Tag: Power

From Policing to Pedagogy: Navigating AI’s Transformative Power – Faculty Focus

The rapid integration of generative artificial intelligence (GenAI) into higher education has reignited a familiar moral panic around academic dishonesty. While much of the immediate institutional response has centered on detection and enforcement, this reaction echoes a familiar pattern—one that treats academic dishonesty as an individual moral failure rather than a symptom of broader systemic issues (Bertram Gallant, 2008). Students, faced with overloaded schedules, mounting debt, and an unforgiving emphasis on grades, often make pragmatic decisions about where to invest their time and effort gravitating toward efficiency and certainty over exploration and risk. In this environment, the ethical clarity around “cheating” becomes murky—not because students don’t understand right from wrong, but because the structures around them reward efficiency and penalize risk. AI tools such as ChatGPT or Grammarly simply fit into this equation as time-saving devices—much like calculators, Google, or even essay mills before them. What has shifted is not the motivation, but the accessibility. A student’s use of AI is a reflection of the transactional nature of how learning is often experienced in contemporary institutions.

The proliferation of AI tools has not so much introduced a new problem as it has exposed the fragility of existing educational structures. Before we focus on what AI changes, we must confront what it reveals: that higher education has long incentivized a culture of performance over learning. Research has shown that when students perceive academic work as irrelevant, overly procedural, or divorced from their goals and identities, they disengage—regardless of whether AI is available (Ambrose et al., 2010). In this light, the question is not “How do we catch them?” but rather, “What kind of learning environments have we built that make outsourcing feel logical or even necessary?” This reframing shifts the pedagogical conversation from one of compliance and control to one of capacity-building and curiosity. If we can use this moment to ask how to foster a culture of learning that values growth over grades, process over product, and understanding over output, then AI may serve not as a threat to education but as a catalyst for its reinvention.

Why Students Turn to AI

When students turn to generative AI to complete assignments, they are not necessarily demonstrating a lack of understanding or unethical behavior—they are often responding rationally to the conditions of their academic lives. In surveys and interviews, students routinely cite overwhelming workloads, unclear expectations, time scarcity, and mental health struggles as reasons they seek shortcuts or support tools (McCabe, Treviño, & Butterfield, 2001; Pascoe, Hetrick, & Parker, 2020). AI fits seamlessly into a landscape where efficiency is often more highly rewarded than curiosity. Faced with tasks that feel repetitive, decontextualized, or performative, many students learn that their survival depends on doing just enough, not necessarily doing it deeply.

When a student uses AI to write a discussion post or summarize an article, the act is not just a form of evasion—it’s often a judgment about the value of the task itself. If the assignment doesn’t ask them to do something personally meaningful, intellectually stimulating, or clearly useful for their future goals, it becomes an obligation to manage rather than a learning opportunity to embrace. This disconnect is further amplified by the unspoken norms that teach students to prioritize grades, speed, and performance over exploration, failure, and growth (Margolis, 2001). In such a climate, using AI can feel less like cheating and more like optimization. Students aren’t necessarily trying to game the system—they’re playing the game as they perceive it was designed.

The challenge, then, is not to eliminate AI from the learning process, but to design learning experiences that make authentic engagement the easier, more meaningful choice. Rather than dismissing AI use as evidence of student laziness or misconduct, educators might ask: What does the pattern of AI usage tell us about how students experience our courses? What if the real issue isn’t student behavior but assignment design and instructional culture? By attending to these questions, we shift the focus from enforcement to empathy—from trying to control student actions to trying to understand their motivations and constraints.

Process Over Product

If generative AI makes it easier for students to produce work without deeply engaging in the learning process, it invites faculty to reconsider what their assessments are really measuring. Too often, traditional assessments prioritize polished outputs—essays, quizzes, presentations—over the messy, iterative, and uncertain processes that lead to genuine understanding. These conventional formats may reward conformity and correctness, but they do little to cultivate the flexibility, reflection, and critical thinking required in a world shaped by automation and ambiguity.

In contrast, AI offers a lens through which educators can reassess their learning goals: Are students being asked to think or to comply? To demonstrate mastery or to demonstrate growth? Increasingly, the competencies that matter most in both life and work—such as collaboration, problem framing, ethical reasoning, and the ability to adapt—are not easily captured through static, time-bound tasks (National Academies of Sciences, Engineering, and Medicine, 2018). Nor are they easily outsourced to AI. These are precisely the skills that thrive when assessment shifts from evaluating finished products to examining students’ thinking and decision-making processes along the way.

Emerging research on assessment design suggests that when students are asked to reflect on how they used AI, evaluate its limitations, compare its outputs to their own, or build on AI-generated responses with original insights, they begin to see these tools not as shortcuts but as thought partners (Mollick & Mollick, 2023; Popenici & Kerr, 2017). This approach not only fosters academic integrity, but also helps students develop the judgment, discernment, and contextual understanding that AI cannot replicate. Moreover, process-oriented assessments are more inclusive. They allow students with diverse learning styles, linguistic backgrounds, and levels of prior knowledge to demonstrate learning in multiple ways. They also encourage metacognition—students thinking about their own thinking—which is known to enhance long-term retention and transfer of learning (Ambrose et al., 2010). Rethinking assessment does not mean lowering standards; it means realigning them with the kinds of learning we claim to value. When assessments emphasize authentic engagement over mere output, they become more resilient to automation—and more relevant to the lives students are preparing to lead.

Disciplinary Innovation

While discussions about AI in education often remain abstract or policy-focused, meaningful change is already taking root within disciplines as faculty reimagine how to integrate AI into the logic of their fields. Rather than banning its use outright, many instructors are embedding AI into course design in ways that mirror authentic disciplinary practices. The goal is not just to accommodate new tools, but to cultivate students’ judgment in using them—aligning learning with the actual thinking, creating, and problem-solving expected in professional contexts.

Creative Disciplines

In design, media production, and the arts, instructors are moving beyond static portfolio reviews and embracing reflective, process-based documentation. Students are asked to keep iterative journals that detail how their ideas evolved, what role AI tools played in generating or refining concepts, and how creative decisions were made at each stage. This encourages fluency with new tools while reinforcing core disciplinary values: originality, intentionality, and critique. As Sullivan (2010) and McArthur & White (2021) argue, creative practice is inherently dialogic, and integrating AI into that dialogue allows students to develop their own voices in conversation with machine-generated suggestions.

Simulating Complexity

In fields such as public administration, business, and marketing, instructors are shifting from case-study write-ups to scenario-based simulations and role-playing exercises. These assessments ask students to evaluate data, propose interventions, justify decisions, and communicate across stakeholder perspectives. AI-generated content may be introduced as one data source among many, prompting students to critique its assumptions, identify potential biases, or integrate it with qualitative insights. This simulates real-world complexity and ethical ambiguity—core aspects of professional judgment that cannot be easily automated (Farrell, 2023; Wiggins, 2016).

Modeling Scientific Reasoning

In the sciences, instructors are piloting assignments that blend AI-assisted analysis with human critique. For example, students might be given an AI-generated interpretation of experimental data and asked to assess its validity, identify methodological flaws, or propose alternative explanations. These tasks promote skills fundamental to scientific reasoning: skepticism, data literacy, and peer review. As Wieman (2017) and Holmes, Wieman, & Bonn (2015) have shown, such approaches encourage deeper engagement with the epistemological foundations of science—what counts as evidence, how claims are justified, and why precision matters.

