The Biggest Challenge for AI in Academia

What concerns you the most?

Last week, I explored several major challenges facing higher education as AI becomes a normal part of teaching and learning. Academic integrity, critical thinking, equity, and ethics are all under pressure as institutions adapt to a rapidly changing landscape.

I would love to hear from you. Of the issues we discussed, which one do you believe will have the largest impact on education over the next few years?

Poll Question: What is the biggest challenge AI creates for academic settings?

1. Academic integrity
2. Critical thinking loss
3. Bias and inequity
4. Data privacy risks

Thank you for sharing your perspective. Your insight helps shape future posts and conversations about responsible, thoughtful use of AI in education.

Poll on LinkedIn

Bias, Equity, and Ethical Concerns in Educational AI

Why responsible use cannot be optional

As AI continues to shape academic life, the conversation must extend beyond plagiarism and critical thinking. The most complex challenges involve ethics, bias, and equity. These issues affect not only how AI is used, but who benefits from it and who may be harmed by it.

AI systems are trained on vast datasets drawn from the public internet. These datasets contain the biases, assumptions, and inequities of the societies that produced them. When AI is used in admissions, grading, tutoring, or proctoring, those biases can become automated and amplified. Studies have documented disparities in facial recognition, language evaluation, and writing assessment, raising concerns about fairness for students from underrepresented or multilingual backgrounds.

There is also a growing digital divide in AI access. Premium tools offer stronger performance, but not all students can afford them. This creates a new form of academic inequality where advantages are tied not to skill or effort, but to subscription level. Ethical AI use must consider not only what the technology can do, but who is excluded when it becomes a requirement.

Privacy is another unresolved concern. Many AI tools rely on external servers and proprietary datasets. When student data is processed, stored, or used to improve commercial models, institutions must navigate compliance with FERPA, GDPR, and emerging national standards. The risks are significant and long-lasting.

For AI to serve education responsibly, institutions need clear governance, transparency, and ethical review processes. Faculty and students must understand how AI works, where its data comes from, and how its outputs should be interpreted. Ethical use is not a barrier to innovation. It is the foundation that allows AI to support learning without compromising equity or trust.

Posted to LinkedIn

The Erosion of Critical Thinking and the Risk of Student Deskilling

Protecting the core purpose of education

Education is not simply the transmission of information. It is the development of skills that allow students to think independently, solve unfamiliar problems, and understand the world with clarity and depth. This is why the rapid adoption of generative AI raises concerns that go beyond academic misconduct. The deeper worry is the gradual erosion of critical thinking itself.

AI can produce quick, polished answers to complex prompts, and the responses are often convincing enough to pass casual scrutiny. When students lean on AI for first drafts, explanations, or problem-solving, they skip the productive struggle that leads to deep learning. They bypass the process of research, synthesis, and reflection and instead accept the most immediate solution the machine provides. This is cognitive offloading at scale, and the long-term impact is a decline in foundational skills.

Faculty report widening gaps in students' writing, reasoning, and analysis. Some describe students who cannot explain work completed with AI assistance. Others see growing dependency on tools that can break at any time. If students never engage with the intellectual labor behind an answer, they lose the capacity to troubleshoot or generate original thought when AI is unavailable.

The solution is not to ban AI but to integrate it intentionally. Students must learn how to evaluate AI output, question its assumptions, compare it with credible sources, and revise it with their own insight. The presence of AI in learning environments should raise the bar for critical thinking, not lower it. We must design instruction that treats AI as a tool for inquiry rather than a shortcut for answers.

Posted to LinkedIn

Academic Integrity and Plagiarism in the AI Era

Maintaining trust in the learning process

Academic integrity has always been the foundation of higher education. Yet the rise of generative AI has created a new level of uncertainty in classrooms and assessment spaces. Students can now produce essays, code, or research summaries within seconds. The challenge is not that students are using AI, it is that the traditional markers of originality and authorship are harder to verify than ever.

Detection tools were expected to solve this problem, but research shows they often create more harm than good. Some systems flag human writing as AI generated. Others allow AI written content to pass without notice. International reports highlight dramatic increases in academic misconduct cases, particularly where institutions rely heavily on flawed detection technology. The result is a landscape where genuine student work can be questioned while AI generated work slips through unchallenged.

AI has also forced us to reconsider the very definition of plagiarism. Is it misconduct to ask AI for an outline? What about using it to rewrite a paragraph? Students are already using these tools, and they often see them as no different from spell checkers or grammar assistants. Educators must determine how to draw clear lines between acceptable support and the outsourcing of intellectual labor.

If we want academic integrity to survive this moment, we cannot rely on detection. We must redesign assessment practices. Assignments that require process, reflection, revision, and personal context are far more resilient to AI misuse. In the end, AI should enhance learning, not replace it. Our job is to ensure students still develop their own voice, judgment, and scholarly identity.

Posted to LinkedIn

The Responsible Use of AI in Academic Settings

How to make AI trustworthy in learning environments

Recently, I asked a popular AI system to summarize several books I have written. It performed well, for the most part, but it invented a book out of thin air. The imaginary book sounded interesting, and I may write it someday, but in a research assignment, this would have been a clear failure. The example illustrates a simple truth. AI cannot be accurate without proper guidance.

