Imagine a world where faculty and staff actually enjoy classifying data. You can’t, can you? It’s almost impossible to picture, but what if aligning our policies with better practices could make compliance feel a little less painful? In this week’s issue, we explore a University of Wisconsin-Madison study tackling the ongoing challenge of bridging the gap between data policy and practice. After that, we discuss the importance of student trust in institutions before closing with a look at why writing matters more than ever in the age of AI.   

After reading today’s issue, use the comments section to share how your institution classifies data. 

Improving Data Classification Practices 

From Policies and Practices: How to Improve Data Classification in Higher Education | EDUCAUSE Review  

As colleges and universities collect and use more data for more purposes, understanding how to organize and safeguard it becomes critically important.   

Our Thoughts 

Even as a self-proclaimed data nerd, I couldn’t help but chuckle near the end of this article when I read, “People do not organize their lives around data classifications.” Data classification is a thankless and never-ending task at institutions. However, as we increasingly rely on data to drive decisions and power AI chatbots, this work has become more than just an administrative burden. It plays a critical role in cybersecurity, compliance, and risk management.  

The University of Wisconsin-Madison’s study highlights a clear disconnect between data policy and real-world practice. Many faculty and staff struggle with unclear guidelines, inconsistent implementation, and a lack of training for handling classified data. This misalignment creates serious vulnerabilities in regulatory compliance with FERPA and HIPAA, as well as in mitigating cybersecurity risks.  

One aspect I particularly appreciated about this article is that the authors don’t just highlight the problem, but they also offer practical solutions. Their recommendations provide a roadmap for institutions to align data policies with actual practice by improving training, clarifying guidelines, and ensuring policies are truly integrated into institutional workflows. By closing the gap between policy design and real-world application, institutions can turn data governance from a compliance headache into a strategic advantage. 

Students Trust Professors the Most 

From Trust Matters | Inside Higher Ed  

According to Inside Higher Ed’s annual Student Voice survey, students trust their professors the most and campus senior leadership the least.   

Our Thoughts 

Trust is a cornerstone of institutional success. The level of trust students have in their institution shapes their experiences, engagement, and outcomes, and directly affects retention and graduation rates. Students are far less likely to remain at an institution if they do not trust that it prioritizes their best interests. Would you stay with an employer if you didn’t trust its leadership?  

The survey highlights that the most trusted figures on campus are those with whom students have the most direct contact—their professors and academic advisors. This is significant because it suggests institutions could leverage these individuals as primary channels for building student confidence and trust. Strengthening these relationships may also improve communication and transparency, key components of trust that institutions should actively measure and cultivate.  

Perhaps the most striking discovery in the survey is the trust gap between students and college and university presidents. While leadership roles naturally face scrutiny, this data points to a deeper disconnect between senior administrators and the students they serve. Political tensions, institutional controversies, or broader societal distrust may play a role, but at its core, this gap suggests that leaders aren’t effectively engaging with their student communities. The article offers practical solutions for bridging this divide, including active listening sessions and demonstrating clear alignment between institutional values and actions.  

Ultimately, senior institutional leaders must reassess how they build and maintain trust on campus. Ensuring that all members of the community feel heard, valued, and supported isn’t just a public relations strategy. It’s essential to institutional success. 

Why Writing Matters in the Age of AI 

From The Edge: Writing in the age of AI | The Chronicle of Higher Education  

John Warner discusses his new book on writing, arguing that “writing is thinking” and goes beyond what AI can produce.  

Our Thoughts  

So, you might be thinking, “Wait, I work with data. Why are you sharing an article about the importance of writing?” but bear with me. In his book, Warner’s “writing is thinking” argument challenges the transactional model of education that prioritizes the finished product over the cognitive and reflective journey. Our formulaic approach to writing instruction, where rigid assessments favor polished output over deeper learning, is exactly the kind of work that AI can easily replace. This presents a challenge that directly connects to our work with data.  

When we substitute AI for the natural learning process of reflection and growth, we risk losing the ability to discern context for our work. And as we know, context is vital in data analysis. It adds meaning to raw numbers and helps inform better decisions. AI-generated analysis, without human insight, risks becoming another member of the “Datasaurus dozen“—technically accurate but missing the bigger picture. The institutional knowledge and contextual understanding that you bring to the table remain irreplaceable.  

Warner also raises broader concerns about AI’s impact on professional development. If AI automates entry-level tasks that once helped young professionals build expertise, we could end up with a workforce that lacks essential foundational skills in their profession. Institutions must not only teach students how to use AI effectively but also ensure that its use does not erode critical thinking, creativity, or deep learning. Warner’s emphasis on depth over volume and intellectual curiosity over efficiency is a call to action for educators. Instead of allowing AI to deskill students, we should focus on creating learning environments that empower them to become thoughtful, engaged writers and thinkers.