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An Evidence-Based Approach on Academic Management in a School of Public Health Using SMAART Model

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  • Ashish Joshi

    (Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA
    Academic and Student Affairs, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA)

  • Robyn Gertner

    (Academic and Student Affairs, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA)

  • Lynn Roberts

    (Academic and Student Affairs, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA
    Department of Community Health and Social Sciences, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA)

  • Ayman El-Mohandes

    (Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10027, USA)

Abstract

Data-driven modeling, action, and strategies have become popular, and the education community has witnessed increased interest in data-driven decision-making (DDDM). DDDM values and prioritizes decisions supported by high-quality, verifiable data that has been effectively processed and analyzed. The objective of our study is to describe the design, development, and implementation of a data-driven, evidence-based model of academic development in the context of CUNY Graduate School of Public Health and Health Policy (CUNY SPH) utilizing SMAART (Sustainability Multisector Accessible Affordable Reimbursable Tailored) model. The alignment of academic and student affairs within CUNY SPH brought with it several challenges. Defining roles and responsibilities across different student and academic affair units with a goal of collaborative leadership model and lack of meaningfulness were key challenges. It was important to listen to the experiences and recommendations of various individuals performing various functions in different capacities. A unified framework of key data indicators was needed to create a transparent and equitable model. An innovative interactive SMAART SPH dashboard designed, developed, and implemented to guide data-driven, evidence-based decision-making. Institutions can use a large amount of data from various sources to improve students’ learning experience, enhance research initiatives, support effective community outreach, and develop campus infrastructure to bring in sustainability.

Suggested Citation

  • Ashish Joshi & Robyn Gertner & Lynn Roberts & Ayman El-Mohandes, 2021. "An Evidence-Based Approach on Academic Management in a School of Public Health Using SMAART Model," Sustainability, MDPI, vol. 13(21), pages 1-18, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12256-:d:673511
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    References listed on IDEAS

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    1. KerryAnn O’Meara & Courtney Jo Lennartz & Alexandra Kuvaeva & Audrey Jaeger & Joya Misra, 2019. "Department Conditions and Practices Associated with Faculty Workload Satisfaction and Perceptions of Equity," The Journal of Higher Education, Taylor & Francis Journals, vol. 90(5), pages 744-772, September.
    2. Ashish Joshi & Mohit Arora & Bhavya Malhotra, 2017. "Usability Evaluation of a Portable Health Information Kiosk Using a SMAARTTM Intervention Framework," Global Journal of Health Science, Canadian Center of Science and Education, vol. 9(8), pages 153-153, August.
    3. KerryAnn O’Meara & Audrey Jaeger & Joya Misra & Courtney Lennartz & Alexandra Kuvaeva, 2018. "Undoing disparities in faculty workloads: A randomized trial experiment," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-15, December.
    4. Ashish Joshi & Arushi Arora & Chioma Amadi-Mgbenka & Nidhi Mittal & Shruti Sharma & Bhavya Malhotra & Ashoo Grover & Archa Misra & Menka Loomba, 2019. "Burden of household food insecurity in urban slum settings," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-24, April.
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