Higher Ed’s Move Toward Student Success
In recent decades, higher education has undergone vast transformations and has pivoted towards a more outcome-focused model. This shift has been significantly influenced by an increasing emphasis on “student success,” a broad term that encompasses different things to different people and institutions but mainly focuses on things such as student persistence, retention, degree completion, and whether or not recent graduates were able to get jobs (Link).
The 2019 report by The Chronicle of Higher Education titled “The Truth About Student Success” links the rise of this movement to several key factors:
- Enhanced Engagement Research: There is a growing body of research focused on how student engagement directly impacts learning outcomes.
- Calls for Accountability: Stakeholders, including governments and educational bodies, are increasingly demanding that institutions demonstrate their effectiveness in ensuring student success.
- Data-Driven Approaches: The push for rigorous assessments and the use of data in educational decision-making have become more pronounced, a trend partly spurred by initiatives like President Obama’s education policies.
- Addressing Persistent Challenges: Institutions are responding to historically low graduation rates and impending demographic shifts that could result in a decrease in college-age students.
A pivotal factor in this evolution has been the advanced use of data analytics, and more particularly the incorporation of early alert systems. Ewaoluwa Obatuase and Monique O. Ositelu in an article for New America define early alert systems as “communication advocacy tools used for identifying academically at-risk students and improving student retention.” They go on to note that “these systems are intended to provide wrap-around services to students and help institutions make data-driven decisions to improve their retention and completion rates.”
While early alert systems have been around for over two decades, they gained national prominence during the 2010s, not only in response to the factors listed in The Chronicle report above but also through the success of numerous institutions implementing them, most notably Georgia State University. The inclusion of such measures led to not only a vast increase in the number of meetings students held with advisors, but a a growth in the enrollment, persistence, and graduation of their students, particularly students from historically marginalized populations. As Jean Dimeo, in an article for Inside Higher Ed, reports in a 2017 article, “Black male enrollment is up 15 percent in five years, and the number of black men graduating with STEM degrees is up 111 percent.”
In response to such successes, many institutions have rapidly adopted similar data analytic approaches including early alert systems. Moreover, such systems have become integral to the operations of many higher education institutions in identifying students of concern and connecting them with vital resources such as counseling, academic advising, and tutoring.
While this article aims to explore the growing prevalence of early alert systems within the context of higher education, it seeks to do so through the McDonaldization framework developed by the sociologist, George Ritzer. Such a framework will not only help to better understand the intricacies of this phenomenon but link it to much larger processes happening throughout the globe.
What is McDonaldization?
George Ritzer introduced the term “McDonaldization” in his 1993 work, The McDonaldization of Society. Building upon the theories of sociologists Max Weber and Zygmunt Bauman, Ritzer described McDonaldization as a process by which the principles of the fast-food industry increasingly dominate various sectors, both in the United States and globally. This concept encapsulates how these principles transform social structures and institutions.
To Ritzer, McDonaldization is structured on four interrelated principles:
- Efficiency: Ritzer defines efficiency as “finding and using the optimum method for getting from one point to another” (2). In the fast food model, this is the quickest and best way from the customer being hungry to the customer becoming full.
- Calculatility: Ritzer defines “calculability” in McDonaldization as focusing on the measurable aspects of products and services, such as portion size, price, and the time required for service delivery. This concept emphasizes quantification in every aspect of the system, from the duration of making a hamburger to the waiting time for customers, the cost of products, and even the wages paid to employees.
- Predictability: Ritzer defines this as “the assurance that products and services will be much the same over time and in all locales” (3). To Ritzer, a Big Mac should look and taste the same whether being sold in upstate New York or Beijing, China. This principle of predictability extends beyond the products themselves to encompass the behavior of both employees and customers within the system.
- Control: Control in McDonaldization is the influence exerted on both employees and customers. This concept is exemplified by the dining experience at McDonald’s, where management’s goal is to expedite the customer’s eating process, resulting in quick turnover. This objective is reflected in the restaurant’s design, characterized by features such as queue lines, limited menu options, and basic seating arrangements. Similarly, employees at McDonald’s are subject to control mechanisms that align with these efficiency goals (4).
