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Implementing Academic Analytics and the Impact to Academic Advising
dc.contributor.advisor | Twombly, Susan | |
dc.contributor.author | Coffin, Abigail | |
dc.date.accessioned | 2019-01-01T18:59:27Z | |
dc.date.available | 2019-01-01T18:59:27Z | |
dc.date.issued | 2018-05-31 | |
dc.date.submitted | 2018 | |
dc.identifier.other | http://dissertations.umi.com/ku:15885 | |
dc.identifier.uri | http://hdl.handle.net/1808/27548 | |
dc.description.abstract | Institutions are facing pressure to improve retention and graduation rates. Because of the positive impact that academic advising can have on these metrics and the growing use of academic analytics in higher education, spending on Integrated Planning and Advising Services (IPAS) is higher than ever before. IPAS tools promise to streamline advising efforts, alert advisors of students at risk of dropping out, nudge students to engage in and out of the classroom, predict which students will be successful in rigorous courses and majors, and ultimately, improve retention rates. With vendors rapidly entering and expanding the IPAS market, institutions are encouraged to get in the game, or risk losing their share of the market. For this study, comparative case study methods were used to understand why two public, 4-year, doctoral degree-granting institutions implemented the Education Advisory Board’s Student Success Management System (EAB SSMS), the steps followed during implementation, the impact implementation of such a system plays on advising work, and the perception of impact to any existing advising approach or philosophy. The study concludes that strategic planning that included increasing student success metrics led to the implementation of the SSMS. Creating buy-in, communication with advising leaders and front-line advisors, and making decisions about how the use of the tool would be required or encouraged affected individual campus’ implementations. Each institution demonstrated that gaps in advising tool functionality was addressed by the EAB SSMS and that advisors with less experience and those who demonstrated more flexibility in approach and with technology were most successful in adjusting to the implementation of the tool. The institutions differed in the approach that was in place for academic advising, and use of the tool did not make any substantive change to the advising approach in place. Four additional conclusions are offered from the study: (1) Despite a proliferation of advising tools, gaps in function still exist, (2) Resistance to change impacts implementation, even if the outcome is desired, (3) Centralization plays a significant role in the success of the tool implementation and (4) Absence of a developmental advising approach may lead to more prescriptive advising actions. The findings of this study can assist administrators in setting expectations for a successful implementation of an IPAS tool and guide advising directors on impacts to expect through an implementation process. | |
dc.format.extent | 134 pages | |
dc.language.iso | en | |
dc.publisher | University of Kansas | |
dc.rights | Copyright held by the author. | |
dc.subject | Higher education administration | |
dc.subject | academic advising | |
dc.subject | academic analytics | |
dc.subject | advisor | |
dc.subject | case study | |
dc.subject | higher education | |
dc.subject | predictive analytics | |
dc.title | Implementing Academic Analytics and the Impact to Academic Advising | |
dc.type | Dissertation | |
dc.contributor.cmtemember | Wolf-Wendel, Lisa | |
dc.contributor.cmtemember | Roney, Marlesa | |
dc.contributor.cmtemember | Parker, Eugene | |
dc.contributor.cmtemember | Storkel, Holly | |
dc.thesis.degreeDiscipline | Educational Leadership and Policy Studies | |
dc.thesis.degreeLevel | Ed.D. | |
dc.identifier.orcid | ||
dc.rights.accessrights | openAccess |
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