Dr Lynette Pretorius

Sandeep Khattri

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Sandeep Khattri is a PhD candidate in the School of Learning and Teaching at Monash University. His research interests lie in the fields of student wellbeing and experiences, international education, doctoral education, and student success.

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Most doctoral students begin their PhD expecting to learn how to conduct research. They read the literature, design a study, collect and analyse data, and aim to contribute new knowledge to their field. On paper, the path to becoming a scholar appears relatively clear: map the literature, master the methods, produce rigorous research, publish your work, and complete the milestones. Yet, the lived experience of doctoral study often tells a more complicated story.

As doctoral students progress through their programmes, many encounter questions that are rarely addressed directly. How do scholars build credibility within their field? What kinds of research are recognised as valuable? Why do some opportunities appear to open more easily for certain researchers than for others? Gradually, students realise that succeeding in academia involves far more than developing research expertise and producing publications.

Alongside learning how to conduct research, doctoral students must also learn how the academic world operates. Over time, they begin to understand how credibility and legitimacy are established, how recognition circulates within academic communities, and how scholars position themselves within disciplinary fields. These norms and expectations are rarely written down in a PhD handbook or formally taught in doctoral training. Becoming a scholar, therefore, involves not only developing research skills but also learning to navigate the often-unspoken rules that shape academic careers and opportunities.

Scholars have described these unwritten expectations as part of the hidden curriculum. The term refers to the informal, unwritten, and unofficial knowledge students acquire beyond the official curriculum of their doctoral programmes. While formal curricula focus on disciplinary knowledge and technical competencies, the hidden curriculum encompasses the norms, behaviours, and values that students absorb through everyday academic interactions. Through these experiences, doctoral students gradually come to understand how scholarly work is evaluated, how recognition is distributed, and what forms of conduct are rewarded within academic life.

In our recent study, we explored these less visible dimensions of doctoral education. Specifically, we examine what these norms are, how they shape doctoral students’ experiences, and the actors who reproduce them. By examining these dynamics, we seek to illuminate how doctoral students gradually come to interpret what it means to be recognised as a “good scholar” within academia and how these interpretations shape academic identities and paths.

Read the paper

What do doctoral students learn beyond formal training?

We identified eight norms of doctoral education, shown in the picture below, along with their indicators and their impact on students’ experiences.

Norms of doctoral education and their indicators and impact on the student experience. Reproduced from our preprint paper (CC-BY license).

Publishing was one of the most visible markers of credibility and recognition in academic life. As doctoral students become immersed in the research environment, they learn how academic publishing works: drafting manuscripts, submitting them to journals, and navigating the often-demanding process of peer review. Through these experiences, many begin to recognise that publications signal scholarly competence to supervisors, peers, and wider disciplinary communities. Over time, publication records also come to be understood as important indicators of how scholars are evaluated and positioned within their disciplines, shaping decisions about hiring, promotion, funding, and collaboration. For doctoral students in the early stages of their candidature, this realisation often begins to influence how they approach their research and how they imagine their future academic trajectories.

At the same time, students learn that academic disciplines are organised around particular intellectual traditions that shape what counts as legitimate knowledge. Through reading the literature, receiving feedback from supervisors, and engaging in scholarly discussions, they become aware that certain theories, methods, and research approaches carry greater authority within their fields. While doctoral education often emphasises originality and innovation, participants reflected that early-career researchers must also learn how to position their ideas within established disciplinary conversations. Producing credible scholarship, therefore, involves not only generating new knowledge but also aligning one’s work with the intellectual traditions that define what is recognised as legitimate within a discipline.

Academic work is further shaped by powerful cultural expectations about dedication and perseverance. Many participants described how long working hours, constant busyness, and the ability to manage demanding workloads are often interpreted as signs of commitment to research. Through everyday experiences, interactions with supervisors, observations of colleagues, and responses to institutional expectations, students gradually come to understand that endurance is often taken as evidence of dedication to academic life. At the same time, setting clear boundaries around time or workload can sometimes be interpreted as a lack of commitment to academic work. This has significant implications for students’ wellbeing. Importantly, though, wellbeing is often framed as something students are responsible for in academia. Resilience is valued while help-seeking attracts stigma. Over time, these expectations can begin to feel like a normal part of the doctoral journey, even though they are rarely articulated explicitly.

