From Theory to Practice: What the Most Effective Student Success & Advising Teams Do Differently

By Michael Griffin, Strategic Product Advisor at Advisor AI and Former VP of Enrollment Management, with 25+ years of experience across higher education administration, enrollment, retention, financial aid and advising operations.

Across higher education, student success teams are navigating a period of real change.

Student expectations are evolving. Career uncertainty is rising. Caseloads remain high. And while new technologies promise efficiency, many teams are asking the same question quietly:

How do we adapt—without losing the human connection of our work?

The institutions making meaningful progress are not chasing trends or tools. They are grounding decisions in evidence, strengthening professional practice, and using technology with intention—not as a replacement for judgment, but as a way to transform engagement and connections.

Based on decades of research, national surveys, and real-world case studies, a clear pattern emerges. The most effective student success teams consistently focus on a small set of practices—and use technology only where it is required.

1. They Create Clarity Early—Before Confusion Sets In

Research is consistent: students don’t struggle because they lack options. They struggle because they lack direction.

Studies from the Community College Research Center, the Gates Foundation, and Inside Higher Ed show that students want clearer academic pathways, better planning tools, and earlier connections between coursework and careers. Without this clarity, uncertainty compounds—and momentum slows.

Advising teams that excel address this challenge by:

• Helping students understand how programs connect to real outcomes
• Providing structured academic and career pathways
• Making expectations visible early, especially in the first year

Technology plays a supporting role here—not by overwhelming students with information, but by organizing complexity into clear, navigable choices. When students arrive at advising conversations with shared context, advisors can focus on meaning, not mechanics.

2. They Strengthen Conversations—Not Access to Information

AI can surface information quickly. What it cannot do is interpret nuance, read hesitation, or build trust. The most effective advising teams recognize this distinction. They use technology to reduce repetitive searching and administrative friction so advisors can spend more time on:

• Listening for uncertainty
• Helping students articulate goals
• Coaching through decision points

Evidence from NACADA and peer-reviewed advising research shows that frequency and quality of advisor interaction are strong predictors of retention—especially for first-generation and underserved students.

When technology is designed to reinforce the advising relationship, not bypass it, conversations improve. Students come prepared. Advisors have visibility. Trust deepens.

3. They Build Momentum Through Small, Purposeful Actions

Momentum matters—especially early.

Gallup, Jobs for the Future, and Gen Z research consistently show that engagement and confidence are closely linked. Students who take small, meaningful steps are more likely to persist and feel hopeful about their future.

Effective teams design systems that:

• Encourage progress without pressure
• Offer timely nudges, not constant notifications
• Help students move from exploration to action

Here, technology works best when it supports short, intentional interactions—not engagement for engagement’s sake. The goal isn’t to keep students “on platform.” It’s to help them move forward, then reconnect with people who can guide the next step.

4. They Use Data to Grow Teams—Not Monitor Them

Data can be powerful. It can also be misused. Leading institutions use analytics to:

• Understand common student questions and objections
• Identify moments where guidance is needed and intervene
• Inform resource development and expansion decisions

What they avoid is surveillance-driven design or metrics that reduce advising to activity counts.

When data is anonymized, contextual, and shared transparently, it becomes a tool for team excellence—helping professionals focus their time where it matters most and adapt services to real student and institutional needs.

5. They Treat Technology as a Supplement—Not the Focus

Perhaps most importantly, the strongest teams don’t frame AI as a threat to the profession.

They see it as:

• A way to scale access to trusted information
• A support for growing caseloads and limited capacity
• An opportunity to elevate the craft of advising

Research from McKinsey and large-scale institutional case studies reinforces a simple truth: most roles are not replaced by technology—they are reshaped. When routine tasks are automated responsibly, professionals gain time for judgment, care, and impact.

Moving Forward—With Intention

The future of student success is not about choosing between people and technology.

It’s about designing systems that honor professional expertise, meet rising student expectations, and make progress feel achievable.