Building AI Fluency Across the Curriculum

To meet the demands of a world increasingly shaped by automation, higher education must move beyond treating AI as an external threat and begin cultivating AI fluency as a foundational component of 21st-century learning. AI fluency goes beyond knowing how to use tools like ChatGPT or Midjourney—it encompasses the ability to understand how AI systems work, critically evaluate their outputs, use them ethically, and reflect on their broader social and disciplinary implications (Long & Magerko, 2020; Luckin et al., 2016).

Integrating AI fluency into the curriculum means designing assignments that treat AI not as a banned shortcut or unexamined assistant, but as a subject of inquiry. Students should be taught to interrogate the design of AI tools, including how they are trained, what kinds of data they rely on, and how they reflect or reinforce existing social biases. Courses across disciplines can include assignments that ask students to compare AI-generated outputs with human-created work, evaluate their quality and assumptions, or explore how different prompts lead to different results. These tasks cultivate what Holmes, Bialik, & Fadel (2019) describe as “cognitive partnership”—the ability to think with, through, and about technology, rather than simply accepting its outputs.

Building AI fluency involves normalizing reflective practice. Students should be encouraged to articulate how and why they used AI tools in the completion of an assignment: What choices did they make? What did the AI get right—or wrong? How did it shape their thinking? This kind of metacognitive work not only deepens learning, but also demystifies AI as a black box and empowers students to use it responsibly (Mollick & Mollick, 2023).

Crucially, AI fluency should not be siloed within STEM or computer science. Every field—from history to healthcare, literature to law—will be transformed by AI in some way, and students in every discipline deserve the opportunity to engage critically with those transformations. Developing AI fluency as a form of literacy positions students to become not just competent users of technology, but thoughtful citizens capable of shaping its role in society.

The task before educators is not merely to regulate AI use, but to reimagine what it means to be educated in an age of intelligent machines. By embedding AI fluency into course outcomes, assessment practices, and institutional values, higher education can help students navigate this new landscape with agency, insight, and integrity.

The text was generated in collaboration with Gemini (2.5 Flash), Google’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.

References

Ambrose, Susan A., Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, and Marie K. Norman. How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco: Jossey-Bass, 2010.

Bertram Gallant, Tricia. Academic Integrity in the Twenty-First Century: A Teaching and Learning Imperative. San Francisco: Jossey-Bass, 2008.

Farrell, Paul. “Integrating AI into Public Administration Education: Risks and Rewards.” Journal of Public Affairs Education 29, no. 1 (2023): 45–58.

Holmes, Wayne, Maya Bialik, and Charles Fadel. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign, 2019.

Holmes, N. G., Carl E. Wieman, and Doug A. Bonn. “Teaching Critical Thinking.” Proceedings of the National Academy of Sciences 112, no. 36 (2015): 11199–204.

Long, David, and Brian Magerko. “What Is AI Literacy? Competencies and Design Considerations.” In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. New York: ACM, 2020.

Luckin, Rose, Wayne Holmes, Mark Griffiths, and Laurie B. Forcier. Intelligence Unleashed: An Argument for AI in Education. London: Pearson, 2016.

Margolis, Eric. The Hidden Curriculum in Higher Education. New York: Routledge, 2001.

McArthur, Janine A., and Betty White. “Redesigning Creativity: AI, Agency, and Reflective Practice in the Visual Arts.” International Journal of Art & Design Education 40, no. 2 (2021): 437–51.

McCabe, Donald L., Linda Klebe Treviño, and Kenneth D. Butterfield. “Cheating in Academic Institutions: A Decade of Research.” Ethics & Behavior 11, no. 3 (2001): 219–32.

Mollick, Ethan, and Lilach Mollick. “Assigning AI: Seven Approaches for Students with Prompts.” Working paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4573321 (accessed July 8, 2025).

National Academies of Sciences, Engineering, and Medicine. How People Learn II: Learners, Contexts, and Cultures. Washington, D.C.: The National Academies Press, 2018.

Pascoe, Michaela C., Rosanna M. Hetrick, and Alexandra G. Parker. “The Impact of Stress on Students in Secondary School and Higher Education.” International Journal of Adolescence and Youth 25, no. 1 (2020): 104–12.

Popenici, Stefan C., and Sharon Kerr. “Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education.” Research and Practice in Technology Enhanced Learning 12, no. 1 (2017): 1–13.

Sullivan, Graeme. Art Practice as Research: Inquiry in the Visual Arts. Thousand Oaks, CA: SAGE Publications, 2010.

Wieman, Carl E. “The Similarities between Research in Education and Research in the Hard Sciences.” Educational Researcher 46, no. 6 (2017): 319–29.

Wiggins, Grant. “A True Test: Toward More Authentic and Equitable Assessment.” Educational Leadership 70, no. 6 (2016): 28–33.

Source link

September 5, 2025
From Policing to Pedagogy: Navigating AI’s Transformative Power – Faculty Focus

The rapid integration of generative artificial intelligence (GenAI) into higher education has reignited a familiar moral panic around academic dishonesty. While much of the immediate institutional response has centered on detection and enforcement, this reaction echoes a familiar pattern—one that treats academic dishonesty as an individual moral failure rather than a symptom of broader systemic issues (Bertram Gallant, 2008). Students, faced with overloaded schedules, mounting debt, and an unforgiving emphasis on grades, often make pragmatic decisions about where to invest their time and effort gravitating toward efficiency and certainty over exploration and risk. In this environment, the ethical clarity around “cheating” becomes murky—not because students don’t understand right from wrong, but because the structures around them reward efficiency and penalize risk. AI tools such as ChatGPT or Grammarly simply fit into this equation as time-saving devices—much like calculators, Google, or even essay mills before them. What has shifted is not the motivation, but the accessibility. A student’s use of AI is a reflection of the transactional nature of how learning is often experienced in contemporary institutions.

The proliferation of AI tools has not so much introduced a new problem as it has exposed the fragility of existing educational structures. Before we focus on what AI changes, we must confront what it reveals: that higher education has long incentivized a culture of performance over learning. Research has shown that when students perceive academic work as irrelevant, overly procedural, or divorced from their goals and identities, they disengage—regardless of whether AI is available (Ambrose et al., 2010). In this light, the question is not “How do we catch them?” but rather, “What kind of learning environments have we built that make outsourcing feel logical or even necessary?” This reframing shifts the pedagogical conversation from one of compliance and control to one of capacity-building and curiosity. If we can use this moment to ask how to foster a culture of learning that values growth over grades, process over product, and understanding over output, then AI may serve not as a threat to education but as a catalyst for its reinvention.

Why Students Turn to AI

When students turn to generative AI to complete assignments, they are not necessarily demonstrating a lack of understanding or unethical behavior—they are often responding rationally to the conditions of their academic lives. In surveys and interviews, students routinely cite overwhelming workloads, unclear expectations, time scarcity, and mental health struggles as reasons they seek shortcuts or support tools (McCabe, Treviño, & Butterfield, 2001; Pascoe, Hetrick, & Parker, 2020). AI fits seamlessly into a landscape where efficiency is often more highly rewarded than curiosity. Faced with tasks that feel repetitive, decontextualized, or performative, many students learn that their survival depends on doing just enough, not necessarily doing it deeply.

