Dustin Hosseini 21/02/2026 Dustin Hosseini 21/02/2026

Listening, Speaking, Learning: On Verbal Feedback and (Re)Humanizing Assessment

Sunset over Queens Park pond, Glasgow, UK

Recently, I listened to a podcast from 2022, Educatalks: Reflective Practice featuring Professor Melaine Coward, a professor of medical education reflect on her career and her commitment to reflective practice. Medical Educatalks is a podcast created by the Developing Medical Educators Group (DMEG) at the Academy of Medical Educators. Toward the end of the conversation, she described her decision to give students verbal feedback on their assessments. The interviewer sounded genuinely surprised, he hadn’t encountered that approach before.

I paused.

Not because it felt novel, but because it felt familiar.

In 2015, while teaching at a University of London institution, I experimented with providing verbal feedback on written assignments. At the time, our digital marking platform enabled tutors to attach audio recordings directly to students’ scripts, so feedback could be posted alongside the written work itself. Students could either listen asynchronously or book a short follow-up slot to discuss it further. I would have their script in front of me as I recorded or spoke with them, talking through strengths, misunderstandings, and next steps. It was dialogic, immediate, and relational, but it was not universally welcomed.

The pushback was swift and couched in procedural language:

How could this be standardized?
How could it be moderated?
Where was the audit trail?

Ironically, the digital system did generate an artefact. The audio file was stored alongside the script. There was a record. And yet the discomfort persisted. What seemed to trouble colleagues was not the absence of documentation, but the presence of voice, with its tone, inflection, and spontaneity. Feedback had become less easily reduced to a static text block. The underlying concern was not simply technical. It was cultural. Feedback, in this framing, was not primarily a pedagogical encounter, it was a compliance mechanism.

Listening to Coward years later, I realized something I could not fully articulate back then: verbal feedback is not merely a technique. It is an epistemological stance. It is a small but meaningful act of (re)humanising assessment.

“But what I found was, so they weren’t reading the comments that I’d spent ages putting on marking there, because I do spend time, it matters that I give good feedback. When I did recorded feedback, I found I had a lot more follow-up from students, because they had had to listen to my feedback, and it was a very clear message of, I really enjoyed this, something for you to think about. I would be quite structured in how I recorded it, so I had notes, so it was formulaic in that sense, but not rehearsed.”

— Professor Melaine Coward

Feedback as encounter, not transmission

Higher education assessment cultures are deeply shaped by what Paulo Freire famously critiqued as the “banking model” of education in Pedagogy of the Oppressed. In that model, knowledge is deposited; feedback becomes a written correction of deficits; learning is framed as remediation.

Written feedback, of course, can be thoughtful and transformative. But it often operates within systems that prioritize defensibility over dialogue. Comments are calibrated for external examiners. Language becomes cautious. Tone becomes formal and neutralized. The student becomes a case.

Audio feedback, even when delivered asynchronously through a digital platform, subtly shifts that dynamic. Students hear emphasis. They hear encouragement. They hear uncertainty where appropriate. Meaning is shaped not only by what is said, but how it is said.

And when audio is paired with optional follow-up conversation, feedback becomes dialogic in a deeper sense. Students can respond, query, reinterpret.

This resonates with Freire’s insistence on dialogue as the foundation of emancipatory education. It also aligns with bell hooks’ vision of engaged pedagogy in Teaching to Transgress, where teaching and learning are relational acts rather than one-way transmissions.

When we speak with students rather than at them, feedback becomes less about surveillance and more about growth. Voice, literal voice, reintroduces presence into assessment by (re)humanizing it.

The standardization question

The resistance I encountered in 2015 revolved around standardisation. Written comments were seen as stable, recordable, and therefore fair. Audio feedback, even though stored and retrievable, was viewed as potentially variable.

But here is the uncomfortable truth: standardization is not synonymous with justice.

Critical and decolonial scholars have long questioned whose norms assessment criteria encode. Ngũgĩ wa Thiong'o, in Decolonising the Mind, reminds us that language and evaluation are never neutral; they are embedded within colonial power structures. Similarly, scholars of antiracist pedagogy argue that assessment practices often privilege dominant linguistic and epistemic norms and performances.