While McDonaldization can lead to efficiencies and uniform service delivery, Ritzer also explores its downsides, termed “the irrationality of rationality.” This includes inefficiencies (like bureaucratic complexities), increased costs, loss of uniqueness (homogenization), and the reduction of human interactions (dehumanization). These elements highlight the complex impact of applying fast-food principles to various societal aspects.
Moving from the broader implications of McDonaldization as outlined by Ritzer, let’s turn our attention to how these principles manifest within the domain of higher education, particularly in the implementation and functioning of early alert systems. This transition allows us to explore whether these systems, designed for student support, also exhibit the characteristics of efficiency, calculability, predictability, and control, thereby reflecting the broader trends of McDonaldization in education.
Early Alerts and the Continuing McDonaldization of Higher Education:
Since the first edition of The McDonaldization of Society was published in 1993, Ritzer saw higher education as one such institution that was quickly becoming McDonaldized. Over the decades in subsequent editions, Ritzer has developed his analysis through numerous examples, including but not limited to the importance of student grades, college rankings, the proliferation of Massive Open Online Courses (MOOCs), and the creation of computerized Learning Management Systems (LMS) to deliver course content and assist with assessing students. In what follows, I apply Ritzer’s four principles of McDonaldization to student alerts.
Efficiency:
Early alert systems epitomize efficiency by streamlining the communication of student behavior concerns. For example, when a faculty member raises an alert for a student, such as absenteeism, this information is quickly disseminated to a network of relevant offices. This process ensures swift action to support the student, creating a comprehensive support network. The system also keeps track of which offices have contacted the student, when they contacted them, and records the details of any meetings, thereby ensuring efficient follow-up and intervention.
Calculability:
In these systems, alerts are categorized by type and severity, making them quantifiable. Each interaction, from the number of communications to the details of student meetings, is tracked and recorded. This quantification extends to correlating these interactions with other data points, such as the student’s academic performance, resource utilization, and even their campus activity as monitored through ID card usage. This approach allows for a measurable assessment of student engagement and the effectiveness of interventions.
Predictability:
In early alert systems, predictability manifests as a standardized and systematic approach to student monitoring and intervention. These systems create a consistent environment by applying uniform protocols for various student situations, akin to how a product or service remains consistent in different settings. This standardization extends to the expectations and roles of both staff and students. Faculty and advisors are trained to respond predictably to certain types of alerts, while students come to anticipate a certain level of institutional monitoring and support. Moreover, the fundamental goal of early alert systems and student success initiatives extends beyond immediate intervention for student success; it also encompasses the development of predictive models aimed at forecasting students’ academic outcomes within the institution.
Control:
While early alert systems are designed with the noble intention of supporting student success, they also result in a significant degree of control over students and staff. Students are monitored and interventions are made to align their behaviors with institutional expectations. Faculty and staff, too, find themselves increasingly guided by these systems, facing pressure to issue alerts and engage in interventions. This control extends to the institutional level, where student success rates impact the perception and funding of these programs.
Advantages of Early Alerts in the Context of McDonaldization:
The success of student success initiatives, particularly early alert systems, has been widely recognized by educational institutions, service providers, and leading academic publications like Inside Higher Education and The Chronicle of Higher Education. These systems have demonstrated a range of benefits, previously exemplified by Georgia State University’s case, and extend to other contexts as well.
Effectively implemented early alert systems offer numerous benefits to both students and their institutions. For students, particularly those who are first-generation college attendees and may lack a robust support network, these systems provide crucial guidance and resources. This proactive support is invaluable, ensuring that issues are addressed before they escalate, and contributing to a more successful academic journey.
From an institutional perspective, the advantages are multifaceted. Enhanced retention and graduation rates not only lead to greater student and parent satisfaction but also improve the institution’s overall standing and attractiveness. Higher rankings and positive perceptions can result from these improved metrics, appealing to prospective students and benefactors alike.
The growth of early alert initiatives also drives economic and professional development within the university setting. They pave the way for new job opportunities, the creation of dedicated offices for student support, and promotional prospects for university staff. Furthermore, the adoption of these systems fosters valuable public-private partnerships, with institutions collaborating with companies like EAB Starfish, Ellucian Advise, or Civitas Learning for system implementation, training, and maintenance.