Navigating institutional systems becomes another important lesson of doctoral life. Administrative procedures, funding arrangements, reporting deadlines, and programme milestones shape how doctoral work is organised. Learning to manage these processes often requires acquiring informal knowledge of how universities operate, knowledge that is rarely explained directly but becomes increasingly important as students progress through their programmes. What initially appears confusing gradually becomes part of the everyday reality of academic work. These institutional structures are also shaped by broader priorities within contemporary higher education, with a focus on efficiency. Expectations around research outputs, performance indicators, and institutional rankings increasingly influence how academic work is evaluated and organised. Within this environment, access to resources and opportunities can sometimes be uneven. Students studying part-time, working externally, or navigating complex funding arrangements may find it harder to participate fully in conferences, research collaborations, or academic networks. Through these experiences, many doctoral students begin to recognise how institutional structures can shape whose work becomes visible and whose opportunities remain limited.

Opportunities in academia also begin to reveal themselves through relationships and informal networks. As doctoral students participate in seminars, conferences, and research groups, they gradually notice how collaborations form, how invitations circulate, and how scholarly visibility develops within academic communities. Access to certain opportunities, such as research partnerships, conference presentations, or future employment possibilities, is not always determined solely by the quality of one’s work. Instead, these opportunities often emerge through professional connections and interactions within disciplinary networks. Through these experiences, many doctoral students begin to understand that building relationships and participating in academic communities can play an important role in shaping how opportunities unfold throughout an academic career.

Finally, many doctoral students come to realise that success in doctoral education is often framed as more than simply completing a degree. The PhD is frequently portrayed as a transformative process that reshapes how students think, work, and understand themselves as scholars. Alongside producing original research, students often encounter expectations that their work should contribute meaningfully to knowledge or to society. Over time, these expectations come to feel like natural markers of what it means to be a “good scholar.” In this context, academic success involves not only intellectual achievement but also demonstrating that one’s research and scholarly identity contribute to the wider academic community.

Who shapes the norms of doctoral education?

Supervisors are often the first and most influential people through whom doctoral students learn how academia really works. They do far more than guide a project or comment on drafts. Through feedback, meeting dynamics, publishing advice, authorship decisions, and even silence, supervisors communicate what counts as credible research, what kinds of behaviour are acceptable, and what academic success should look like. Over time, doctoral students begin to read these interactions carefully. They learn how to frame arguments, when to speak with confidence, when to hold back, and how far they can push an idea before it is seen as risky or inappropriate. In this sense, supervision becomes a key site where legitimacy is granted, withheld, negotiated, and internalised. What makes this especially powerful is that these lessons are rarely taught explicitly. They are absorbed through everyday exchanges, through dependence on references and endorsements, and through the need to anticipate a supervisor’s preferences to move forward. As a result, supervisors do not simply support doctoral education; they actively shape the hidden norms through which students come to understand what it means to be a “good scholar.”

Universities themselves quietly shape many of the norms doctoral students come to recognise as part of academic life. At first, institutional processes can appear straightforward: there are forms to complete, milestones to pass, reports to submit, and funding rules to follow. But as doctoral students move through their programmes, they begin to see that these procedures do more than organise administrative tasks. They reveal how academic work is structured and evaluated within the university. Milestone reviews, progress reports, scholarship conditions, and funding timelines gradually signal what kinds of work are valued and how progress should be demonstrated. Over time, students start to recognise that expectations around productivity, measurable outputs, and timely completion are built into the institutional environment itself. These structures can also shape how different students experience doctoral study. Access to conferences, research opportunities, and academic networks is often easier for those who are fully embedded in university life. Students studying part-time or balancing external work may find it harder to participate in these activities, even though they are often important for building visibility and connections within a field. Funding arrangements and scholarship conditions can therefore influence not only how doctoral work is organised but also which opportunities become available during the doctoral journey. In this way, universities do more than administer doctoral programmes. Through their policies, procedures, and resource structures, they quietly reinforce many of the norms that shape how academic work is organised, recognised, and valued.

