Mike Dial and Paige McKeown, University of South Carolina
Early Intervention Background
Seidman (2012) proposed a formula for student retention RET = E ID + (E + IN + C) IV (p. 272). He suggests that student retention may be achieved by the early identification of student needs plus early, intensive, and continuous intervention. Similarly, Tampke (2013) suggests that “effective intervention” occurs “at the first indication of academic difficulty” through a “systematic method of recording and communicating student behaviors that contribute to student attrition” (pp. 523–524). Consistent with previous literature (Barefoot, Griffin, & Koch, 2012; Habley, Bloom, & Robbins, 2012), the 2017 National Survey of the First-Year Experience (NSFYE) (Estrada & Latino, 2019) found early alert programming to be a prominently featured initiative at a majority (79.4%) of institutions.
Estrada and Latino (2019) report that effective intervention requires the identification of “behaviors that contribute to success” and the implementation of “a systematic method to intervene when students fall short of those behaviors” (p. 53). It is likely that when advisors and other staff think of early intervention, they picture systems in which faculty report student red flags to some intervening agent (Gordanier, Hauk, & Sankaran, 2019; Tampke, 2013; Winfield, 2018). In fact, respondents to the 2017 NSFYE indicated that faculty engage in early alert programs at 89.6% of institutions (Estrada & Latino, 2019). Two of the greatest barriers to implementing high-quality early intervention programs, however, are the challenges of generating faculty buy-in (Estrada & Latino, 2019) and determining a “reliable set of predictors” (Beck & Davidson, 2001, p. 710). Given these challenges, it should be noted that academic advisors can design and implement a host of student interventions relying only on data readily available in existing campus advising technologies. Advisors may be uniquely qualified to serve as intervention agents due to the relationships they form with students, often beginning at orientation.
In their work on choice architecture, Thaler and Sunstein (2009) suggest that individuals make poor choices when “they are inexperienced, and poorly informed, and in which feedback is slow or infrequent.” On the other hand, they make “good choices in contexts in which they have experience, good information, and prompt feedback” (p. 9). By reaching out intrusively to students who exhibit potentially problematic behaviors, advisors equip students with context and valuable information they may lack as novices in the collegiate setting. Advisors are distinctively positioned to gather information, uncover predictive behaviors, and identify students who are at heightened risk of not persisting. The following section examines some of these opportunities where advisors can gather data and leverage their relationships with their caseload to positively impact student success and persistence.
Minimum Credit Hours
Distinctively, advisors have the ability and positioning to examine students’ credit hour enrollment in aggregate, where faculty and other stakeholders may only be looking at students through the lens of a particular course. By establishing a standard number of credit hours, generally 15, at which a student is most likely to balance the ability to succeed with timely completion of a program and graduation, advisors can intervene when students are dipping below this threshold early, and oftentimes catch a student that may otherwise have exhibited no other early risk factors (Szafran, 2002; Venit, 2017). For many students, financial concerns may also arise from lower credit hour enrollment, resulting in extended time to degree.
Enrolling in adequate credit hours may seem to be too simple of a factor on which to conduct an intervention, or even one that advisors may assume many students do not need. However, Whitcomb and Mathews (2014) have demonstrated that there is no statistically significant correlation between any one student demographic and understanding of degree requirements, and “encourage academic advisors not to attempt to predict students’ understanding of degree requirements solely based on grade point average,” among other factors. Utilizing their unique ability to see students’ total enrollment, advisors can contact students, alerting them to the benefit of enrolling in at least 15 credit hours. It should be noted that students may have valid reasons for enrolling in less than 15 credit hours, including disability status, serving as primary caregivers for children or elderly parents, and financial obligations for self and family. This intervention also allows advisors to establish context in these cases and better serve students in future meetings.
University Mandated Compliance and Registration Holds
Advisors can also work in collaboration with key campus partners to assure student compliance in university-wide mandates, neglect of which may trigger academic consequences both directly and indirectly. An example of such a mandate is the completion of online prevention education courses on topics like substance abuse and sexual assault. Directly, failure to complete requirements by university established deadlines will, at many institutions, trigger a registration hold on a student’s account, preventing them from future course registration actions until they have completed the related action item. If students cannot register, despite taking other required actions, then they cannot persist by default. Advisors can work with the campus partners responsible for these initiatives to intervene with students who are not in compliance, emphasizing the importance of the requirement from an academic standpoint and leveraging the advisor to student relationship to encourage compliance.
Indirectly, advisors that are involved in intervention to encourage compliance with prevention education are supporting student success and persistence due to the intended outcomes of the course. A case study conducted at Oregon State University by EverFi (2018) concludes by stating “students [who receive the course] are safer and satisfied—giving them a greater opportunity to succeed. Incidents of alcohol abuse and sexual assault can dramatically disrupt students’ lives, but effective prevention education enables them to remain in school and enjoy every opportunity to succeed.”
Non-Registered Students
Intervening with students who have not registered for the upcoming term in a timely manner—after they have been advised and the opening week or two of registration have passed—can be considered a light touch intervention with a big impact. Hutt (2017) describes the value of a simple, 34-word email that can be sent from advisors to non-registered students asking, “Is there anything I can do to help?” The original campaign, sent by Hutt, the Assistant Vice President for Academic Advising at Kennesaw State University, was sent to 4,000 students with 3.0 or higher grade point averages. This further enforces Whitcomb and Mathews’ study that advisors cannot rely on perceived levels of student success to determine whether students will benefit from intervention. Over 35% of students responded to Hutt’s outreach, many within a few days, to describe registration barriers that they were facing. Factors such as parking tickets, course availability, and lack of resource information—“I know where I want to go, but I don’t know how to get there”—arose frequently in Hutt’s (2017) responses. These are challenges that advisors can assist students in overcoming through intervention, thus encouraging their students to persist and succeed.