AI can support research, writing, and analysis, but only when used with clear safeguards. No AI system is perfect, yet we can design prompts that improve accuracy and reduce hallucinations. The most reliable method is to require evidence. Ask the AI to search for current data, provide citations, and explain its reasoning. For complex or controversial topics, request multiple viewpoints to uncover potential bias.

Academic integrity also depends on verification. For any time-sensitive claim or statistical fact, require sources from peer-reviewed journals or government datasets. Then cross-check what matters most. AI should accelerate research, not replace the work of evaluating sources.

The goal is not perfection. The goal is transparency. When AI documents its process, educators can examine the evidence and trust the result.

At the moment, AI tools face the same legitimacy concerns that surrounded Wikipedia nearly twenty years ago. As both tools mature, they gain traction in academic spaces. Yet just as instructors should not accept a copy and paste from Wikipedia, they should not accept an unverified output from any AI chatbot. Both should be viewed as the beginning of research, not the final product.

Posted to LinkedIn

Feeding the Future

What’s the biggest barrier to universal free breakfast?

This week, we explored how free breakfast in early childhood education does more than feed children;  it fuels learning.

 The research is clear: universal breakfast programs improve attendance, behavior, and focus, while reducing stigma and hunger.

Yet implementation remains uneven. Some schools thrive with breakfast-in-the-classroom models, while others struggle with funding or logistics.

I’d love to hear from you: What’s the greatest challenge your school or organization faces when trying to make breakfast free and accessible for all students?

Poll Question:

What’s the biggest barrier to universal free breakfast?

•  Funding & budget limits
  
  
•  Staffing & logistics
  
  
•  Policy & compliance rules
  
  
•  Cultural or parental buy-in

Your experiences and insights can help shape better policies and stronger programs for our youngest learners.

Building a Culture of Nourishment

From feeding programs to learning ecosystems

Early childhood programs thrive when learning begins with care. Free breakfast supports cognitive readiness, social connection, and equity, all before the first lesson starts. A review from Frontiers in Human Neuroscience  found that schools offering universal breakfast saw stronger attendance and fewer behavioral issues.

Breakfast is professional development for the brain. When we treat it as part of instruction rather than an optional service, we nurture both hearts and minds.

What if “ready to learn” began with “ready to eat”?

References

Adolphus K, Lawton CL, Dye L. The effects of breakfast on behavior and academic performance in children and adolescents. Front Hum Neurosci. 2013 Aug 8;7:425. doi: 10.3389/fnhum.2013.00425. PMID: 23964220; PMCID: PMC3737458.

https://pmc.ncbi.nlm.nih.gov/articles/PMC3737458/

 FRAC (2024). Benefits of School Breakfast.

https://frac.org/programs/school-breakfast-program/benefits-school-breakfast

 No Kid Hungry (2023). School Breakfast Program Factsheet.

https://www.nokidhungry.org/sites/default/files/pdfs/school-breakfast-program-factsheet.pdf

Posted to LinkedIn

When Breakfast Meets Learning

Connecting nutrition and classroom outcomes

I have been working more eggs into my breakfast routine. I don't actually like eggs, so I am only eating boiled egg whites. But research this week suggests I consider more ways to eat them. 

A growing body of research links breakfast participation to measurable academic benefits. An early review in the American Dietetic Association reported improved attendance and fewer tardies when schools provided breakfast at no cost. Students also showed higher intake of iron, calcium, and vitamins, nutrients essential for brain development.

In the U.S., the School Breakfast Program serves over 2.5 billion meals yearly. When breakfast moved from the cafeteria to the classroom, participation rose from 37 percent to 94 percent, and diet quality improved.

Healthy starts lead to healthy learning.

Could moving breakfast into the classroom increase participation in your school setting?

References

 Pollitt, E.. (1995). Does Breakfast Make a Difference in School? Journal of the American Dietetic Association, Volume 95, Issue 10, 1134 - 1139

https://www.jandonline.org/article/S0002-8223(95)00306-1/abstract

 USDA ERS (2024). Child Nutrition Programs: School Breakfast Program.

https://www.ers.usda.gov/topics/food-nutrition-assistance/child-nutrition-programs/school-breakfast-program

 School Nutrition Association (2025). Egg-Based Universally Free Breakfast Pilot.

https://schoolnutrition.org/journal/spring-2025-an-egg-based-universally-free-breakfast-in-the-classroom-program-increases-school-breakfast-participation-and-improves-diet-quality-in-middle-school-adolescents-a-feasibility-pilo/

Posted to LinkedIn

The Power of Universal Access

Free breakfast and the fight against stigma

Programs that offer breakfast only to those who qualify can unintentionally create stigma. Universal free breakfast removes that barrier. Research from the University of Washington’s Health Services Population Center found that universal meal programs improved student health outcomes and increased participation among low-income families.

When everyone eats together, no one feels singled out. A New Zealand study showed that universal breakfast improved attendance and classroom behavior, particularly in early grades.