The teams leading this work are grounded in evidence, clear in purpose, and disciplined in how they adopt new tools. They understand that excellence in advising is both an art and a discipline—and that technology, when used well, can help protect both.

For institutions navigating what comes next, the lesson is clear:

Start with trust. Design for clarity. Use technology to make room for better human work.

Appendix: Foundations for Student Success & Advising Excellence

After interviewing and running experiments with advising and workforce teams nationwide, our team at Advisor AI has compiled this repository of the most relevant research on student success. The insights presented are grounded in a wide body of external research and institutional practice. The sources below draw on peer-reviewed studies, national surveys, philanthropic initiatives, and documented case studies from higher education institutions and workforce organizations. We gratefully acknowledge the researchers, associations, and institutions whose work continues to inform and advance evidence-based approaches to student success and excellence in higher education.

Inside Higher Ed & Generation Lab. (2024, July 26). Survey: Students want more clarity

• Key Insight: Students want clarity about academic pathways and better planning tools.
• Methodology: Web-based survey conducted May 6–21, 2024. Sample drawn from Generation Lab’s student panel, which includes students from community colleges, HBCUs, women-only colleges, and other institution types. Panel recruited to approximate a probability-based sample through randomized college lists, proprietary contact methods, advertisement-based outreach, and geographic quotas. Sample included 5,025 students.

Inside Higher Ed (2024), Gallup & New Hampshire Learning Initiative

• Key Insight: Career-connected learning experiences strengthen high school students’ sense of hope and postsecondary ambition; 38% of respondents reported that career learning directly informed their educational and career plans.
• Methodology: Web-based survey conducted May 1–June 7, 2024. Opt-in participation from schools and districts invited by the New Hampshire Learning Initiative. Sample included 8,634 high school students.

Gallup & Walton Family Foundation (2024), The 2024 Voices of Gen Z Study

• Key Insight: School engagement is strongly associated with students’ future outlook and overall life satisfaction, reinforcing the importance of meaningful connection during the educational experience.
• Methodology: Probability-based Gallup Panel™ web survey conducted April 26–May 9, 2024. Sample included 4,157 Gen Z respondents ages 12–27.

Jobs for the Future & Morning Consult. (2024). Career Navigation Survey.

• Key Insight: 66% of students don’t know exactly what career they want, and 74% say more access to career and education information would expand the options they see.
• Methodology: Online survey conducted May 2024. Quota sampling with strata defined by age, gender, educational attainment, and other demographics. Participants recruited through a diverse network of trusted survey panel providers. Sample included 2,046 young people aged 16–24 (Gen Z).

Bailey, T. R., Jaggars, S. S., & Jenkins, D. (2015). Redesigning America's community colleges: A clearer path to student success. Harvard University Press.

• Key Insight: Students don’t fail from a lack of options—they fail from a lack of direction. Structured guidance, real-time personalized advising, and clear program pathways improve student outcomes; over 400 colleges have adopted this model since publication.
• Methodology: Research synthesis and policy analysis drawing on 8+ years of research from the Community College Research Center (CCRC) at Teachers College, Columbia University, including studies on developmental education, student supports, program structure, and completion patterns across U.S. community colleges.

Bill & Melinda Gates Foundation. (n.d.). Pathways Gates Foundation.

• Key Insight: Structured pathways across K-12, higher education, and employers improve credential attainment, advising, and career-connected learning. High student-to-counselor ratios (385:1 vs. recommended 250:1) create gaps that AI and integrated supports can help address.
• Methodology: Philanthropic strategy framework and funding initiative based on multi-year research. Supported the AACC Pathways Project (300+ colleges), CCRC guided pathways research, and state-level initiatives for dual enrollment, mentoring, and advising interventions.