Audio feedback can surface some of this hidden curriculum. It allows educators to unpack what we mean by “criticality” or “coherence” in accessible, responsive ways. It can soften deficit framings by conveying nuance and care. It can make tacit expectations explicit.

For neurodivergent students, multilingual students, or those unfamiliar with disciplinary conventions, hearing feedback, with tone and pacing, can support comprehension in ways that dense written comments may not.

Uniform delivery formats may be easier to audit. But equity sometimes requires responsiveness.

Reflective practice and professional identity

Coward’s framing of verbal feedback emerged from reflective practice, a concept often associated with Donald Schön and his work The Reflective Practitioner. Reflection is not merely about improving technique; it is about interrogating the assumptions that underpin our actions.

Looking back, I can see that my 2015 experience exposed a tension between two logics and a clash of paradigms:

Assessment as pedagogical relationship / Was feedback a compliance mechanism or a pedagogical relationship?
Assessment as quality assurance infrastructure / Was my role to produce defensible documentation or to cultivate understanding?

The digital tool itself was neutral. It could host text or voice. The debate was about what counted as legitimate academic labor and legitimate evidence of fairness.

Reflective practice asks us to interrogate not only how we teach, but why certain practices are normalized while others are treated as suspect.

(Re)humanizing assessment in digital spaces

In my current work, including conversations around decolonizing curricula and rethinking assessment, I often return to a simple question:

What would assessment look like if we centered humanity rather than auditability?

This is not an argument to abandon rigor or documentation. Rather, it is a call to re-balance priorities.

(Re)humanizing assessment might include:

Dialogic feedback conversations alongside written summaries
Audio or video feedback that conveys tone and relational presence
Opportunities for students to respond to feedback
Co-constructed criteria discussions
Assessment designs that value multiple ways of knowing

These moves resonate with broader critical pedagogical commitments: resisting neoliberal metrics, challenging deficit framings, and recognizing students as co-participants in knowledge production. These moves further resonate with critical pedagogy’s insistence on dialogue, with antiracist commitments to challenging hidden norms, and with decolonial calls to unsettle inherited hierarchies of knowledge.

They also align with emerging scholarship on compassionate pedagogy and relational assessment cultures within higher education.

“Hearing someone talk about what you’ve done, the tone and voice to highlight praise, concern, and you can add in a more questioning tone ... They loved it. They loved it because they could hear from my touch. ”

— Professor Melaine Coward

An epiphany, years later: are our systems human enough?

Listening to Coward describe her practice, I felt both affirmed and reflective. The surprise expressed by the podcast interviewer revealed how deeply entrenched written, standardized feedback remains. Yet the fact that such practices continue to surface across disciplines, from medical education to the humanities, suggests a quiet shift. I also felt less concerned with whether verbal feedback is innovative and more interested in what it reveals. What I once framed defensively as “innovative feedback” now feels more clearly like a small act of resistance against depersonalized academic systems.

Even when captured and archived in a digital platform, voice unsettles the fantasy that assessment can be entirely standardised and neutral. It reintroduces tone, care, and relational accountability.

Perhaps the question is not whether audio feedback can be moderated.

Perhaps the more urgent question is whether our assessment cultures allow space for humanity, for dialogue, for nuance, for recognition.

If critical, antiracist, and decolonial pedagogies ask us to re-centre people rather than processes, then even something as simple as attaching a recorded voice note to a script can become a quietly radical act.

Exploring ideas for decolonizing the curriculum using generative AI tools

In this post, I share some examples created by generative AI for decolonizing the curriculum. I also contextualize the examples by providing commentary from colleagues from the University of Glasgow Decolonising the Curriculum Community of Practice.

“The master’s tools will never dismantle the master’s house.”

— Audre Lorde

Decolonizing education is part of many university strategies, including the university where I work. So, it seemed natural to think of how generative AI tools might help university students and staff think of ideas for decolonizing the curriculum. However, we must remember that the underlying logic of generative AI represents tools created by those in nations that hold power over others. Generative AI tools are often created in former imperial nations that seek out and obtain cheaper labor in other parts of the world to train and ‘develop’ the tools further. Generative AI also imparts a significant environmental impact, which must be considered.