Providing breakfast for all is not charity; it is a strategy.

If you could redesign your institution’s breakfast model, would you choose universal access?

References

 UW Health Services Population Center (2024). Universal Free School Meals: A key ingredient in improving childhood health outcomes.

https://hspop.uw.edu/universal-free-school-meals-improve-health-outcomes/Outcomes.

Gontijo de Castro T, Gerritsen S, Santos LP, Marchioni DML, Morton SMB, Wall C. Child feeding indexes measuring adherence to New Zealand nutrition guidelines: Development and assessment. Matern Child Nutr. 2022 Oct;18(4):e13402. doi: 10.1111/mcn.13402. Epub 2022 Jul 19. PMID: 35851558; PMCID: PMC9480915.

https://pmc.ncbi.nlm.nih.gov/articles/PMC9480915/

Posted to LinkedIn

Hungry to Learn

Why breakfast is the first lesson of the day.

Every morning, thousands of children arrive at school without breakfast. What seems small has an outsized impact. Research from the Food Research & Action Center shows that children who skip breakfast are less able to master the tasks needed to do well in school. Those who eat breakfast at school perform better on standardized tests and attend more consistently.

The reason is simple: nutrition drives cognition. Young learners depend on steady energy for attention, memory, and emotional regulation. When we ensure every child starts the day fed, we set the tone for focus and belonging.

Hunger is not just a health issue; it is a learning barrier.

How does your learning institution make sure no child begins the day hungry?

References

Food Research & Action Center (2024). Benefits of School Breakfast.

https://frac.org/programs/school-breakfast-program/benefits-school-breakfast

No Kid Hungry (2023). School Breakfast Program Factsheet.

https://www.nokidhungry.org/sites/default/files/pdfs/school-breakfast-program-factsheet.pdf

Posted to LinkedIn

The Culture of Continuous Learning

Building schools that learn as fast as their students

The best schools do not just teach learning, they live it.

Continuous learning is more than a phrase we use in mission statements. It is a leadership model that values curiosity, reflection, and growth at every level of an organization. When leaders create environments where experimentation is encouraged, feedback is shared, and professional growth never stops, they set the tone for meaningful transformation.

•  Teachers learn from data.
  
  
•  Leaders learn from teachers.
  
  
•  Institutions learn from mistakes.

In a world where knowledge doubles every few years, agility has become the new measure of accountability. An authentic learning culture turns change from a source of anxiety into a source of energy. It helps schools and organizations move from reacting to reinventing.

I once worked with a non-academic institution that hosted “research days.” Everyone was encouraged to explore new topics or personal areas of interest in depth, often unrelated to their daily work. The goal was to spark connections and fresh insights that would later strengthen their primary responsibilities. I began to look forward to those days, though I still had to remind myself not to check emails or tell myself, “I’ll just work a little bit.” The lesson was clear: time for exploration is not time lost, it is time invested in learning how to learn again.

What does “continuous learning” look like in your organization?

Posted to LinkedIn

Innovation vs. Initiative Overload

Why focus beats novelty

Every year brings a new “must-have” program, AI tools, SEL frameworks, gamified learning, microcredentials, each promising transformation. But when everything is a priority, nothing is.

True innovation doesn’t come from adding more. It comes from aligning what already works.

Before launching the next initiative, ask:

•  Does this align with our core mission?
  
  
•  Does it solve a real pain point for teachers or students?
  
  
•  Can we sustain it for more than a year?

Innovation needs to be a mindset, not a shopping list. Schools that focus on fewer, deeper goals create space for real creativity, and protect educators from burnout.

If you had to drop one initiative tomorrow to focus on what matters most, what would it be?

Posted to LinkedIn

Data-Informed, Not Data-Driven

Rethinking analytics in education

I talk a lot about data, and we have more data than ever, but not always more insight.

Being data-driven can unintentionally replace human judgment with dashboards and KPIs. Being data-informed means using numbers as a conversation starter, not a verdict.

In classrooms, analytics can highlight patterns, but it’s the teacher who understands why. In leadership, metrics reveal performance, but culture determines progress.

Let’s use data to:

 * Illuminate, not dictate

 * Ask better questions, not give easy answers

 * Empower decisions, not replace them

Data should serve educators, not the other way around. When combined with experience, empathy, and context, it becomes truly transformative.

How do you ensure data supports, rather than controls, your decision-making?

Posted to LinkedIn 

Leading Through Change Fatigue

Helping teachers adapt without burning out

Change isn’t the problem in education; the pace of change is.

New technologies, new standards, new initiatives... all arriving faster than schools can adapt. The result? Change fatigue.

Teachers and instructional staff feel caught in a loop of “just one more thing,” often without time to reflect, refine, or rest. The solution isn’t to stop changing, it’s to lead change differently.

• Create psychological safety for experimentation
  
  
• Prioritize depth over speed
  
  
• Celebrate iteration, not perfection

Leaders who model adaptability, transparency, and trust transform resistance into resilience.

In the AI era, schools don’t need more change; they need better rhythms of change.

What’s one leadership practice that helps your team manage change sustainably?

Posted to LinkedIn