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With the constantly advancing of university engineering education accreditation, in the curricular of assessment of teaching quality, establishing an effective quality guarantee system that meets the standard of engineering education accreditation becomes one of issues that need to be addressed urgently in higher education reform. The paper proposes a new Higher Engineering Education Accreditation evaluation scheme to investigate the issue of teaching evaluation in higher education where decision management cycle makes a decision based on integrated expert opinions and generated knowledge in which machine learns, analyzes huge chunks of education data and makes predictions. A collaboration decision mechanism is implemented to assist to make multi-target cooperative decisions for evaluation of teaching, which provides more high-quality expert opinions for teaching. A practical case study has been successfully validated for the adaptability and practicability of the quality assurance scheme where Bayesian techniques process many variables and large of observations to achieve expert opinions integration. The scheme reached a degree of predictive ability, generalization ability, and self-improvement and it can improve the efficiency of teaching management decision.

A Quality Assurance Scheme of Higher Engineering Education Accreditation Based on Expert Opinions Integration