This phenomenological study expands upon Bean and Metzner's (1985) A Conceptual Model of Nontraditional Student Attrition framework by introducing a new Academic Variable, Learning Analytics (LA), and identifying two specific Social Integration Variables (Sense of belonging; Microaggressions). LA was not a factor in 1985 when the original model was created. However, the researcher believes that learning analytics should be added to the model to account for the changing landscape of academic advising in higher education institutions in the 21st century. This study explored the impact of learning analytics on academic advisors' perceptions of their nontraditional online advisees. The participants in this study comprised eight academic advisors with more than one year of experience working with nontraditional online students who also identified that they use learning analytics as part of their advising practices. Using a modified approach to Seidman's Three-Series Interview Protocol (2019), the researcher conducted a series of two required interviews with an optional third interview per participant (seven of the eight participants completed all three interviews). During the first interview, the researcher asked a series of questions relative to institutional advising practices during the first portion of the interview and then introduced three vignettes to serve as a framework for a line of questioning that would allow each participant to apply advising practices from their institution to respond to the questions in a standardized approach. Interview II began by showing the 2nd series of vignettes, which were the same three vignettes from Interview I. Two of the vignettes had additional pieces of information added to them, and one remained unchanged. The researcher asked the same questions of participants that were asked after the 1st series of vignettes during the first portion of the interview. The second half of Interview II focused on Learning Analytics practices. Interview III provided an opportunity to make meaning of how participating in this study did or did not impact each participant's advising practice and their final thoughts about the use of learning analytics in academic advising. This study identified how lack of LA, lack of training on interpreting LA, bias, and personal experience impact perceptions. The researcher believes that standardized practices on how LA is being used across IHE and how to interpret and apply LA should be required before allowing advisors to use LA to engage with students. The researcher found examples of advisors making negative assumptions about students in the absence of data and instances of using the LA to make biased statements about the students presented in the vignettes. The researcher believes that comprehensive training on the ethical use of LA should be required for all advisors using LA in the advising process. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]