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Human-Centered, Tech-Enabled: Scalin...

Halmo, Holly,

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Human-Centered, Tech-Enabled: Scaling Academic Advising in Higher Education Through Predictive Analytics and Organizational Change an Innovation Study /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Human-Centered, Tech-Enabled: Scaling Academic Advising in Higher Education Through Predictive Analytics and Organizational Change an Innovation Study // Holly Halmo.
Author:	Halmo, Holly,
Description:	1 electronic resource (207 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-08, Section: A.
Contained By:	Dissertations Abstracts International86-08A.
Subject:	Higher education administration. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31838897
ISBN:	9798304909952

Human-Centered, Tech-Enabled: Scaling Academic Advising in Higher Education Through Predictive Analytics and Organizational Change an Innovation Study /
Halmo, Holly,

Human-Centered, Tech-Enabled: Scaling Academic Advising in Higher Education Through Predictive Analytics and Organizational Change an Innovation Study /Holly Halmo. - 1 electronic resource (207 pages)

Source: Dissertations Abstracts International, Volume: 86-08, Section: A.

This study examines the potential of integrating predictive analytics into undergraduate academic advising at Vernon University (VU, a pseudonym) to enhance proactive advising and improve student retention, aiming to raise the retention rate from 95% to 98%. Advising at VU is framed as a developmental partnership that aligns with the university's teaching mission to support students' academic, personal, and professional growth and is grounded in the values of empowerment, inclusivity, adaptability, and holistic care; VU academic advising strives to foster a supportive and connected community where students can thrive. While the research underscores a strong link between academic advising and retention, achieving this vision at scale requires technological innovation and cultural transformation.Proactive advising, supported by data-driven insights, offers a promising solution to identify students needing support before they reach critical academic barriers and depart the university. The study examines advisors' attitudes and perceptions regarding using a predictive analytics tool in advising and students' expectations and potential reactions to receiving proactive outreach the tool prompted. Surveys conducted with VU first-year students and academic advisors provide insights into how such a tool could be implemented effectively and what operational and cultural barriers must be addressed.The findings indicate that students see value in and expect proactive outreach and advising, and advisors see potential value in predictive analytics, particularly in the early identification of at-risk students. However, there is some apprehension about how these tools might decrease the human-centric nature of advising. The study proposes a model for advising that emphasizes the importance of predictive tools to engender and enhance rather than replace personal interactions between students and advisors.This research underscores the importance of a change management approach that respects the organization's established culture of human-centered support while emphasizing the need to integrate technology seamlessly into academic advising. By positioning predictive analytics as a complement to, rather than a replacement for, the advising process, the study provides actionable strategies for implementing these tools. These recommendations aim to address organizational barriers, foster a proactive, student-centered support culture, and help VU achieve its ambitious retention goals.

English

ISBN: 9798304909952Subjects--Topical Terms:

2122863
Higher education administration.
Subjects--Index Terms:

Academic advising

Human-Centered, Tech-Enabled: Scaling Academic Advising in Higher Education Through Predictive Analytics and Organizational Change an Innovation Study /
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520 $a This study examines the potential of integrating predictive analytics into undergraduate academic advising at Vernon University (VU, a pseudonym) to enhance proactive advising and improve student retention, aiming to raise the retention rate from 95% to 98%. Advising at VU is framed as a developmental partnership that aligns with the university's teaching mission to support students' academic, personal, and professional growth and is grounded in the values of empowerment, inclusivity, adaptability, and holistic care; VU academic advising strives to foster a supportive and connected community where students can thrive. While the research underscores a strong link between academic advising and retention, achieving this vision at scale requires technological innovation and cultural transformation.Proactive advising, supported by data-driven insights, offers a promising solution to identify students needing support before they reach critical academic barriers and depart the university. The study examines advisors' attitudes and perceptions regarding using a predictive analytics tool in advising and students' expectations and potential reactions to receiving proactive outreach the tool prompted. Surveys conducted with VU first-year students and academic advisors provide insights into how such a tool could be implemented effectively and what operational and cultural barriers must be addressed.The findings indicate that students see value in and expect proactive outreach and advising, and advisors see potential value in predictive analytics, particularly in the early identification of at-risk students. However, there is some apprehension about how these tools might decrease the human-centric nature of advising. The study proposes a model for advising that emphasizes the importance of predictive tools to engender and enhance rather than replace personal interactions between students and advisors.This research underscores the importance of a change management approach that respects the organization's established culture of human-centered support while emphasizing the need to integrate technology seamlessly into academic advising. By positioning predictive analytics as a complement to, rather than a replacement for, the advising process, the study provides actionable strategies for implementing these tools. These recommendations aim to address organizational barriers, foster a proactive, student-centered support culture, and help VU achieve its ambitious retention goals.
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