These collaborations enhance the systems’ effectiveness, bringing in additional expertise and ensuring their successful integration into the university’s educational framework. However, they can also lead to irrationalities, which are discussed next.
The Irrationality of Student Alerts:
As higher education increasingly adopts early alert systems in a bid to streamline and improve the student experience, a paradox emerges. While these systems are designed to bring rationality and efficiency to the educational process, they inadvertently give rise to a series of irrational outcomes. It’s important to note that the following list of irrationalities is not exhaustive but rather illustrative, highlighting key areas where the intended rational benefits of these systems clash with unintended consequences.
Diverted Funding and Faculty Roles
In the wake of the 2008 financial recession, a notable correlation can be observed between the rise of student success initiatives in higher education and the changing landscape of faculty employment. Following the recession, there was a decrease in funding from state and federal governments to colleges and universities, which coincided with an increased emphasis on student success initiatives. These initiatives often involve the establishment of new administrative roles and departments dedicated to enhancing student services and outcomes.
As institutions have directed more resources towards these student success initiatives, a parallel trend has emerged in faculty employment. The American Association of University Professors (AAUP) reports a significant rise in part-time and contingent faculty positions, contrasted with a decline in full-time tenured roles. This trend suggests a shift in the focus of institutions from traditional academic roles to administrative functions related to student success.
While this does not imply a direct causal relationship, the correlation between the growth of student success initiatives and the shift in faculty composition is noteworthy. It reflects a broader change in priorities within higher education, where the resources and attention are increasingly being channeled towards administrative measures aimed at improving student experiences and outcomes. This shift raises questions about the balance between academic and administrative priorities in higher education and its implications for the quality of education and the role of faculty.
Growing Surveillance Culture
The implementation of early alert systems in higher education has not only transformed the approach to student success but also established a pervasive surveillance network. This network extends its oversight beyond student activities, encompassing the performance and behaviors of faculty and staff, which raises concerns about privacy and the implications of continuous monitoring.
For students, this surveillance is manifested in the monitoring of their academic performance and behaviors, with alerts being raised for issues like attendance, grades, or engagement. The alerts can lead to beneficial interventions but also place students under a microscope, potentially impacting their sense of autonomy and privacy.
Faculty members, traditionally focused on teaching and research, now find themselves under surveillance for how they interact with and report on student issues. The quality and frequency of their alerts are monitored, making them accountable not only for their teaching responsibilities but also for their vigilance in tracking student progress. This added dimension of surveillance can affect their approach to teaching and student interaction, potentially leading to a more cautious, report-driven focus.
Staff members, particularly those in student success and advisory roles, also experience increased surveillance. Their effectiveness is often measured by their responsiveness to alerts and the outcomes of their interventions. This continuous monitoring can create a pressurized work environment, where staff actions and decisions are constantly evaluated, potentially leading to a more procedural and less personalized approach to student support.
In essence, the comprehensive surveillance network fostered by early alert systems in higher education institutions creates a culture of constant monitoring and accountability. This culture not only impacts the ways in which students are supported and guided but also significantly influences the roles and responsibilities of faculty and staff, reshaping the educational landscape into one where surveillance is an integral component.
Challenges with Inputs and Outputs
Student alerts are only information, meaning they only shape and are only as good as their inputs and outputs. The primary inputs for these systems come from faculty members, who are responsible for observing and reporting on student behaviors and academic performance. This step is crucial as the quality and timeliness of these reports directly influence the effectiveness of the alert system. However, ensuring consistent and thorough reporting from faculty can be challenging. It requires not only a commitment from the faculty but also adequate incentives and support to encourage their active participation in the system.
Once these reports are submitted, the next crucial step involves processing and acting upon this information, typically undertaken by advising offices and individual advisors. These advisors assess the reports, determining the necessary interventions, which often include referrals to support services like tutoring, especially for academic concerns. This process is vital for converting early alerts into actionable support for students.