Academic journals and editors also play an important role in shaping the norms of academic life. As doctoral students begin submitting manuscripts and receiving reviewer feedback, they quickly discover that publishing is not simply about presenting research findings. The peer-review process often communicates what kinds of questions, theoretical approaches, and methodological choices are considered acceptable within a field. Editors decide which manuscripts move forward for review, and reviewers evaluate whether a paper fits the expectations of the journal and the broader discipline. Through rounds of revision and feedback, authors are frequently encouraged to frame their arguments in particular ways, engage with certain bodies of literature, or position their work within established debates. Over time, these experiences reveal how journals help define the boundaries of credible scholarship. Publishing, therefore, becomes more than a mechanism for sharing knowledge. It is also one of the ways disciplinary standards are reinforced, and scholars learn which kinds of research are most likely to gain recognition within the academic field.

Peers and broader academic communities also play an important role in making these norms visible to doctoral students. Much of what students learn about academic life emerges through informal conversations with colleagues, shared experiences in research groups, and interactions at seminars or conferences. Discussions about publishing strategies, responding to reviewer feedback, or navigating institutional processes often circulate among doctoral students and early-career researchers. Through these exchanges, students begin to piece together how the academic field operates and how opportunities emerge within it. Peers also provide important insights into the practical realities of doctoral study, from managing workloads to navigating professional expectations. In this way, everyday interactions within academic communities help translate the often opaque rules of academia into shared understandings of how the system works.

Why these hidden norms matter for doctoral education

Recognising the hidden norms of doctoral education matters because they shape how doctoral students understand success, belonging, and possibility within academia. When these expectations remain invisible, students are often left to interpret them on their own. Learning how publishing works, how institutional systems operate, or how professional relationships influence opportunities becomes a process of trial and error rather than guidance. For many students, particularly those entering academia without prior exposure to academic culture, this hidden curriculum can make the doctoral journey feel uncertain and difficult to navigate.

Making these norms more visible does not mean removing the intellectual challenge of doctoral study. Rather, it means recognising that becoming a scholar involves learning how the academic field operates and producing research within it. Greater transparency about how academic work is evaluated, how opportunities emerge, and how institutional structures shape academic life could help doctoral students better understand the environments they are entering.

At the same time, recognising the hidden curriculum also invites reflection within academic communities themselves. Supervisors, institutions, journals, and scholarly networks all play roles in shaping the expectations that doctoral students encounter. Becoming more aware of these processes may help create doctoral environments where expectations are clearer and where students are better supported as they learn to navigate academic life.

Ultimately, doctoral education is not only about producing knowledge. It is also about learning how a scholarly community functions and how one might find a place within it. By bringing these hidden norms into view, we can better understand the often unseen processes through which scholars are formed.

Questions to ponder

What unspoken rule did you encounter during your doctoral journey, and how did you learn about it?

Who or what has shaped your understanding of what it means to be a “successful” doctoral student in your academic environment?

In what ways might hidden norms in doctoral education advantage some students while creating barriers for others?

How might supervisors, institutions, and doctoral communities make the hidden rules of academia more visible and more equitable for future students?

Research funding acknowledgement
Note: We acknowledge that this research was made possible by a Research Grant from the Higher Education Research and Development Society of Australia and a Research Support Seeding Grant from the School of Curriculum, Teaching, and Inclusive Education at Monash University.

Becoming a scholar together: why doctoral writing groups matter

by Lynette Pretorius

Posted: 27 February, 20268 April, 2026

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Abdul Qawi Noori

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Abdul Qawi Noori is an educator and PhD researcher. His scholarly focus lies in doctoral education, higher education cultures, and academic life across global contexts. His broader interests include comparative and international education, decolonisation, and English education.

Dr Michael J. Henderson

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Dr Michael J. Henderson is an academic educator and researcher. His scholarly interests are in the areas of adult learning and choice-making, higher education research approaches, leadership, and technologies (inside and outside of education). He is currently developing a laptop-based AI-enabled tool set for an upcoming project.

Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

We often imagine doctoral writing as a solitary endeavour. The image of a PhD candidate working alone, a lone ‘genius’ wrestling with literature, writing drafts, chasing deadlines, and decoding reviewer comments, still dominates academic and public culture. When writing stalls or publications don’t succeed, we tend to blame the individual: a supposed lack of discipline, poor writing skills, or weak academic language. Struggle becomes a private burden, and many doctoral researchers internalise it as personal failure. Yet, writing has never been a purely individual practice. It is learned through participation: by talking about ideas, sharing unfinished drafts, observing how others revise, and engaging in dialogue about what counts as convincing academic work. Doctoral writing groups bring these often invisible processes into the open. They function as communities of practice where doctoral researchers collectively learn how to write, publish, and belong in academia.