Effective Timelines for Intervention
A final component of impactful early intervention conducted by advisors is intentional timing. To construct an effective intervention timeline, it is necessary to think about meeting students where they are and providing the support and resources they need, when they need them. The role of the advisor, particularly in intervention, says McElwee (2013), is to “at each stage . . . respond to the students’ characteristics and developmental stage, providing information, support, or encouragement as needed.” An intentional framework will use academic dates and deadlines as a guide to avoid “too much, too soon.” If an intervention about non-registration is sent before students have had the opportunity to get comfortable with the process and system of registration, it will likely not serve its intended outcomes. Likewise, an intervention to reach student below a minimum credit hour threshold sent after the timeframe during which students can add additional classes is ineffective and likely frustrating for the student.
Implications for Institutional Improvement
Early intervention programs, such as those detailed above, target intrusive outreach to students based on the display of potentially problematic behaviors beyond-the-classroom that may hinder their ability to progress within their degree programs. By monitoring all students and not just those that enter the university with an at-risk label, advisors and therefore the institution are able to reach more students at risk of departure. This is especially significant upon acknowledging that many at-risk students will go on to lead productive academic lives and complete the requirements of their degree program while some students admitted as high-achievers will face academic and personal struggles that may lead to their departure. High-touch, high-impact interventions, such as these carried out by academic advisors, as students’ primary points of contact, further demonstrate the attention and care promised to students and their families in the admissions and orientation processes. They also may deliver increased benefit to first-generation and low-socioeconomic status students, leveling the playing field for novice learners who lack context. Most importantly, the interventions described herein do not require institutional buy-in/support. Individual advisors can implement these initiatives of their own accord for the benefit of the students in their caseload.
Mike Dial Assistant Director of First-Year Advising University Advising Center, Office of the Provost University of South Carolina [email protected]
Paige McKeown Coordinator of First-Year Advising and Academic Intervention University Advising Center, Office of the Provost University of South Carolina [email protected]
References
Barefoot, B. O., Griffin, B. Q., & Koch, A. K. (2012). Enhancing student success and retention throughout undergraduate education: A national survey. The John N. Gardner Institute for Excellence in Undergraduate Education.
Beck, H. P., & Davidson, W. D. (2001). Establishing an early warning system: Predicting low grades in college students from survey of academic orientations scores. Research in Higher education, 42(6), 709–723.
Estrada, S., & Latino, J. (2019). Early alert programs. In D. Young (Ed.), 2017 National Survey on The First-Year Experience: Creating and coordinating structures to support student success (pp. 53–61). University of South Carolina, National Resource Center for The First-Year Experience & Students in Transition.
EverFi. (2018, March 9). Going online: Sexual assault and alcohol abuse prevention at Oregon State University. https://everfi.com/insights/case-studies/oregon-state-university/
Gordanier, J., Hauk, W., & Sankaran, C. (2019, October). Early intervention in college classes and improved student outcomes. Economics of Education Review, 72(1), 23–29.
Habley, W. R., Bloom, J. L., & Robbins, S. (2012). Increasing persistence: Research-based strategies for college student success. Jossey-Bass.
Hutt, C. (2017, November 24). Breaking down barriers to retaining students. The Chronicle of Higher Education. https://www.chronicle.com/article/Breaking-Down-Barriers-to/241814
McElwee, R. O. (2013, April). Teaching and advising first-year students. Observer, 26(4). Retrieved from https://www.psychologicalscience.org/observer/teaching-and-advising-first-year-students
Seidman, A. (2012). Taking action: A retention formula and model for student success. In A. Seidman (Ed.), College student retention formula for student success (pp. 267–284). Rowman & Littlefield Publishers.
Szafran, R. F. (2002). The effect of academic load on success for new college students: Is lighter better? NACADA Journal, 22(2), 26–38. https://nacadajournal.org/doi/pdf/10.12930/0271-9517-22.2.26
Tampke, D. R. (2013). Developing, implementing, and assessing an early alert system. Journal of College Student Retention: Research, Theory & Practice, 14(4), 523–532. https://doi.org/10.2190/CS.14.4.e
Thaler, R. H., & Sunstein, C. R. (2009). Nudge: Improving decisions about health, wealth, and happiness. New York, NY: Penguin.
Venit, E. (2017, August 21). Why even C students should consider taking 15 credits their first semester. https://eab.com/insights/blogs/student-success/why-even-c-students-should-consider-taking-15-credits-their-first-semester/
Whitcomb, H., & Mathews, S. (2014, December). Exploring the relationship between student understanding of degree requirements and academic performance. Academic Advising Today, 37(4). https://www.nacada.ksu.edu/Resources/Academic-Advising-Today/View-Articles/Exploring-the-Relationship-between-Student-Understanding-of-Degree-Requirements-and-Academic-Performance.aspx
Winfield, J. (2018, December). The art of intervention: Partnering with faculty for early academic alert. Academic Advising Today, 41(4). https://nacada.ksu.edu/Resources/Academic-Advising-Today/View-Articles/The-Art-of-Intervention-Partnering-with-Faculty-for-Early-Academic-Alert.aspx
Cite this article using APA style as: Dial, M., & McKeown, P. (2019, December). Beyond faculty referrals: Advisory facilitated early intervention. Academic Advising Today, 42(4). [insert url here]
