What Students Actually Value in College Might Surprise Higher Education Leaders
A new national survey from the LearningWell Coalition and AAC&U challenges the increasingly common narrative that students view college only as a pathway to employment. The findings suggest something far more nuanced: students want careers, but they also want meaning, mentorship, growth, and opportunities to apply learning in real-world contexts.
According to the study, 36.5% of students identified “getting a good job and advancing their career” as their primary reason for attending college. However, nearly the same percentage cited motivations tied to intellectual growth, identity formation, and contributing to their communities.
One of the most important findings in the report involves mentorship and experiential learning.
Students who reported having faculty or staff mentors demonstrated higher wellbeing scores than those without mentors. Likewise, students participating in internships, service-learning, and employment experiences consistently reported stronger wellbeing outcomes and greater perceived value from their education.
What stood out to me as a doctoral candidate in Educational Technology is that the experiences students value most are deeply relational and highly applied:
• mentorship
• real-world problem solving
• internships
• experiential learning
• collaborative growth
• opportunities to connect knowledge to identity and purpose
Ironically, the report also found that many of these highest-impact experiences remain among the least accessible to students.
This has major implications for higher education and for the future design of AI-supported learning environments.
As institutions increasingly integrate AI, analytics, and adaptive technologies into teaching and learning, the challenge is not simply building more efficient systems. The challenge is designing learning ecosystems that preserve human connection, mentorship, exploration, and authentic application of knowledge.
This aligns closely with my ongoing doctoral research in AI-Augmented Exploratory Learning (AAEL), which examines how professionals learn, adapt, and problem-solve alongside AI systems. One of the recurring themes in both the literature and practice is that technology appears most effective when it enhances human guidance rather than replacing it.
Students may remember the technology they used.
But they often remember the people, experiences, and opportunities that helped them grow.
NhanceData
According to the study, 36.5% of students identified “getting a good job and advancing their career” as their primary reason for attending college. However, nearly the same percentage cited motivations tied to intellectual growth, identity formation, and contributing to their communities.
One of the most important findings in the report involves mentorship and experiential learning.
Students who reported having faculty or staff mentors demonstrated higher wellbeing scores than those without mentors. Likewise, students participating in internships, service-learning, and employment experiences consistently reported stronger wellbeing outcomes and greater perceived value from their education.
What stood out to me as a doctoral candidate in Educational Technology is that the experiences students value most are deeply relational and highly applied:
• mentorship
• real-world problem solving
• internships
• experiential learning
• collaborative growth
• opportunities to connect knowledge to identity and purpose
Ironically, the report also found that many of these highest-impact experiences remain among the least accessible to students.
This has major implications for higher education and for the future design of AI-supported learning environments.
As institutions increasingly integrate AI, analytics, and adaptive technologies into teaching and learning, the challenge is not simply building more efficient systems. The challenge is designing learning ecosystems that preserve human connection, mentorship, exploration, and authentic application of knowledge.
This aligns closely with my ongoing doctoral research in AI-Augmented Exploratory Learning (AAEL), which examines how professionals learn, adapt, and problem-solve alongside AI systems. One of the recurring themes in both the literature and practice is that technology appears most effective when it enhances human guidance rather than replacing it.
Students may remember the technology they used.
But they often remember the people, experiences, and opportunities that helped them grow.
Source: https://lnkd.in/ddkmP96c