Within writing groups, doctoral students do far more than polish dissertation paragraphs or sentences. They discuss ideas, test arguments, give and receive feedback, and gradually develop a sense of scholarly identity. These groups operate as critical sites of academic socialisation, where tacit disciplinary norms become discussable and where writing is understood not merely as output, but as a shared intellectual and relational practice. For many doctoral researchers, particularly those navigating unfamiliar academic cultures, writing groups offer one of the few structured spaces where scholarly participation can be safely explored and sustained.

What do doctoral writing groups actually do?

Academic socialisation is not a simple process of absorbing institutional rules. It involves learning how knowledge is constructed, how authority is performed, and how uncertainty is managed in scholarly work. Writing groups play a crucial role in this process by creating dialogic spaces where doctoral researchers can collectively interpret the expectations of academic writing and publishing. Through regular discussion and feedback, participants in writing groups learn how disciplinary arguments are structured, how voice is negotiated, and how critique operates as a generative rather than punitive force.

Importantly, writing groups normalise struggle. Seeing peers grapple with similar challenges disrupts the myth that successful academic writing is effortless or innate. Confidence, in this context, is not a fixed personal attribute but a relational accomplishment that emerges through shared reflective practice in a space that fosters mutual support and repeated engagement with feedback.

These social processes matter because writing is inseparable from identity. Learning to write academically is also learning how to position oneself as a legitimate contributor to a field. Writing groups, therefore, serve as spaces where doctoral students not only improve texts but also actively become scholars.

Our most recent paper synthesised findings from forty-one studies on doctoral writing groups and provides compelling evidence for the pedagogical significance of these spaces. Across diverse disciplines and institutional contexts, writing groups consistently emerged as central environments for learning how to write for publication and how to navigate the emotional and intellectual demands of academic work. The paper demonstrates that writing groups directly support publication readiness by making the hidden curriculum of academia visible. Within these groups, doctoral researchers learn how to select journals, interpret reviewer feedback, respond strategically to critique, and manage rejection as a normal part of scholarly life. As such, writing groups can be understood as informal pedagogical apprenticeships that transform opaque publishing processes into collective learning experiences.

A particularly significant finding concerns writing confidence. Rather than preceding successful writing, our findings show that confidence is produced through participation. It develops as doctoral researchers observe peers revise drafts, engage in feedback exchanges, and persist through setbacks. This challenges deficit-based models that locate writing difficulty within individuals and instead highlights the social and structural conditions that enable doctoral writers to flourish.

Read the paper

Why does this matter?

These findings have important implications for how doctoral writing and publishing are understood. Writing groups should not be viewed as optional supports, wellness initiatives, or productivity tools for struggling students. They are foundational pedagogical spaces where skill development, identity formation, and scholarly belonging intersect.

For doctoral researchers, writing groups counter the profound isolation that often characterises advanced research. They provide continuity, accountability, and a sense of shared purpose. For supervisors and educators, they offer complementary spaces where learning unfolds collectively rather than solely through hierarchical supervision relationships. For institutions, writing groups represent a powerful mechanism for enhancing equity by demystifying academic norms and supporting diverse pathways into scholarly participation.

What if writing groups were central to doctoral education?

Taken together, the evidence in our latest study calls for a shift in how doctoral education is imagined and organised. If publishing is a central expectation of doctoral training, then the pedagogical structures that support learning to write and publish must be embedded systematically within doctoral programs. Writing groups should be recognised as essential infrastructure rather than left to informal or ad hoc arrangements. For theory, this reframes doctoral writing as a socially situated practice of becoming rather than an individual technical skill. For practice, it highlights the need for intentional design, skilled facilitation, and institutional investment in writing groups that foster psychological safety, inclusivity, and reflexive engagement with academic norms.

Moving beyond the individual deficit model requires a corresponding shift in institutional imagination. Doctoral writing groups exemplify how learning is collective, dialogic, and relational. By formally recognising and supporting these spaces, universities can replace a pedagogy of isolation with a pedagogy of shared learning and belonging in academia.

