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The Annual BUILD Snapshot: Tracking Alumni Outcomes

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HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13096))

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Abstract

As the number of alumni of the CSULB BUILD Student Training Program continues to grow, it has become vital to develop a systematic way to track each trainee’s graduate school enrollment and persistence. Developing a system that tracks post-graduate outcomes is not only important for determining the success of the program, but it also creates opportunities for the program to continue supporting its former trainees. A major challenge to tracking is that alumni are not very engaged in the process. To address this challenge, we developed the Annual BUILD Snapshot, a personalized unique Excel file designed to collect information on student activities during their time in the BUILD Program and after graduation. In this paper, we describe the development and implementation of the Annual BUILD Snapshot. We also discuss the strategies we used to launch the Snapshot, the administration process, and the outcomes and lessons learned from the process. Our findings have implications for similar training programs that need to track the short-term and long-term outcomes of their students and aim to remain connected to their alumni in unique and creative ways.

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Acknowledgments

This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Numbers UL1GM118979, TL4GM118980, and RL5GM118978. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Correspondence to Nancy Carrada Zuniga .

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Carrada Zuniga, N., Colbern, A. (2021). The Annual BUILD Snapshot: Tracking Alumni Outcomes. In: Stephanidis, C., et al. HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture. HCII 2021. Lecture Notes in Computer Science(), vol 13096. Springer, Cham. https://doi.org/10.1007/978-3-030-90328-2_22

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  • DOI: https://doi.org/10.1007/978-3-030-90328-2_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90327-5

  • Online ISBN: 978-3-030-90328-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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