However, a significant challenge arises in the availability of staff members to meet these concerns, whether they be tutors, advisors, or other support-based professionals. This is especially true with advisors as according to a 2011 survey by the National Academic Advising Association (NACADA), the advisor-to-student ratio in higher education institutions has been declining. On average, there was one advisor for every 367 students, a decrease from one per 282 students in 2003. In some community colleges, the ratio can be as skewed as one advisor to every 1,700 students. While this survey was completed in 2011 there is little evidence that this situation has improved on college campuses, and instead more evidence that it is getting worse. This disparity raises a critical question: with such limited advisory resources, who will ensure that these alerts are addressed effectively?
In summary, the success of early alert systems is contingent on two key factors: the faculty’s engagement in providing detailed and prompt reports and the subsequent efficient handling of these reports by advisors. Without addressing these challenges, the potential of early alert systems to positively impact student success may not be fully realized, emphasizing the need for a balanced approach to both the technological and human aspects of these systems.
Dehumanization in Student Engagement:
The evolution of student success initiatives from the classroom to administrative domains has inadvertently led to a reduction in the “human touch” that is intrinsic to the educational experience. Traditionally, faculty members and teaching assistants, who interact with students on a regular basis, played a pivotal role in providing personalized support. Their direct, ongoing engagement with students in academic settings allowed for tailored guidance and a deeper understanding of individual student needs.
However, with the shift towards administrative-centric models, this personalization has waned. Student success employees and advisors, who often lack prior, or reduced, direct communication with the students they are assisting, are increasingly filling these roles. Consequently, the nature of interaction with students has transformed. Personalized, nuanced communications have given way to standardized, templated messages. This change, while streamlining processes, risks losing the individualized attention that can be crucial in addressing the unique challenges and concerns of each student.
Further exacerbating this issue, some educational technology companies have embraced an approach that significantly depersonalizes the student experience. These systems distill a student’s educational journey into numerical scores, prioritizing algorithmically derived data over the qualitative aspects of their academic and personal growth. Such a method, while efficient for administrative purposes, fails to capture the complexity and humanity inherent in each student’s educational path. This shift towards quantification, away from a more holistic understanding of student development, epitomizes the dehumanization concerns in modern educational practices.
Questionable Efficacy:
A 2018 article written by Lindsay McKenzie for Inside Higher Ed examines the efficacy of early alert systems in higher education to achieve desired outcomes despite significant investments into these systems. One of the key issues is the accuracy and relevance of data being used to generate alerts. For higher education professionals, alerts are based on broad data points that may not fully capture the nuances of individual student experiences and their academic journeys. Moreover, it can lead to false positives and negatives, where students who are not at risk are flagged, and those who are in need of support are overlooked.
Moreover, as the article notes, the reliance on quantitative data over qualitative insights can lead to superficial understandings of student needs. While the data can indicate general trends or issues, it may not provide the depth of understanding required to tailor interventions effectively to individual students, meaning interventions based on such alerts might not be as impactful as anticipated.
This situation highlights a critical gap and irrationality in the implementation and design of many early alert systems. While they are intended to support student success by providing timely interventions, the effectiveness of these interventions is contingent on the accuracy and applicability of the data being used. The challenge, therefore, is to ensure that these systems are sophisticated and nuanced enough to accurately identify students in need and provide them with meaningful support towards specific circumstances.
Conclusion:
This article has been an attempt to bring together the intricate landscape of higher education reshaped by student success initiatives, more particularly early alert systems, with the McDonaldization theory formulated by the sociologist, George Ritzer. As has been shown, early alert systems can be looked at through the lens of efficiency, calculability, predictability, and control, while providing numerous benefits to the various stakeholders within the college system. However, this transformation isn’t without its irrationalities. As shown, this can result in diverted funding, the growth of surveillance culture, challenges in input and output management, and the risk of dehumanizing student engagement. These irrationalities remind us that while the pursuit of efficiency and standardization is valuable, it must be balanced with the intrinsic human elements of education. As higher education continues to evolve, it is crucial to keep these considerations at the forefront, ensuring that the systems we implement enhance rather than detract from the rich, diverse, and deeply human endeavor of learning.
In conclusion, the future of higher education lies not just in embracing technological and systemic advancements but in harmonizing these developments with the core values of education. By doing so, we can create an educational landscape that is not only efficient and effective but also compassionate, inclusive, and truly conducive to student growth and success.
The Online Sociologist 