Questions to ponder

What messages about “good” academic writing did you internalise during your doctoral training? Where did they come from and how did you learn these norms?

Do writing groups address or reproduce the norms of academic writing?

What are the implicit norms of academic publishing?

How can academic careers be influenced by inadequate support or inexperienced writing group facilitation?

How do institutional structures either support or undermine the sustainability of doctoral writing groups?

Research funding acknowledgement

Note: We acknowledge that this research was made possible through funding from the Monash-Warwick Alliance Education Fund and a Research Grant from the Higher Education Research and Development Society of Australia.

The questions that keep me up at night and what I plan to do about them in 2026

by Lynette Pretorius

Posted: 20 January, 2026

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Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Hi everyone, and welcome to The Scholar’s Way for 2026! As I start the year back at work, I thought it would be a good time to reflect on what I do. A nice introduction to my new subscribers and a reminder of why you are here if you’ve subscribed for a while. So buckle up for some exciting research-related reflections and plans for the year!

First, I am particularly passionate about doctoral education, so you will see me posting a lot about how to improve the experiences of doctoral education. I have published widely about the benefits of doctoral writing groups. In particular, I keep coming back to the same question: “How do writing groups support doctoral student wellbeing and academic identity formation?”. Some of my favourite papers about writing groups include: Learning Together Through Collaborative Peer Feedback and Discussion, Doctoral Writing Groups as Vehicles for Pastoral Care, and Reflection for Learning in Doctoral Writing Groups. I currently have two papers in peer review about writing groups, so watch this space for more exciting writing groups work!

I have also written two books about the lived experiences of PhD students navigating academia: Wellbeing in Doctoral Education and Research and Teaching in a Pandemic World. These practical books offered students a platform to share their own stories in their own words. This allowed me to reveal the invisible culture of doctoral education. At the moment, I’m particularly interested in how PhD students learn about, and navigate, the often-unspoken norms, rules, and complex expectations of academia. I’ve previously shown that the system of academia marginalises and disempowers PhD students. Currently, I am asking: “How do students’ cultural backgrounds, personal experiences, and social resources shape their doctoral journeys?” and “How can doctoral programmes be more inclusive for students with diverse experiences?”. I’m busy analysing a huge dataset and hope to write several papers! Stay tuned! 😎

Second, I post a lot about AI literacy in higher education. I often wonder, “How does GenAI help or complicate research and teaching?” and “How can educators encourage their students to use GenAI in a way that enhances their higher-order thinking?”. I was one of the first to try to define AI literacy in the age of GenAI. I have since developed this definition into a comprehensive framework, showing that AI literacy comprises five domains: foundational, conceptual, social, ethical, and socio-emotional. At the moment, I am particularly interested in the equity and ethical dimensions of GenAI in academia. I also worked with colleagues from around the world to develop an ETHICAL AI use framework for higher education. Most recently, I wrote a paper with my PhD students demonstrating how GenAI can empower scholars from non-English-speaking backgrounds, helping to democratise and decolonise academia. It is one of my favourite papers I’ve written, so make sure to check it out! This year, I am focusing on editing two open-access practice-based books on GenAI use in higher education, as well as writing several papers on how GenAI can be used to foster critical thinking. 🤖

Third, I am also interested in exploring how research is actually done. I ask myself: “How can emerging scholars be equipped with the literacy to conduct research in a sound, ethical, and reflexive manner?” I am perhaps best known for my work explaining how research paradigms work. Ontology, epistemology, and axiology cause significant confusion for researchers, so I created a practical, easy-to-understand introductory paper that explains each term and how different combinations of these terms lead to distinct paradigms. The paper has been downloaded nearly 30,000 times! 🎉 I have recently been exploring the implications of GenAI on the research process. I showed that GenAI can foster researchers’ higher-order thinking and reflexivity as a partner in data analysis. I also showed how GenAI can be a legitimate source of data generation for autoethnography. I also recently explored how pseudonyms and demographics are used, showing that it is a much more ethical and empowering approach to give participants space to choose their own names and how they are represented in research. Finally, I am particularly well-known for my methodological explanations of the theoretical aspects of autoethnography and its practical application. This year, I am editing a book that expands my research paradigms paper into a practical guide. I am also editing a book on how to actually do reflexivity in qualitative research.

