数智时代信息资源管理学科本科专业人才培养质量的多维评价研究OACHSSCD

[Purpose/Significance]Digital-intelligence transformation and China's strategy for building a leading country in education have created new requirements for evaluating undergraduate talent cultivation in information resource management(IRM).Generic undergraduate evaluation frameworks provide essential quality safeguards but do not fully re-present the discipline's shift toward data governance,knowledge services,intelligent decision-making,interdisciplinary integration,and digitally enabled learning.This study therefore developes a discipline-responsive,process-oriented framework linking cultivation objectives,resource inputs,educational processes,and student outcomes.[Method/Process]Guided by the Context-Input-Process-Product(CIPP)model,the study synthesized relevant literature and national policy documents to identify core evaluation elements,establish an initial indicator pool,and classify the indicators under the four CIPP dimensions.Fourteen experts in IRM and educational evaluation participated in three rounds of consultation con-ducted from March to June 2026.The first round combined five-point importance ratings with open-ended comments;the second used revised five-point ratings and feedback confirmation;and the third used seven-point ratings to confirm indica-tors on which disagreement remained.Indicator decisions combined mean importance scores and coefficients of variation with qualitative judgments concerning theoretical fit,practical operability,and relevance to the digital-intelligence era.Feedback from 18 students at different levels was also considered.Weights for the dimensions and first-level indicators were derived through the Analytic Hierarchy Process using aggregated pairwise comparisons and consistency tests,whereas second-level weights were calculated from normalized seven-point expert ratings.[Result/Conclusion]The resulting frame-work contains four dimensions,12 first-level indicators,and 65 second-level indicators.Cultivation outcomes received the largest dimensional weight(34.436%),followed by cultivation objective positioning(27.518%),cultivation process empowerment(19.521%),and cultivation resource support(18.525%).The dimensional judgment matrix showed satisfac-tory consistency(CR=0.018).Kendall's W values across the three consultation rounds were 0.527,0.659,and 0.587,respectively(all p<0.001),indicating statistically significant concordance,although convergence was not strictly mono-tonic.Responsiveness to industry demand ranks first among the second-level indicators,while alignment with national strategy and fit with regional socioeconomic development tie for second.Research and knowledge-creation outcomes and practical application and social-service outcomes also received relatively high weights,reflecting an emphasis on trans-lating disciplinary learning into observable academic and societal contributions.Digital-intelligence requirements are repre-sented across faculty composition and capability,curriculum and resource development,technology-enabled teaching and learning support,and student digital-intelligence literacy.The framework clarifies the quality-generation chain from objec-tives to outcomes and distinguishes goal statements,resource provision,process implementation,and outcome evidence.It provides an expert-informed basis for subsequent evaluation but is not yet an empirically validated assessment instru-ment;operational definitions,measurement thresholds,weight stability,and performance in institutional applications require further testing.