When a student uses AI to write a discussion post or summarize an article, the act is not just a form of evasion—it’s often a judgment about the value of the task itself. If the assignment doesn’t ask them to do something personally meaningful, intellectually stimulating, or clearly useful for their future goals, it becomes an obligation to manage rather than a learning opportunity to embrace. This disconnect is further amplified by the unspoken norms that teach students to prioritize grades, speed, and performance over exploration, failure, and growth (Margolis, 2001). In such a climate, using AI can feel less like cheating and more like optimization. Students aren’t necessarily trying to game the system—they’re playing the game as they perceive it was designed.

The challenge, then, is not to eliminate AI from the learning process, but to design learning experiences that make authentic engagement the easier, more meaningful choice. Rather than dismissing AI use as evidence of student laziness or misconduct, educators might ask: What does the pattern of AI usage tell us about how students experience our courses? What if the real issue isn’t student behavior but assignment design and instructional culture? By attending to these questions, we shift the focus from enforcement to empathy—from trying to control student actions to trying to understand their motivations and constraints.

Process Over Product

If generative AI makes it easier for students to produce work without deeply engaging in the learning process, it invites faculty to reconsider what their assessments are really measuring. Too often, traditional assessments prioritize polished outputs—essays, quizzes, presentations—over the messy, iterative, and uncertain processes that lead to genuine understanding. These conventional formats may reward conformity and correctness, but they do little to cultivate the flexibility, reflection, and critical thinking required in a world shaped by automation and ambiguity.

In contrast, AI offers a lens through which educators can reassess their learning goals: Are students being asked to think or to comply? To demonstrate mastery or to demonstrate growth? Increasingly, the competencies that matter most in both life and work—such as collaboration, problem framing, ethical reasoning, and the ability to adapt—are not easily captured through static, time-bound tasks (National Academies of Sciences, Engineering, and Medicine, 2018). Nor are they easily outsourced to AI. These are precisely the skills that thrive when assessment shifts from evaluating finished products to examining students’ thinking and decision-making processes along the way.

Emerging research on assessment design suggests that when students are asked to reflect on how they used AI, evaluate its limitations, compare its outputs to their own, or build on AI-generated responses with original insights, they begin to see these tools not as shortcuts but as thought partners (Mollick & Mollick, 2023; Popenici & Kerr, 2017). This approach not only fosters academic integrity, but also helps students develop the judgment, discernment, and contextual understanding that AI cannot replicate. Moreover, process-oriented assessments are more inclusive. They allow students with diverse learning styles, linguistic backgrounds, and levels of prior knowledge to demonstrate learning in multiple ways. They also encourage metacognition—students thinking about their own thinking—which is known to enhance long-term retention and transfer of learning (Ambrose et al., 2010). Rethinking assessment does not mean lowering standards; it means realigning them with the kinds of learning we claim to value. When assessments emphasize authentic engagement over mere output, they become more resilient to automation—and more relevant to the lives students are preparing to lead.

Disciplinary Innovation

While discussions about AI in education often remain abstract or policy-focused, meaningful change is already taking root within disciplines as faculty reimagine how to integrate AI into the logic of their fields. Rather than banning its use outright, many instructors are embedding AI into course design in ways that mirror authentic disciplinary practices. The goal is not just to accommodate new tools, but to cultivate students’ judgment in using them—aligning learning with the actual thinking, creating, and problem-solving expected in professional contexts.

Creative Disciplines

In design, media production, and the arts, instructors are moving beyond static portfolio reviews and embracing reflective, process-based documentation. Students are asked to keep iterative journals that detail how their ideas evolved, what role AI tools played in generating or refining concepts, and how creative decisions were made at each stage. This encourages fluency with new tools while reinforcing core disciplinary values: originality, intentionality, and critique. As Sullivan (2010) and McArthur & White (2021) argue, creative practice is inherently dialogic, and integrating AI into that dialogue allows students to develop their own voices in conversation with machine-generated suggestions.

Simulating Complexity

In fields such as public administration, business, and marketing, instructors are shifting from case-study write-ups to scenario-based simulations and role-playing exercises. These assessments ask students to evaluate data, propose interventions, justify decisions, and communicate across stakeholder perspectives. AI-generated content may be introduced as one data source among many, prompting students to critique its assumptions, identify potential biases, or integrate it with qualitative insights. This simulates real-world complexity and ethical ambiguity—core aspects of professional judgment that cannot be easily automated (Farrell, 2023; Wiggins, 2016).

Modeling Scientific Reasoning

In the sciences, instructors are piloting assignments that blend AI-assisted analysis with human critique. For example, students might be given an AI-generated interpretation of experimental data and asked to assess its validity, identify methodological flaws, or propose alternative explanations. These tasks promote skills fundamental to scientific reasoning: skepticism, data literacy, and peer review. As Wieman (2017) and Holmes, Wieman, & Bonn (2015) have shown, such approaches encourage deeper engagement with the epistemological foundations of science—what counts as evidence, how claims are justified, and why precision matters.

Building AI Fluency Across the Curriculum

To meet the demands of a world increasingly shaped by automation, higher education must move beyond treating AI as an external threat and begin cultivating AI fluency as a foundational component of 21st-century learning. AI fluency goes beyond knowing how to use tools like ChatGPT or Midjourney—it encompasses the ability to understand how AI systems work, critically evaluate their outputs, use them ethically, and reflect on their broader social and disciplinary implications (Long & Magerko, 2020; Luckin et al., 2016).

Integrating AI fluency into the curriculum means designing assignments that treat AI not as a banned shortcut or unexamined assistant, but as a subject of inquiry. Students should be taught to interrogate the design of AI tools, including how they are trained, what kinds of data they rely on, and how they reflect or reinforce existing social biases. Courses across disciplines can include assignments that ask students to compare AI-generated outputs with human-created work, evaluate their quality and assumptions, or explore how different prompts lead to different results. These tasks cultivate what Holmes, Bialik, & Fadel (2019) describe as “cognitive partnership”—the ability to think with, through, and about technology, rather than simply accepting its outputs.

Building AI fluency involves normalizing reflective practice. Students should be encouraged to articulate how and why they used AI tools in the completion of an assignment: What choices did they make? What did the AI get right—or wrong? How did it shape their thinking? This kind of metacognitive work not only deepens learning, but also demystifies AI as a black box and empowers students to use it responsibly (Mollick & Mollick, 2023).

Crucially, AI fluency should not be siloed within STEM or computer science. Every field—from history to healthcare, literature to law—will be transformed by AI in some way, and students in every discipline deserve the opportunity to engage critically with those transformations. Developing AI fluency as a form of literacy positions students to become not just competent users of technology, but thoughtful citizens capable of shaping its role in society.

The task before educators is not merely to regulate AI use, but to reimagine what it means to be educated in an age of intelligent machines. By embedding AI fluency into course outcomes, assessment practices, and institutional values, higher education can help students navigate this new landscape with agency, insight, and integrity.

The text was generated in collaboration with Gemini (2.5 Flash), Google’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.