So if you’re passionate about reshaping higher education, supporting doctoral students, or exploring the creative possibilities of research design, you’re in the right place. Subscribe to follow along for updates on my latest publications, reflections on research, and practical how-to-guides. A final note: make sure to follow me on Threads or Bluesky, where you will also find me posting about my huskies (a lot!), books, and food.

Do you have an idea about what I should explore in my research? What are the research questions that keep you up at night? Comment below so that we can reshape academia together.

Deadline extended – you can still submit your abstract! 🎉

by Lynette Pretorius

Posted: 10 November, 202510 December, 2025

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Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Hi everyone!

A quick note to let you know the deadline has been extended to submit an abstract for our upcoming research paradigms book. Final abstracts are due 28 November 2025 at 12PM AEST (Melbourne time; UTC+11). So you still have time! 🎉 We are looking for stories from all different paradigms – how did your research paradigm actually shape your research design, practice, and impact? Share your stories to help others navigate the complexities of ontology, epistemology, and axiology!

Please also share with colleagues across disciplines: method stories from lab, field, classroom, clinic, and community settings are all welcome.

👉 Submit your abstract

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Call for abstracts for our research paradigms handbook!

by Lynette Pretorius

Posted: 25 September, 202523 January, 2026

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We are seeking chapter contributions for a forthcoming edited book titled The Researcher’s Compass: Choosing Your Paradigm, Finding Your Voice. This book aims to demystify research paradigms by offering accessible, reflective, and grounded accounts of how paradigms shape research design, practice, and identity. The book will be co-edited by Dr Lynette Pretorius and Dr Basil Cahusac de Caux.

Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Dr Basil Cahusac de Caux

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Dr Basil Cahusac de Caux is an Associate Professor with a specialisation in the sociology of higher education, postgraduate research, and the sociology of language.

This book is designed for early career researchers, doctoral students, supervisors, and interdisciplinary scholars who want to better understand how ontology, epistemology, and axiology influence the way we know, question, and explore the world through research. By using the metaphor of a compass, the book will guide readers in navigating the often murky terrain of research philosophy. The book will begin with foundational chapters exploring the “big three” philosophical questions (ontology, epistemology, and axiology).

The second part of the book, for which this call is issued, will feature reflexive and practical contributions from researchers across disciplines and paradigms. These chapters should provide grounded, narrative accounts of how specific paradigms shaped research questions, relationships, ethical decisions, and researcher identity. We invite expressions of interest from researchers who:

Have conducted a research project situated within a specific paradigm. We seek chapters from those who have used the more traditional paradigms (e.g. Positivism, Post-Positivism, Constructivism, Interpretivism, Critical Realism, or Pragmatism) as well as those who have used emerging or non-Western paradigms (e.g., Indigenous Paradigms, Post-Colonial or Decolonial Paradigms, Transformative Paradigms, Religious Paradigms, Post-Humanist Paradigms, or Queer Paradigms).
Are willing to reflect critically on how their paradigm influenced the design, process, ethics, and outcomes of their work.
Are open to writing in a clear, accessible, and reflective style, suitable for readers who may be new to research paradigms.
Can commit to peer reviewing two of the chapters in the book in 2026.

We welcome contributions from researchers across all disciplines, cultures, and career stages. Collaborative or co-authored chapters are also most welcome.

Chapter Structure

Each chapter will follow a shared reflective scaffold:

What paradigm did you choose, and why?
How did this paradigm shape your research questions, methodology, and relationships with data, participants, or concepts?
What challenges, tensions, or surprises did you experience working within this paradigm?
How has this paradigm influenced your understanding of yourself as a researcher (your identity, purpose, or practice)?

Chapters should be approximately 5,000–6,000 words, written in an engaging, thoughtful, and accessible style. References should follow APA 7th edition.

For an example of the style and tone of writing we are expecting, you can refer to the paper below.

Demystifying Research Paradigms

Key Dates

Abstracts due: 10 November 2025
**Deadline extended: Final abstracts are due 28 November 2025 at 12PM AEST (Melbourne time; UTC+11).
Notification of acceptance: Start of December 2025
Full chapters due: 30 March 2026

Each accepted chapter author will be expected to peer review at least two other chapters in the book during 2026.

How to Submit

Please submit your abstract using the button below.