AI and ethical considerations: coloniality of…

There are several caveats to using AI and generative AI generally, which I briefly outline in Karen Hao’s article from July 2020:

ghost work
- this is invisible labor provided by underpaid workers who are often in former US and UK colonies (among others)
beta testing
- sometimes beta testing is used on more vulnerable groups; yes, this is unethical, but it does still happen
AI governance
- think about who creates governance for AI; high-wealth nations and the Global North largely drive this at the expense of Global South nations
international social development
- if we consider ‘AI for…’ initiatives, we have to consider who drives these and who the targets or recipients are
algorithmic discrimination and oppression
- if we consider who creates algorithms, then we can begin to understand why some algorithms can portray racist, gendered, xenophobic imagery

Generative AI’s suggestions for decolonizing

For the following outputs, as shown in the GIF images below, I used the initial prompt:

I'm a lecturer and there is talk of decolonising the curriculum. I teach mathematics and statistics. What can I do to start decolonising my curriculum?

As we can see in the GIFs below, each generative AI tool appears to give some considered suggestions for how a lecturer in this particular area might go about decolonizing the curriculum they teach. Ideas such as incorporating more diverse views, Indigenous knowledges and contextualizing what is being learned are all general suggestions that I might expect to find in such a curriculum that is undertaking decolonizing.

However, I wanted to see more detail and so I followed up with another prompt.

The follow-up prompt was designed to see what else generative AI might suggest. Interestingly, with insight from colleagues, plenty could be done and suggested to create a curriculum that undertakes decolonization within a specific context.

In this case, the lists seemed familiar and similar in some respects and then a bit different in other respects in ways that I couldn’t immediately pick up on. The suggested names stem from ancient to modern times, albeit with a jump between ancient and modern times! Some familiar names are there, but are there perhaps some that could be included?

Here is the prompt I used:

What are some prominent but overlooked non-Western scholars of mathematics and statistics?

Reflections from colleagues

I consulted some colleagues, given the topic, the example is from an area I’m not familiar with. Specifically, I consulted colleagues in the UofG Decolonising the Curriculum Community of Practice who kindly provided their thoughts.

Soryia Siddique, whose background is in chemistry/pharmaceuticals/politics, provided the following:

My initial observation is that we ensure women of colour are represented in the materials. Perhaps a specific search around this.
BAME and Muslim women are underrepresented in many professions, including senior roles in Scotland, and are likely to experience systemic bias. Taking into consideration that Muslim women can experience racisim, sexism, and Islamaphobia. It is questionable whether media/society represents Muslim and BAME women's current and historical achievements.
They are also "missing” from Scotland’s media landscape.
In utilising AI, are we relying on data that is embedded in algorithmic bias and potentially perpetuating further inequality?

Soryia also suggested the following reading: The Movement to Decolonize AI: Centering Dignity Over Dependency from Standford University’s Human-Centered Artificial Intelligence. It’s an interview with Sabelo Mhlambi who describes the role of AI in colonization and how activists can counter this.

Samuel Skipsey, whose background is in physics and astronomy, also shared his thoughts:

The "list of important non-Westerners" is fairly comparable between the two - Bard is more biased towards historical examples and is pretty India-centric (with no Chinese or Japanese examples, notably), ChatGPT does a lot better at covering a wider baseline of "top hits" across the world (although given that "Nine Chapters on the Mathematical Art" doesn't have known authors - the tradition of the time it was written means that it probably had many contributions whose authorship is lost to history - I would quibble about it being a "scholar"). I note that this is still a Northern-Hemisphere centric list from both - although that's somewhat expected due to the problems citing material from pre-colonial Latin America, say. Still, it would have been nice to see some citation of contributions from Egypt, say.
In general, both lists are subsets of the list I would have produced by doing some Wikipedia diving.
The "advice on decolonising" is very high-level and tick-boxy from both. It feels like they're sourced from a web search (and, indeed, on an experimental search on DDG [DuckDuckGo] for "how can I decolonise my course" the first few hits all have a set of bullet points similar to those produced by the LLMs, which is unsurprising). To be fair to the LLMs, this is also basically what a lot of "how do I start decolonising" materials look like when produced by humans, so...
As Soryia notes, because the answers are quite generic there's a bunch of specific considerations that they don't touch on (they're not very intersectional - Hypatia turns up on both lists of non-Western scholars, doing a lot of heavy lifting as the only female name on either!)