References

Ambrose, Susan A., Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, and Marie K. Norman. How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco: Jossey-Bass, 2010.

Bertram Gallant, Tricia. Academic Integrity in the Twenty-First Century: A Teaching and Learning Imperative. San Francisco: Jossey-Bass, 2008.

Farrell, Paul. “Integrating AI into Public Administration Education: Risks and Rewards.” Journal of Public Affairs Education 29, no. 1 (2023): 45–58.

Holmes, Wayne, Maya Bialik, and Charles Fadel. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign, 2019.

Holmes, N. G., Carl E. Wieman, and Doug A. Bonn. “Teaching Critical Thinking.” Proceedings of the National Academy of Sciences 112, no. 36 (2015): 11199–204.

Long, David, and Brian Magerko. “What Is AI Literacy? Competencies and Design Considerations.” In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. New York: ACM, 2020.

Luckin, Rose, Wayne Holmes, Mark Griffiths, and Laurie B. Forcier. Intelligence Unleashed: An Argument for AI in Education. London: Pearson, 2016.

Margolis, Eric. The Hidden Curriculum in Higher Education. New York: Routledge, 2001.

McArthur, Janine A., and Betty White. “Redesigning Creativity: AI, Agency, and Reflective Practice in the Visual Arts.” International Journal of Art & Design Education 40, no. 2 (2021): 437–51.

McCabe, Donald L., Linda Klebe Treviño, and Kenneth D. Butterfield. “Cheating in Academic Institutions: A Decade of Research.” Ethics & Behavior 11, no. 3 (2001): 219–32.

Mollick, Ethan, and Lilach Mollick. “Assigning AI: Seven Approaches for Students with Prompts.” Working paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4573321 (accessed July 8, 2025).

National Academies of Sciences, Engineering, and Medicine. How People Learn II: Learners, Contexts, and Cultures. Washington, D.C.: The National Academies Press, 2018.

Pascoe, Michaela C., Rosanna M. Hetrick, and Alexandra G. Parker. “The Impact of Stress on Students in Secondary School and Higher Education.” International Journal of Adolescence and Youth 25, no. 1 (2020): 104–12.

Popenici, Stefan C., and Sharon Kerr. “Exploring the Impact of Artificial Intelligence on Teaching and Learning in Higher Education.” Research and Practice in Technology Enhanced Learning 12, no. 1 (2017): 1–13.

Sullivan, Graeme. Art Practice as Research: Inquiry in the Visual Arts. Thousand Oaks, CA: SAGE Publications, 2010.

Wieman, Carl E. “The Similarities between Research in Education and Research in the Hard Sciences.” Educational Researcher 46, no. 6 (2017): 319–29.

Wiggins, Grant. “A True Test: Toward More Authentic and Equitable Assessment.” Educational Leadership 70, no. 6 (2016): 28–33.

Source link

September 5, 2025
Free speech and ‘the executive power’ with Advisory Opinions

What are the limits of presidential power? How many
days has it been since President Trump’s TikTok ban moratorium went
into place? What is the state of the conservative legal movement?
And where did former FIRE president David French
go on his first date?

French and Sarah Isgur
of the popular legal podcast “Advisory
Opinions” join the show to answer these questions and
discuss the few free speech issues where they disagree with
FIRE.

Timestamps:

00:00 Intro

02:18 Origin story of “Advisory Opinions”

08:15 Disagreements between FIRE and AO

15:04 Why FIRE doesn’t editorialize on the content of
speech

24:27 Limits of presidential power

43:30 Free speech, the dread of tyrants

51:01 The prosecution of political figures

58:01 Cracker Barrel

01:00:09 State of the conservative legal movement

Enjoy listening to the podcast? Donate to FIRE today and
get exclusive content like member webinars, special episodes, and
more. If you became a FIRE Member
through a donation to FIRE at thefire.org and would like access to
Substack’s paid subscriber podcast feed, please email [email protected].

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September 4, 2025
Black Women’s Leadership in Higher Education: The Remaking of Academic Power

I
Dr. Tina M. King n the storied halls of higher education, Black women who ascend to the presidency do so while carrying the weight of history, community, and the unspoken expectation that we will be both miracle workers and scapegoats. Black women in higher education leadership navigate a complex matrix of anti-Blackness and misogynoir —a reality where their expertise is simultaneously appropriated and undermined. Research reveals that more than most Black women executives in predominantly white institutions (PWIs) experience racelighting (racialized gaslighting), characterized by dehumanizing scrutiny. We endure identity taxation, where we are expected to carry the unsustainable burden of single-handedly solving institutional race problems, often where we are the target of the attack while comforting white fragility. Simultaneously, we experience racelighting where people of color receive racialized messages and question their thoughts and experiences. This racelighting is perpetuated by the institution’s willingness to tokenize Black women’s identities for diversity optics while suppressing our agenda for transformative anti-racist praxis. The narrative of Black women’s leadership in PWIs is not simply a tale of individual achievement but also reflects the deep, persistent anti-Blackness embedded in the academy’s very structure.

The attacks, swift and severe, are often cloaked in the familiar rhetoric of “governance, academic integrity, or collegial concern,” but the subtext is unmistakably racial. They are orchestrated not as a response to policy but as a rebuke of Black authority daring to reshape the institution’s priorities. In such attacks, we are called incompetent, corrupt, and unwilling to do the hard work (lazy), echoing tropes that have long been used to undermine Black people in general and Black women in leadership specifically. The most insidious move, however, is often the elevation of a single Black or Brown person to be the messenger or carrier of the attack, serving as a shield to deflect accusations of racism and to lend legitimacy to the movement or campaign t o disparage and discredit Black women’s leadership.Dr. Regina Stanback Stroud

This dynamic is not new. Dr. Patricia Hill Collins (2000), in her foundational work on Black Feminist Thought, describes how Black women in leadership are subjected to controlling images— stereotypes that are deployed to police the boundaries of acceptable Blackness. In the academy, these images manifest as relentless questioning of competence, insinuations of aggression, and the expectation that Black women will perform emotional labor to maintain white comfort. The token messenger, perhaps unwittingly, becomes complicit in this system, their proximity to whiteness granting her temporary power even as it reinforces the very structures that marginalize leaders of color—in other words, they become complicit in using the academic tools of white supremacy to join in the assault on Black women’s leadership.

What begins to emerge is a spectator sport where people at all levels of influence remain silent in the face of orchestrated attacks. Please make no mistake: silence does not represent neutrality; it represents complicity. By refusing to address the racialized nature of the attacks, the institution is signaling that Black women leaders are ultimately expendable, their contributions contingent upon their willingness to placate white interests and prioritize white comfort. This is the reality of what Breonna Collins (2022) calls “epistemic violence” –the systematic invalidation of Black knowledge and leadership under the guise of procedural fairness.

Yet Black women leaders have always found ways to resist and reimagine the academy. Drawing on the tradition of Black feminist resistance, we create counterspaces within hostile institutions, mentoring the next generation and insisting on the legitimacy of their vision. We redefine “institutional fit” not as assimilation into white norms but as the capacity to transform the institution in service of justice.

