Construction and practice of a university teaching laboratory usage efficiency evaluation system based on ANP-FCE
[Objective]At present,research on the construction of evaluation systems for the efficacy of university teaching laboratories and on reformation of laboratory assessment methods is limited in China.In response to the existing issues in the current evaluation systems,particularly the irrational calculation of indicator weights and the challenges in quantifying qualitative indicators,this study synergizes the analytic network process(ANP)with the fuzzy comprehensive evaluation(FCE)method.Using specialized auxiliary tools,yaanp and yafce,we developed an ANP-FCE-based evaluation framework tailored for university teaching laboratories.This framework substantially refines the scientific approach to ranking indicator weights and enhances the precision of the assessment results,thereby offering a more robust and accurate evaluation system for the effective use of teaching laboratories in higher education institutions.[Methods]A set of assessment indicators comprising 4 primary,11 secondary,and 32 tertiary indicators was created in the present study.Drawing from the evaluation indices proposed in related literature and considering the actual conditions of university teaching laboratories,ANP was employed instead of the commonly used analytic hierarchy process in current technologies for calculating index weights.A complete ANP network structure model was constructed in this study.The model construction began with the establishment of an initial judgment matrix.Following a specific sequence,the cluster weight supermatrix,weighted supermatrix,unweighted supermatrix,weighted supermatrix,and limit supermatrix were computed.This process resulted in ranking index weights based on ANP,which overcomes the limitations of existing technologies that neglect the interconnectivity among indices and the mitigation of subjective biases.FCE was used to formulate an index evaluation scheme,thereby enhancing its scientific rigor and rationality.This set of fuzzy comprehensive evaluations was then used to calculate a weight distribution vector.By applying the principle of maximum membership and using the fuzzy synthesis algorithm,the evaluation result for laboratory usage efficiency was obtained,and then a new evaluation scheme based on FCE was developed.This scheme aimed to quantitatively assess qualitative indicators,thereby enhancing the accuracy and credibility of the evaluation results.[Results]An empirical study was conducted at a specific university to determine the efficacy of the evaluation system.To gauge content satisfaction,the importance given to various indices,and the overall evaluation plan,a survey was administered to 371 individuals who benefited from the university's services.These 371 individuals included leaders,teaching staff involved in experimental teaching,and laboratory technicians of the 15 units being evaluated.The satisfaction survey incorporated five levels:very satisfied,satisfied,average,dissatisfied,and very dissatisfied.The collected data indicated satisfaction rates of 90.24%for index content,90.47%for index weights,91.02%for the evaluation scheme,and 90.58%overall.[Conclusions]Combining ANP and FCE can enhance the scientific and rational allocation of index weights and the precision and truthfulness of the evaluation outcomes.The ANP-FCE-based assessment system for university teaching laboratory usage efficiency constructed in this paper enhances the construction and management of university laboratories,improves the efficiency of laboratory usage,and amplifies the role of laboratories in talent cultivation,scientific research,and social services.The system has achieved the anticipated effects in practice and holds important practical implications and value for promotion.
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