Sumbit your abstract

If you have any questions, please direct them to Dr Lynette Pretorius (Contact details).

Seeing myself in pixels: What happens when GenAI becomes a co-researcher?

by Lynette Pretorius

Posted: 27 August, 202510 December, 2025

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Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

I didn’t set out to write an essay about academic identity, generative AI, and publishing politics. But, as with so many qualitative journeys, the story found me first. What started as a playful experiment with image generation soon became a critical turning point in how I understand knowledge, creativity, and resistance within the academy. Seeing Myself in Pixels, my latest autoethnographic essay, tells that story.

Read Seeing myself in pixels

Let me share a little of what happened and why I think it matters. I used GenAI, specifically image-generating tools like DALL·E and ChatGPT, to create two visual representations of my academic identity: one as an educator, the other as a researcher. These weren’t just illustrations for a paper. They were evidence. They helped me see myself more clearly, ask deeper questions, and articulate values that had previously remained unspoken.

And then… they were deleted.

Despite surviving peer review and editorial approval, the images were removed by the publisher at the final stage. The reason? A blanket policy against GenAI-generated figures, even though the book itself was about GenAI in higher education.

The irony wasn’t lost on me.

In qualitative research, we often talk about “making the invisible visible”. That’s what these images did. They surfaced metaphors, values, tensions, and identities that weren’t easily captured in prose. Working with GenAI wasn’t smooth or straightforward. It forced me to confront stereotypes (“university professor” almost always defaulted to an older white man), question aesthetic choices, and reckon with my own reactions. The image of myself as a hyper-glamorous figure in a fitted and revealing dress? That stung. But instead of rejecting it outright, I used the discomfort as compost for deeper reflection. Why did this feel wrong? What gendered expectations were being surfaced?

In this way, the process became iterative and affective. Prompt. Reflect. Revise. Repeat. I called this my “evidence tree” method: germinating ideas, branching into new directions, tending to nuance, and harvesting insight.

If you are interested in how to apply this method, you can watch the video below.

But when those co-created images were removed from the final chapter, it wasn’t just the visuals that were lost. It was a particular way of knowing that got silenced.

So, I made a choice. I published the images in an open-access repository, cited them in the chapter, and wrote Seeing Myself in Pixels to document the erasure.

Call it a quiet act of academic defiance.

This experience laid bare a fundamental tension in academia: What kinds of knowledge are considered legitimate? And who gets to decide? We talk a lot about innovation in research, but often still cling to conventional forms. Text is trusted. Emotion is suspect. Visuals are decoration, not argument. And anything co-created with GenAI? Treated as a risk, not a resource.

But this isn’t just about policy. It’s about power. The gatekeeping logic that removed my images echoes broader dynamics in scholarly communication where multimodal, affective, or experimental work is often sidelined. The publishing system rewards neatness over nuance, prose over presence, and familiarity over innovation. By documenting this erasure, I wanted to make visible the institutional mechanisms that quietly shape what counts as knowledge.

This wasn’t just a personal journey, it reshaped how I teach, too. In my autoethnography unit, I now invite students to create GenAI-generated images as part of their own identity explorations in the classroom. Together, we ask: How does visual co-creation help us see ourselves and our stories differently? What gets revealed when we look beyond text?

One of my proudest classroom moments involved unveiling a GenAI-generated “Academic Avenger” action figure of myself, complete with accessories. Yes, it was playful. Yes, the figure wasn’t perfect. But it sparked meaningful discussion about academic labour, visibility, and imagination. Creativity became rigour. Gen AI became an interlocutor. Learning came alive.

Throughout this process, I didn’t just use GenAI as a tool, I actively collaborated with it. I’ve trained a customised version of ChatGPT called Artzi Dax (named after my favourite Star Trek 🖖🏼 character while showcasing artistic flair), who has now become an intellectual partner of sorts. It (or should I say she?) didn’t write the essay for me. Artzi Dax helped me think more clearly, revise more creatively, and reflect more deeply. In fact, it was Artzi Dax who helped me transform my original four research steps into the growth metaphor, which ultimately shaped the entire essay.

So can a machine be a co-researcher? I believe so, if we approach it reflexively, ethically, and with imagination. Seeing Myself in Pixels is not just an essay. It’s a call to action. We need to rethink what counts as scholarly labour. We need to make room for affect, imagination, and multimodality. And we need to resist the quiet silencing that happens when institutional norms override epistemic possibility.