Despite these acts of resistance and reimagination, the very presence and leadership of Black women in academic spaces often disrupts entrenched power structures and exposes the discomfort many have with authentic Black excellence. A threat to many, Black excellence in leadership prioritizes the needs of marginalized students and communities over the preservation of the status quo.

While some may wish to uphold privilege and power for themselves, others may be well-intentioned but unable to recognize Black excellence. They may interpret Black leadership as arrogance or see Black Leaders simply as flaunting their positions or being opinionated. Still others may believe they are doing good but fail to recognize their own deep biases. Those who consider themselves allies may suffer fatigue along with Black leaders, but that mutual suffering does not, an ally make. It must be accompanied by one’s willingness to use their white privilege and capital to actively combat anti-Blackness and misogynoir at play.

Studies of HBCU leadership reveal how Black women executives subvert PWI pathologies through radical self-definition, where we reject white-normed leadership frameworks to implement culturally grounded approaches and ethical care (prioritizing community needs over respectability politics). We create counter-spaces that center Black epistemologies, such as mentorship programs that affirm Black women’s intellectual sovereignty. Black women leaders engage in institutional truth-telling where we document systemic racelighting through critical race methodology.

True transformation requires more than performative allyship. It demands redistribution of resources, independent accountability structures, and a commitment to centering Black epistemologies in institutional decision-making. There is a growing recognition that Black leadership is not incidental— it is essential to the future of higher education. The time has come for institutions to choose: will they cling to the master’s tools, or will they finally make room for the radical imagination and power of Black women’s leadership?

Until higher education is willing to confront its foundational anti-Blackness, it will continue to sacrifice its most visionary leaders on the altar of white comfort. The question is not whether another attack will come but who will have the courage to stand in solidarity and say, “Enough.” The future of academia depends on this shift. Ultimately, we must move beyond the white gaze and demand for our pain, and instead, embrace the Black radical imagination and the remaking of power in the academy.

Dr. Tina M. King is president of San Diego College of Continuing Education

Dr. Regina Stanback Stroud is the chief executive officer of RSSC Consulting

Dr. Jennifer Taylor Mendoza serves as the 13th president of West Valley College.

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August 22, 2025
Humanizing Higher Ed Data: The Strategic Power of Student Digital Twins
Higher education institutions are overflowing with data, yet many still struggle to turn that information into actionable insight. With systems siloed across admissions, academics, student support, and alumni relations, it’s hard to get a clear picture of the student journey — let alone use that data to enhance engagement or predict outcomes.

Enter the “digital twin”: a transformative framework that helps institutions centralize, contextualize, and humanize student data. More than a dashboard or data warehouse, a student digital twin creates a living, dynamic model that reflects how students interact with your institution in real time. It’s the difference between looking at data and understanding a student.

The data disconnect holding higher ed back

Disconnected data is one of the most persistent obstacles facing colleges and universities. Key information is often trapped in different systems — student information systems (SIS), learning management systems (LMS), customer relationship management (CRM) tools, financial aid platforms, and more.

This fragmentation makes it difficult to:
- Personalize student communications
- Identify at-risk students in time to intervene
- Support seamless transfers or cross-departmental collaboration
- Harness emerging technologies like generative AI
The result? Missed opportunities, inefficient outreach, and limited visibility into student experiences.

Demystifying the student digital twin

A digital twin is a virtual representation of a physical entity. In higher education, that entity is the student. The student digital twin brings together behavioral, academic, and operational data to create a comprehensive, contextual profile of each learner.

Unlike a static dashboard or data warehouse, a digital twin captures relationships, sequences, and interactions. It enables institutions to:
- Visualize student journeys across systems
- Model future scenarios
- Generate predictive insights
- Power real-time personalization
Most importantly, a digital twin humanizes data by shifting the focus from systems to students.

What makes it work: The Connected Core® architecture

At Collegis, the digital twin is powered by Connected Core — a composable, cloud-native platform built specifically for higher education. The architecture includes:
- Integrated data fabric: A higher ed-specific data layer that unifies SIS, LMS, CRM, and more.
- Packaged business capabilities: Modular features like lead scoring, advising nudges, and financial aid workflows.
- Composable platform: A low-code development environment that allows institutions to customize workflows and experiences.
Together, these elements create an agile foundation for digital transformation and continuous improvement.

Ready for a Smarter Way Forward?

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Use cases that drive institutional impact

Digital twins aren’t theoretical. They’re already delivering measurable value across the student lifecycle. With real implementations across enrollment, student success, and digital engagement, Collegis partners are proving just how powerful a connected data foundation can be.

These examples show how the digital twin moves from concept to impact:
- AI lead prioritization: By integrating digital journey signals with CRM intelligence, one partner increased inquiry-to-appointment conversion by 38%.
- Transfer credit evaluation: AI-driven transcript assessments delivered >85% accuracy in early evaluations, reducing friction for prospective students.
- AI-powered website search: Semantic search functionality improved engagement by 250% during pilot testing, enhancing conversion potential.
These outcomes demonstrate how digital twins don’t just aggregate data — they activate it.

Implementation, integration, and ROI

One common question we encounter about this concept is, “Can’t we do this with our own data warehouse?” The answer is not really.

Data warehouses are optimized for reporting, not real-time personalization. The digital twin’s networked model is designed for operational use, enabling advisors, marketers, and faculty to act in the moment.

Collegis typically helps institutions realize value within three to six months. Whether starting with a marketing use case or building a full student model, we work with partners to:
- Identify quick wins
- Integrate priority data sources
- Build a data model tailored to their institution
Why Collegis — and why now?

Unlike generic analytics platforms, Connected Core is purpose-built for higher education. It’s not a retrofitted enterprise tool. The following features make it unique from other offerings:
- AI-native and human-centered: It’s designed to deliver explainable, actionable insights.
- Composed, not constrained: It’s flexible enough to integrate with legacy systems and custom-built tools.
- A strategic partnership: Collegis provides not just the technology, but the advisory services and data talent to ensure sustained success.
Start humanizing your student data

The digital twin helps institutions shift from reactive reporting to proactive engagement. It empowers colleges and universities to not only understand their students better, but to serve them more effectively.

Ready to explore how a student digital twin could transform your data strategy? Contact us to request a demo!

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Higher ed is evolving — don’t get left behind. Explore how Collegis can help your institution thrive.
Bryan Chitwood is Director of Data Enablement at Collegis Education, where he helps lead data strategy, product development, and advisory services. With a Ph.D. in English and advanced certifications in data leadership and cloud architecture, he helps institutions harness data to drive results.

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August 21, 2025
Elite Power, Higher Education, and Political Ambition

[JB and Penny Pritzker]

The Pritzker family stands as a symbol of wealth, influence, and access in American public life. From the luxury of Hyatt Hotels to the boardrooms of private equity and the highest ranks of government, their reach extends across economic sectors and institutional spheres. But beneath the carefully managed public image lies a troubling contradiction—one that implicates higher education, for-profit exploitation, and national politics.

Penny Pritzger

Penny Pritzker, a former U.S. Secretary of Commerce and current trustee of Harvard University, has been a key figure in shaping education policy from elite perches. She also had a working relationship with Vistria Group, a private equity firm that now owns the University of Phoenix and Risepoint. These two entities have been central to the subprime college industry—profiting from the hopes of working-class students while delivering poor outcomes and burdensome debt.

