Quality Evaluation of Collaborative Education Between Schools and Enterprises Based on Cloud Model and Entropy

Addressing the long‐standing issue that “existing indicators are outdated and misaligned with social demand” in evaluating talent cultivation quality through industry–education integration, this study develops an indicator system within the CIPP (Content, Input, Process, Product) framework. The system includes 4 primary and 11 secondary indicators. It is operationalized using a hybrid entropy‐like weight cloud‐model method, which transforms qualitative indicators into normalized cloud drops for quantitative analysis. Taking a petroleum university as an example, we illustrate the complete workflow of indicator deployment and model application and compare the proposed method with the conventional analytic hierarchy process (AHP). Results show that: (1) the indicator system closely reflects current social expectations for graduate competence and (2) the entropy‐like weight cloud‐model approach offers stronger practicality and operability. This study provides higher education institutions with a replicable indicator system and an extensible evaluation protocol for self‐assessment and continuous quality improvement of industry–education integrated talent cultivation.