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CUNY SPH: An Evidence based model of Academic Management using SMAART Informatics approach
March 24, 2021 @ 2:42 pm - 2:54 pm IST
2021 ASPPH Annual Meeting
CUNY SPH: An Evidence based model of Academic Management using SMAART Informatics approach
It is critical to leverage data driven decision-making and spurn innovation in higher education by having optimal strategy that prioritizes data standardization, integration, transparency, quality and reliability and make most of their resources. Immediate need is to establish robust data systems, combined with a well-coordinated, multi-stakeholder collaboration across administrative and academic units to drive evidence based modeling of academic management. We describe SMAART informatics framework to design, develop, and implement an internet enabled informatics platform, that facilitates data driven, evidence based models of academic development in the context of CUNY Graduate School of Public Health and Health Policy. The framework is conceptualized using principles of Data, Information and Knowledge, Human Centered approach, Cognitive Fit Theory, Information Processing Theory and humanistic, behavioral and learning theories. A step by step approach towards implementation of this technology enabled framework included creating a transparent and an equitable model through range of activities including (a) identifying key stakeholders and their engagement, (b) defining essential data elements and integration of data related to faculty workload data, policy for compensation of designated leadership roles, classroom staffing with rules of adjunct and college assistant allocations, and data across range of student support services such as office of registrar, international office, career, experiential learning, writing and quantitative services and student advisement. The aim is to create a unified data framework using SMAART Informatics approach to bring together faculty, student and student support services data on one common platform. To the best of our knowledge, it is the first study outlining the value of implementing collaborative, coordinated, data driven decision making approaches across various administrative and academic units towards enhancement of a transparent, and an equitable environment of academic success. This will enable administrators to determine successes and challenges, identify areas of improvement, and help evaluate effectiveness of programs.