Pritzker’s relationship with Vistria runs deeper than simple association. In the late 1990s, she partnered with Vistria co-founder Marty Nesbitt to launch The Parking Spot, a national airport parking venture that brought them both business success and public recognition. When Nesbitt founded Vistria in 2013, he brought with him the experience and elite networks formed during that earlier partnership. Penny Pritzker’s family foundation—Pritzker Traubert—was among the early funders of Vistria, helping to establish its brand as a more “socially conscious” private equity firm. Although she stepped away from any formal role when she joined the Obama administration, her involvement in Vistria’s formation and funding set the stage for the firm’s expansion into sectors like for-profit education and healthcare.

Vistria’s acquisition of the University of Phoenix, and later Risepoint, positioned it as a major player in the privatization of American higher education. The firm continues to profit from schools that promise economic mobility but often deliver student debt and limited job prospects. This is not just a critique of business practices, but a systemic indictment of how elite networks shape education policy, finance, and outcomes.

Penny’s role as a trustee on the Harvard Corporation only sharpens this contradiction. Harvard, a university that markets itself as a global champion of meritocracy and inclusion, remains silent about one of its trustees helping to finance and support a firm that monetizes educational inequality. The governing body has not publicly addressed any potential conflict of interest between her Harvard role and her involvement with Vistria.

JB Pritzger

These contradictions are not limited to Penny. Her brother, J.B. Pritzker, is currently the governor of Illinois and one of the wealthiest elected officials in the country. Though he has no documented personal financial stake in Vistria, his administration has significant ties to the firm. Jesse Ruiz, J.B. Pritzker’s Deputy Governor for Education during his first term, left state government in 2022 to take a top leadership position at Vistria as General Counsel and Chief Compliance Officer.

This revolving-door dynamic—where a senior education policymaker transitions directly from a progressive administration to a private equity firm profiting from for-profit colleges—underscores the ideological alignment and operational synergy between the Pritzker political machine and firms like Vistria. While the governor publicly champions equity and expanded public education access, his administration’s former top education official is now helping manage legal and compliance operations for a firm that extracts value from struggling students and public loan programs.

J.B. Pritzker has announced plans to run for a third term as governor in 2026, but many observers believe he is positioning himself for a 2028 presidential campaign. His high-profile public appearances, pointed critiques of Donald Trump, and increased visibility in early primary states all suggest a national campaign is being tested. With his vast personal wealth, Pritzker could self-fund a serious run while drawing on elite networks built over decades—networks that include both his sister’s role at Harvard and their shared business and political allies.

Elites in US Higher Education, A Familiar Theme

What emerges is a deeply American story—one in which the same elite networks shape both the problems and the proposed solutions. The Pritzkers are not alone in this dynamic, but their dual influence in higher education and politics makes them a case study in elite capture. They are architects and beneficiaries of a system in which public office, private equity, and nonprofit institutions converge to consolidate power.

The for-profit education sector continues to exploit regulatory gaps, marketing expensive credentials to desperate individuals while avoiding the scrutiny that traditional nonprofit colleges face. When private equity firms like Vistria acquire troubled institutions, they repackage them, restructure their branding, and keep extracting value from public loan dollars. The government lends, students borrow, and investors profit. The people left behind are those without political clout—low-income students, veterans, working parents—who believed the marketing and now face debt with little return.

Harvard’s silence, University of Phoenix’s reinvention, the rebranding of Academic Partnerships/Risepoint, and J.B. Pritzker’s ambitions all signal a troubling direction for American democracy. As more billionaires enter politics and public institutions become more dependent on private capital, the line between public service and private gain continues to erode.

The Higher Education Inquirer believes this moment demands not only scrutiny, but structural change. Until elite universities hold their trustees accountable, until political candidates reject the influence of exploitative industries, and until the public reclaims its voice in higher education policy, the Pritzker paradox will continue to define the American experience—where access to opportunity is sold to the highest bidder, and democracy is reshaped by those who can afford to buy it.

Sources

– U.S. Department of Education College Scorecard

– University of Phoenix outcome data (IPEDS, 2024)

– Harvard University governance and trustee records

– Vistria Group investor reports and public filings

– Wall Street Journal, “America’s Second-Richest Elected Official Is Acting Like He Wants to Be President” (2025)

– Associated Press, “Governor J.B. Pritzker positions himself as national Democratic leader” (2025)

– Vistria.com, “Marty Nesbitt on his friendship with Obama and what he learned from the Pritzkers”

– Politico, “Former Obama Insiders Seek Administration’s Blessing of For-Profit College Takeover” (2016)

– Vistria Group announcement, “Jesse Ruiz Joins Vistria as General Counsel and CCO” (2022)

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July 25, 2025
New Research Highlights the Power of Access Work — and the Tools We Need to Evaluate It
- This blog was kindly authored by Dr Anna Anthony, director of HEAT. HEAT provides a collaborative data service enabling higher education providers, Uni Connect partnerships and Third Sector Organisations to show the impact of their equality of opportunity delivery through a shared, standardised data system. By aggregating data from across the membership, HEAT can publish national-level impact reports for the sector.
It has never been more important for providers across the sector to show that access and participation activities have an impact. With resources stretched, we need to know the work we are doing is making a measurable difference. New research from HEAT reveals a series of powerful findings:
1. Intensive outreach boosts HE entry by up to 29% – Students who received at least 11 hours of intensive outreach were up to 29% more likely to enter higher education (HE) than matched peers receiving minimal support.
1. Disadvantaged students see the biggest gains – Free school meal (FSM) eligible students were up to 48% more likely to progress to HE when engaged in intensive outreach.
1. Uni Connect makes a difference – The largest relative increases in HE entry were observed in FSM-eligible students who participated in Uni Connect-funded activities, further demonstrating the importance of impartial outreach delivered collaboratively.
1. Access to selective universities improves – Intensive outreach from high-tariff providers increased the chance of progressing to a high-tariff university by 19%.
1. Sustained support across Key Stages is vital – Outreach delivered across both Key Stages 4 and 5 had the greatest impact, highlighting the need for long-term, multi-stage interventions throughout secondary education.
These findings provide compelling evidence that the work being done across the sector to widen participation is not only reaching the right students but changing trajectories at scale. Crucially, this latest research includes previously unavailable controls for student-level prior attainment — adding new rigour to our understanding of outreach impact. You can read the full report on our website.

What’s next for national-level research?

Our ability to generate this kind of national evidence is set to improve even further thanks a successful bid to the Office for Students (OfS) Innovation Fund. Through a collaboration with academics at the Centre for Education Policy and Equalising Opportunities (CEPEO) at the UCL Institute of Education, HEAT will lead on the development and piloting of a pioneering new Outreach Metric, measuring providers’ broader contribution to reducing socio-economic gaps in HE participation. More details about this project can be found here, and we look forward to sharing early findings with the sector in 2026.

Local-level evaluation is just as important

While national analyses like these are essential to understanding the big picture, the OfS rightly continues to require providers to evaluate their own delivery. Local evaluations are critical for testing specific interventions, understanding how programmes work in different contexts, and learning how to adapt practice to improve outcomes. Yet robust evaluation is often resource-intensive and can be out of reach for smaller teams.

