includes establishing a data monitoring and evaluation system,implementing full chain data monitoring,conducting differentiated development evaluation,innovating data governance models,and constructing feedback decision-making mechanisms to better promote the high-quality development of education evaluation.
Big dataDigital educationEducation monitoring and evaluationEvaluation modePractical path
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