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In this paper, we present the Systems Engineering Initiative for Student Success (SEISS) framework we are developing for enabling educational organizations to scan, evaluate and transform their operations to achieve their diversity, equity, and inclusion goals in student recruitment, retention, and graduation. The underlying structure and logic in our SEISS framework is that an organization such as a college of engineering is a sociotechnical system (STS) consisting of a social subsystem and a technical subsystem. The social subsystem consists of people, their roles and is a model of who talks to whom about what. The technical subsystem consists of all the activities, programs, policies, and operations that help the organization achieve its goals. In a sociotechnical system, the social and technical subsystems are interdependent in their functioning, and they must be jointly optimized from an organizational design perspective. Our SEISS framework which views a college or a similar organizational unit as a sociotechnical system lends the organizational designer a unique systems lens with which to view, analyze and design the operations and organize the capacities and resources in the college. The systems lens views an organizational unit, its sub-systems, components, and its corresponding capacities not in isolation, but as entities that interact with each other. With support from an NSF IUSE grant, we have been developing the SEISS framework and have piloted the framework in a predominantly white college of engineering to identify existing and potential technical and social system capacities for underrepresented minority (URM) students to succeed in the college. Preliminary results from our qualitative analyses of URM student interviews reveal the utility of the SEISS framework and the STS lens in unearthing the barriers and enablers for these students in the social and technical subsystems in the college. We also model the interactions between the social and technical subsystem elements in the SEISS framework, revealing latent opportunities for leveraging the connections between the social and technical subsystem capacities and resources.
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A Linked Data Mosaic for Policy-Relevant Research on Science and Innovation: Value, Transparency, Rigor, and Community
This article presents a new framework for realizing the value of linked data understood as a strategic asset and increasingly necessary form of infrastructure for policy-making and research in many domains. We outline a framework, the ‘data mosaic’ approach, which combines socio-organizational and technical aspects. After demonstrating the value of linked data, we highlight key concepts and dangers for community-developed data infrastructures. We concretize the framework in the context of work on science and innovation generally. Next we consider how a new partnership to link federal survey data, university data, and a range of public and proprietary data represents a concrete step toward building and sustaining a valuable data mosaic. We discuss technical issues surrounding linked data but emphasize that linking data involves addressing the varied concerns of wide-ranging data holders, including privacy, confidentiality, and security, as well as ensuring that all parties receive value from participating. The core of successful data mosaic projects, we contend, is as much institutional and organizational as it is technical. As such, sustained efforts to fully engage and develop diverse, innovative communities are essential.
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- PAR ID:
- 10369098
- Date Published:
- Journal Name:
- Harvard data science review
- Volume:
- 4
- Issue:
- 2
- ISSN:
- 2644-2353
- Page Range / eLocation ID:
- https://hdsr.mitpress.mit.edu/pub/u073rjxs/release
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1162/99608f92.1e23fb3f