This is where use of a sector-wide system for evaluation helps – shared systems like HEAT provide the infrastructure to track student engagement and outcomes at a fraction of the cost of building bespoke systems. Thanks to a decade of collaboration, we now have a system which the sector designed and built together, and which provides the tools necessary to deliver the evaluation that the OfS require providers to publish as part of their Access and Participation Plans (APP).

We’re also continuing to improve our infrastructure. Thanks to a second successful bid to the OfS Innovation Fund we are building system functionality to support providers to use their tracking data when evaluating their APP interventions. This includes an ‘automated comparator group tool’ that will streamline the process of identifying matched participant and non-participant groups based on confounding variables. By reducing the need for manual data work, the tool will make it easier to apply quasi-experimental designs and generate more robust evidence of impact.

Next steps – sharing through publication

With all these tools at their disposal, the next step is to support the sector to publish their evaluation. We need shared learning to avoid duplication and siloed working. HEAT is currently collaborating with TASO to deliver the Higher Education Evaluation Library (HEEL), which will collect, and share, intervention-level evaluation reports in one accessible place for the first time. By collating this evidence, the HEEL will help practitioners and policymakers alike to see what works, what doesn’t, and where we can improve together.

If we want to continue delivering meaningful progress on access and participation, we need both meaningful, critical local evaluation and powerful national insights. Centralised data tracking infrastructure can give the sector the tools it needs to do both.
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July 25, 2025
The Brand Power of Licensing
For many colleges and universities, licensed merchandise has long been a quiet but steady source of revenue and brand visibility. From sweatshirts and baseball caps to water bottles and notebooks, these products not only generate income but also serve as walking billboards that boost school spirit and brand recognition far beyond campus.

But lately, there’s been a shift. Higher ed marketers should be paying close attention to what’s happening in the licensing space, because the early warning signs of disruption are already here.

Tariffs and Canceled Orders: A Brewing Storm

Recent increases and uncertainty regarding tariffs on imported goods are driving up pricing for licensees to manufacture and import collegiate merchandise. With rising material, shipping and import costs, many licensees are reassessing their strategies. Some are choosing to cancel or reduce purchase orders, pulling back on riskier bets or deprioritizing smaller-volume schools in favor of top-tier brands with national visibility. Some are choosing to completely rebuild their supply chains, which involves changing product offerings, factory partners and source nations. Smaller-volume schools necessarily will be cut from some offerings as supply chains are rebuilt.

For institutions outside the Power Four athletic conferences, that means your branded products may no longer be showing up on some store shelves for a while or may be offered in significantly reduced volume. Even for larger schools, the financial strain on licensees and the changes they need to make could lead to diminished SKU/style offerings, fewer special collections, slower product refreshes and reorders, and less innovation.

The Impact on Brand Visibility and Affinity

This isn’t just a revenue issue; it’s a brand issue. Licensed merchandise is one of the few marketing channels that turn fans, alumni and students into ambassadors. Today’s prospective students are tomorrow’s student body and future alumni and lifetime fans. When a fan or parent wears your school’s hoodie to the grocery store or a high school senior sees your logo in a retail window, that visibility reinforces your institution’s cultural presence.

If fewer products are being made or if those products aren’t showing up in physical and digital storefronts, your brand presence shrinks. That affects more than just sales; it influences how connected your audience feels to your institution and has downstream negative impacts on enrollment, community involvement, donations and athletic support. These supply chain and licensee challenges are coming on the heels of significant COVID-related upheavals and before an anticipated nationwide enrollment cliff related to shrinking high school population.

Why Marketing Leaders Should Get Involved

Traditionally, licensing may live under auxiliary services or a separate business office. But as marketing leaders, we should be partnering more closely with licensing teams to ensure we have a full picture of how our brand is performing in the marketplace.

Here are three steps marketing leaders can take now to mitigate the impact of this changing landscape.
1. Re-Engage With Your Licensing Team
Ask for a performance snapshot: How have royalties trended? Are specific categories, like youth apparel, tailgating gear or alumni merchandise, down or up more than others? What are your top-selling or worst-performing licensees and SKUs? Are there any retail partners you could work with to broaden their selection of licensed products?
1. Evaluate Your Licensee Mix and Sourcing Strategy
Encourage conversations about domestic sourcing options and alternative manufacturers with domestic production. If one of your primary partners is pulling back due to tariffs, there may be smaller or niche partners who are better equipped to weather the storm and innovate in response.
1. Activate Your Community Through Storytelling
If retail sales are contracting, consider how your marketing team can help drive traffic to official online stores or promote domestic-sourced direct-to-consumer efforts. Strategic storytelling such as featuring alumni-owned or local licensees or highlighting sustainable merchandise can align with institutional values while boosting sales.

A Moment for Brand Resilience

In higher ed, we often talk about resilience in terms of enrollment, endowment or curriculum. But brand resilience matters, too, and licensing is a key part of that equation. As market conditions tighten, schools that stay actively involved in their licensing strategy will have an advantage—not just financially, but reputationally.

Now is the time to treat your licensing portfolio not as a passive revenue stream but as an extension of your brand strategy. The marketers who do will be best positioned to navigate the challenges ahead and emerge stronger.

Jenny Petty is vice president, marketing communications, experience and engagement, and chief marketing and communications officer, and Denise “Goat” Lamb is chief licensing officer at the University of Montana.
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July 15, 2025
It’s the little moments that power social mobility

Anyone who has gone into higher education from a “non-traditional” background knows that widening participation is a double-edged sword. It is there to promote social mobility – but for individual students this journey, once taken, tends to be irreversible.

In return for out-earning your family of origin, you are likely to endure a long period of feeling like an outsider. Whether it’s your accent, the words you use, the house you lived in, what you eat, the school you went to, or where (and indeed, if) you go on holiday, there are thousands of ways that you can feel different – and lesser. For some students, this feeling of being an imposter is further compounded by differences in culture, religion and ethnicity. As time goes on you can either continue standing out like a sore thumb or you can start to assimilate and, in doing so, lose little pieces of yourself forever.

This is the story I heard many times over while carrying out research for a report published today. A Different World explores socioeconomic disadvantage in the transition to university and first year experience. In a partnership between Unite Students, University of Leeds and Manchester Metropolitan University, students took part in interviews, focus groups and co-creation, with most of them contributing directly to the report’s 33 recommendations.

If this many recommendations seems excessive (even though they are helpfully grouped into six themes) it’s because most of them are about small but meaningful actions. I’ve spent the best part of 25 years advocating for a more inclusive higher education sector, but it’s only since working in student accommodation that I’ve come to see the value of these day-to-day moments as a force for change.

University visits for schools are good, tutoring projects even better, and the return of grants would be lovely – but wherever the student experience is built on middle-class norms we will continue to see lower enrolment, continuation, completion, attainment and graduate outcomes among students from a different background.

The change that is needed – and attainable – involves small, local actions in addition to system-level change.

In their own words

A Different World enables students to tell their own stories in their own words, which brings a richness of nuance to the topic and reveals opportunities for change.

For example, there are many ways to cope with alienation, but opportunities to meet others from similar backgrounds really helps. As well as other students, this could also include staff members, and not just academic staff. Student accommodation maintenance teams made a difference for one student, and outside of this research I’ve heard many stories of students whose experience has been transformed by housekeepers or the reception team. Do we recognise and encourage this enough? Students were also reassured by services specifically aimed at them. We British don’t like to talk about social class, but maybe it would be helpful if we did.

