Gen AI is not the problem: Reimagining Resource-Rich Learning Environments

GenAI IS NOT the Problem: Reimagining Resource-Rich Learning Environments

Dr. Morris Thomas,PhD,MBA,PMP Provost/Vice President for Academic Affairs & Professor of Higher Education Administration

 

"The continued use of lecture is malpractice at best or an act of discrimination at worst."

When Handelsman and colleagues published this assertion in 2022, it illuminated a deeper truth about higher education: we are remarkably resistant to examining and transforming our own practices, even when evidence demands it. Whether I'm facilitating a panel at an international conference or consulting with faculty domestically, the conversation inevitably turns to generative AI, and the framing is almost always the same: GenAI is the problem. Students are cheating. Academic integrity is under attack. Neither phenomenon is new; technologies emerge and academic misconduct has existed as long as academia itself. What strikes me is our failure to reflect on what these patterns reveal about learning environments. We focus so intently on student behavior that we fail to interrogate the conditions shaping it. Generative AI has not ruined academia but has instead exposed pre-existing gaps in how we facilitate and assess learning. What if the GenAI "crisis" is a mirror reflecting the resource deficiencies in our learning environments? This mirror does more than expose deficiencies—it reveals precisely where reimagining must begin.

Consider research on crime in economically deprived communities. Strain Theory suggests individuals resort to illegitimate means when legitimate pathways to success are blocked. Social Disorganization Theory points to weakened community structures as conditions breeding misconduct. Economic Deprivation Theory describes how lack of resources drives individuals to seek alternative means of meeting needs. As faculty, we are responsible for creating learning communities to meet specific outcomes. When students cannot see viable pathways to success because assessments are disconnected from their lives, instructional methods fail to engage them, or they feel unseen, some will seek alternative routes. GenAI becomes not a cause of misconduct but a tool for navigating environments that feel resource-deficient.

This is not to excuse academic dishonesty. Rather, our response must go beyond detection and punishment. We must ask: "Why would students feel compelled to misuse these tools?" And more importantly: "How do we create learning environments so resource-rich that authentic engagement becomes the preferred path?"

Consider our language. We "teach a class," framing that centers the instructor rather than the learner. In medicine, practitioners speak of "patient care" and their "practice," language that inherently centers the patient and recognizes that practice must evolve to address changing needs. Yet our syllabi often fit paradigms from decades past. Our learners are different. The workforce has transformed. So must our approach.

Reimagining resource-rich learning environments requires a deliberate framework. This brings me to The WHOLE Experience Framework (WEF), an approach centered on creating learning environments that are Welcoming, Holistic, Open, Liberating, and Empowering. These components are not hierarchical or sequential. Each enriches the learning environment in a distinct way. When these elements are present, the motivation for misconduct diminishes because students find themselves in communities where their needs are met, their humanity acknowledged, and success feels achievable through authentic means.

The Welcoming component addresses relational resource deficiency, reducing the adversarial dynamic breeding misconduct. When students feel they belong and perceive genuine care, they communicate struggles rather than seeking shortcuts.

The Holistic component recognizes that students need GenAI literacy alongside content mastery. Do they understand the limitations, hallucinations, biased outputs, fabricated citations? Teaching students to navigate AI's ethical implications adds critical resources to their intellectual toolkit, preparing them for an AI-saturated world.

The Open component builds transparency as a resource, requiring clarity about GenAI expectations: "For this assignment, you may use GenAI to brainstorm, but your analysis must be your own. Document which tool you used, what prompts you entered, and how you refined the output." This transforms GenAI from cheating mechanism into learning tool.

The Liberating component addresses our assessment crisis by expanding what counts as evidence of learning. Rather than one-size-fits-all assignments that students either complete authentically or circumvent through AI, liberating environments offer multiple pathways. A student might demonstrate mastery of historical analysis through a research paper, documentary script, podcast, or digital exhibit. This is resource richness: abundant options rather than artificial scarcity.

The Empowering component connects assessments to students' lives and positions them as creators rather than mere consumers of knowledge. Consider an assignment where students use GenAI to generate an initial draft, critically evaluate it for bias and accuracy, then produce their own enhanced version with reflective commentary. This is AI-proof not because it prohibits technology but because it requires higher-order thinking technology cannot replicate.

Here is the essential question: "Why must evidence of competencies be absent of available technology?" The issue is not use but misuse. When we insist students demonstrate understanding without technological assistance, we prepare them for a world that no longer exists. Students do not need increased surveillance and accusation. They need what only humans can provide: care, empathy, presence, and responsive engagement. GenAI cannot create these elements. These human elements are the ultimate resources, precisely what transform deficient learning environments into thriving ones.

The path forward requires courage to examine our practices, listen to student feedback, and transform approaches that may have served us well in a different era but no longer meet the moment. GenAI has not created a crisis; it has revealed one that already existed. The WHOLE Experience Framework offers a blueprint for reimagining environments rich in pathways, transparency, literacy, belonging, and agency. Let us use our brilliance and energy not to build higher walls, but to create environments so resource-rich that students choose to stay inside them.