Community College Research Center (CCRC). (2015–present). CCRC Guided Pathways

• Key Insight: Whole-college redesign through structured program maps, proactive advising, and early momentum metrics improves completion rates—especially for students of color and low-income students.
• Methodology: Ongoing multi-year research program studying adoption, implementation, costs, and outcomes at 100+ colleges across Ohio, Tennessee, and Washington. Builds on nearly 30 years of community college research and informs the guided pathways model now used by 400+ colleges and 18 state systems.

Lindsay, J., Hughes, K., Dougherty, S. M., Reese, K., & Joshi, M. (2024). What we know about the impact of career and technical education: CTE Research Network

• Key Insight: Career and technical education (CTE) participation positively affects high school outcomes—including academic achievement, completion, employability skills, and college readiness—without statistically significant negative effects.
• Methodology: Systematic review and meta-analysis of 20 years of rigorous causal CTE research meeting What Works Clearinghouse (WWC) standards.

EdTech Magazine. (2024, November 18). What a frictionless student experience looks like.

• Key Insight: Digital-native students expect seamless interaction with college systems, uninterrupted connectivity, and easy access to information. If students “think nothing” about their digital experience, the institution has succeeded; friction indicates outdated systems.
• Methodology: Trade publication/industry perspective based on practitioner insights from CDW Education partnerships with university campuses, reflecting common challenges in technology decentralization and budgeting in higher education.

Ohrablo, S. (2017, February 6). The role of proactive advising in student success.

• Key Insight: Proactive advising—where advisors initiate contact rather than wait for students—is effective for retention and student success. Students with clear academic and career goals who feel connected and cared for are more likely to persist.
• Methodology: Practitioner article and best practices guide drawing on Noel-Levitz (2014) research on advisor knowledge and concern as drivers of satisfaction and retention, as well as NACADA research and early intervention frameworks.

Kinzie, J., & Akyuz, F. (2022, May). Exploring the influence of course-based career experiences and faculty on students' career preparation. NACE Article.

• Key Insight: Course-based career experiences—such as case studies, career research assignments, and learning from professionals—strengthen students’ career preparation. Practical/applied majors (business, education) provide more career-relevant experiences than arts, humanities, or sciences. Faculty interactions significantly influence students’ sense of career preparedness.
• Methodology: Peer-reviewed research using data from the Career & Workforce Preparation (CWP) module developed with Strada Education Network, analyzed seniors’ course experiences and career outcome perceptions by major.

Critelli, J. E., Propst Cuevas, A. E., & Bloom, J. L. (2022). Development of the Appreciative Advising Success Inventory (AASI). Journal of Appreciative Education.

• Key Insight: The Appreciative Advising Success Inventory (AASI) was developed and validated to measure how use of the Appreciative Advising framework by advisors correlates with student psychosocial factors (e.g., academic confidence, motivation, and intent to persist), showing that effective application of the framework positively influences predictors of student success.
• Methodology: Peer‑reviewed instrument development study using psychometric theory to create and validate the AASI, linking advisor practices grounded in Appreciative Advising with student success outcomes.

Swecker, H. K., Fifolt, M., & Searby, L. (2013). Academic advising and first-generation college students: A quantitative study on student retention. NACADA Journal Article.

• Key Insight: Each additional meeting with an academic advisor increased first-generation students’ odds of retention by 13%. Frequency of advisor contact is a significant predictor of retention.
• Methodology: Quantitative research study using multiple logistic regression at a large public research university in the Southeast (University of Alabama at Birmingham), controlling for gender, race, and major.

Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., & Dewhurst, M. (2017, January). A future that works: Automation, employment, and productivity. McKinsey.

• Key Insight: ~50% of current work activities are technically automatable, but fewer than 5% of occupations are fully automatable. Automation is likely to transform jobs rather than eliminate them, supporting AI’s role in augmenting advising services.
• Methodology: Research report and global economic analysis assessing 800+ occupations decomposed into ~2,000 work activities, evaluated against 18 capabilities for automation, with adoption scenarios modeled across 46 countries representing 80% of the global workforce.