Students also shared the challenges of working and balancing a budget, and financial matters certainly did limit opportunities for socialising and extra-curriculars. However, they talked at least as much about their budgeting skills and ability to find the best bargains, skills usually learned from family. They were so impressive in this respect that they would have been helpful peer coaches for students in financial difficulty.

A less obvious impact of socioeconomic background is gaps in fundamental knowledge about higher education. If you are the first person in your family to go to university, and especially if your school or college isn’t geared up to preparing you for it, there will be a lot you don’t know, including “unknown unknowns”, which put you at a disadvantage. For some students, unspoken assumptions tripped them up several times in the first year leading to missed opportunities and academic disadvantage.

A different world

The good news is that there’s a lot that can be done that would benefit students from disadvantaged backgrounds, and much of it would benefit a wider range of students too. You are probably doing some of these already, or in pockets within the organisation.

All academics, and especially personal tutors, could explain expectations, terms and how to interact with them. For example, what are “office hours”, how do students get a meeting with you, and what are they allowed to talk about in those meetings? Module leaders could include ice-breakers at the start of every module, which also helps to promote belonging. Campus services staff could be encouraged and trained to develop more meaningful relationships with students, within appropriate boundaries. You could employ more students, especially those on a low income, and encourage your partners and suppliers to do the same. You could work with student-led societies to develop more inclusive practices and clearer communication. Maybe offer targeted bursaries for extra-curricular activities, via a clear and efficient process. For further inspiration I’d recommend reading the case studies from Manchester Metropolitan University and the University of Leeds that are included in the report.

Widening access has been a success story over the last three decades – but if we’re serious about delivering social mobility as a sector, and as a society, individual students will benefit from better awareness and support while they are undertaking that difficult journey.

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June 10, 2025
Canceling AmeriCorps grants threatens the future of education and workforce pipelines that power our nation’s progress

The recent decision to cancel $400 million in AmeriCorps grants is nothing short of a crisis. With over 1,000 programs affected and 32,000 AmeriCorps and Senior Corps members pulled from their posts, this move will leave communities across the country without critical services.

The cuts will dismantle disaster recovery efforts, disrupt educational support for vulnerable students and undermine a powerful workforce development strategy that provides AmeriCorps members with in-demand skills across sectors including education.

AmeriCorps provides a service-to-workforce pipeline that gives young Americans and returning veterans hands-on training in high-demand industries, such as education, public safety, disaster response and health care. Its nominal front-end investment in human capital fosters economic mobility, enabling those who engage in a national service experience to successfully transition to gainful employment.

As leaders of Teach For America and City Year, two organizations that are part of the AmeriCorps national service network and whose members receive education stipends that go toward certification costs, student loans or future education pursuits, we are alarmed by how this crisis threatens the future of the education and workforce pipelines that power our nation’s progress, and it is deeply personal. We both started our careers as corps members in the programs we now lead.

Related: A lot goes on in classrooms from kindergarten to high school. Keep up with our free weekly newsletter on K-12 education.

Aneesh began his journey as a Teach For America corps member teaching high school English in Minnesota. Jim’s path began with City Year, serving at a Head Start program in Boston. We know firsthand that AmeriCorps programs are transformative and empower young people to drive meaningful change — for themselves and their communities.

At Teach For America, AmeriCorps grants are essential to recruiting thousands of new teachers every year to effectively lead high-need classrooms across the country. These teachers, who have a consistent and significant positive impact on students’ learning, rely on the AmeriCorps education awards they earn through their two years of service to pay for their own education and professional development, including new teacher certification fees, costs that in some communities exceed $20,000.

Termination of these grants threatens the pipeline of an estimated 2,500 new teachers preparing to enter classrooms over the summer. At a time when rural and urban communities alike are facing critical teacher shortages, cutting AmeriCorps support risks leaving students without the educators they need and deserve.

City Year, similarly, relies on AmeriCorps to recruit more than 2,200 young adults annually to serve as student success coaches in K-12 schools across 21 states, 29 cities and 60 school districts.

These AmeriCorps members serving as City Year student success coaches provide tutoring and mentoring that support students’ academic progress and interpersonal skill development and growth; they partner closely with teachers to boost student achievement, improve attendance and help keep kids on track to graduate. Research shows that schools partnering with City Year are two times more likely to improve their scores on English assessments, and two to three times more likely to improve their scores on math assessments.

Corps members gain critical workforce skills such as leadership, problem-solving and creative thinking, which align directly with the top skills employers seek; the value of their experience has been reaffirmed through third-party research conducted with our alumni. The City Year experience prepares corps members for success in varied careers, with many going into education.

AmeriCorps-funded programs like Breakthrough Collaborative and Jumpstart further strengthen this national service-to-workforce pathway, expanding the number of trained tutors and teacher trainees while also preparing corps members for careers that make a difference in all of our lives.

Those programs’ trained educators ensure all students gain access to excellent educational opportunities that put them on the path to learn, lead and thrive in communities across the country. And the leaders of both organizations, like us, are AmeriCorps alumni, proof of the lasting effect of national service.

Collectively, our four organizations have hundreds of thousands of alumni whose work as AmeriCorps members has impacted millions of children while shaping their own lives’ work, just as it did ours. Our alumni continue to lead classrooms, schools, districts, communities and organizations in neighborhoods across the country.

Related: Tracking Trump: His actions to dismantle the Education Department, and more

The termination of AmeriCorps grants is a direct blow to educators, schools and students. And, at a time when Gen Z is seeking work that aligns with their values and desire for impact, AmeriCorps is an essential on-ramp to public service and civic leadership that benefits not just individuals but entire communities and our country at large.

For every dollar invested in AmeriCorps, $17 in economic value is generated, proving that national service is not only efficient but also a powerhouse for economic growth. Rather than draining resources, AmeriCorps drives real, measurable results that benefit individual communities and the national economy.

Moreover, two-thirds of AmeriCorps funding is distributed by governor-appointed state service commissions to community- and faith-based organizations that leverage that funding to meet local needs. By working directly with state and local partners, AmeriCorps provides a more effective solution than top-down government intervention.

On behalf of the more than 6,500 current AmeriCorps members serving with Teach For America and City Year, and the tens of thousands of alumni who have gone on to become educators, civic leaders and changemakers, we call on Congress to protect AmeriCorps and vital national service opportunities.

Investing in AmeriCorps is an investment in America’s future, empowering communities, strengthening families and revitalizing economies. Let’s preserve the fabric of our national service infrastructure and ensure that the next generation of leaders, educators and community advocates who want to serve our nation have the ability to do so.

Aneesh Sohoni is Teach For America’s new CEO. Previously, he was CEO of One Million Degrees and executive director of Teach For America Greater Chicago-Northwest Indiana. He is a proud alum of Teach For America.

Jim Balfanz, a recognized leader and innovator in the field of education and national service, is CEO and a proud alum of City Year.

Contact the opinion editor at [email protected].

This story about AmeriCorps, Teach For America and City Year was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Sign up for Hechinger’s weekly newsletter.

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May 16, 2025