If academia is to remain intellectually vibrant and humane, we must create space for new forms of knowledge creation: forms that not only tell, but show; that not only argue, but resonate. As one of my students once said:

✨ “Don’t let the Muggles get you down.” ✨

Questions to ponder

How do institutional publishing norms shape what “counts” as valid research?

In what ways can GenAI serve as a co-creator rather than a mere tool?

What hidden forms of knowledge might we be ignoring in academic work?

How can educators integrate creative co-creation methods into research training?

When AI meets Ubuntu: rethinking power in academic writing

by Lynette Pretorius

Posted: 15 August, 202510 December, 2025

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Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Hi everyone! I’m excited to share a new podcast episode that I think you’ll enjoy. Last week, I had the privilege of presenting my latest research on generative AI to the Australian Association for Research in Education. We explored some of the big questions shaping higher education right now, particularly how we can foster AI literacy in ways that are compassionate and equitable, and what that type of learning might look like in an AI-driven world. If you’re curious about the discussion, you can listen to the full talk below. The papers I mentioned are freely available, so if something sparks your interest, you can explore the research by clicking on the links. I’d love to hear your thoughts! 🙂

GenAI and Ubuntu in academic writing – how can generative AI disrupt gatekeeping in academic writing and promote epistemic justice?
ETHICAL AI framework – how do you use generative AI ethically?
AI literacy framework – what is AI literacy?

Reclaiming our words: how generative AI helps multilingual scholars find their voice

by Lynette Pretorius

Posted: 25 June, 202510 December, 2025

2 Comments

Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

Redi Pudyanti

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Redi Pudyanti is an educator and researcher pursuing her PhD on the influence of local wisdom on graduate employability. Her other research interests are Indigenisation, decolonisation, and generative AI.

Acknowledgement: This blog post extends our presentation at the Higher Education Research and Development Society of Australasia (HERDSA) Conference 2025. We acknowledge the other co-authors of our paper, as it was a truly collaborative project: Huy-Hoang Huynh, Ziqi Li, Abdul Qawi Noori, and Zhiheng Zhou. As the South African proverb says: “If you want to run fast, run alone; if you want to run far, run together”.

You can listen to the HERDSA2025 presentation below.

In the halls of academia, where prestige often correlates with fluency in a particular kind of English communication, having a voice can feel like a privilege, not a right. For multilingual scholars, this can create a disconnect between who they are and what academia expects of them. These scholars have rich and diverse intellectual contributions, but these are often filtered, flattened, or forgotten by the English-language customs of academia. This isn’t just about grammar or vocabulary. It’s about whose knowledge counts, whose voice is deemed legitimate, and how power circulates in scholarly spaces.

Academic writing is often seen as a neutral skill: something that anyone can learn with enough practice, feedback, and hard work. In reality, though, this idea of neutrality is misleading. Beneath the surface, academic writing carries a host of hidden expectations: about how to structure an argument, what kind of tone sounds “professional”, which sources are seen as credible, and even what types of ideas are considered valuable or “good”. These expectations aren’t universal: they’re shaped by English-speaking academic traditions and Western ways of thinking.

For multilingual scholars, especially those coming from different cultural and educational backgrounds, this can feel like stepping into a performance where the rules haven’t been explained. They’re expected not just to write clearly, but to sound a certain way: to mirror the phrasing, logic, and stylistic choices of native English speakers who have been immersed in this Western ways of thinking from an early age. It’s a bit like being asked to join a play mid-scene, in a language that’s not your own, with the added pressure of sounding polished and convincing. The result is often a quiet and persistent pressure to conform: to smooth out cultural expression, to set aside familiar ways of knowing, and to rewrite one’s voice to match what academia deems “legitimate”. In this context, writing isn’t just about communicating ideas, it becomes a test of belonging.

This experience can be deeply isolating. When your ideas are dismissed because they don’t fit a particular format, or when you constantly feel like your writing is being judged through the lens of language proficiency rather than substance, it can leave you feeling invisible. For many multilingual scholars, it’s not just a matter of learning the rules; it’s the emotional weight of having to silence parts of who you are just to be taken seriously. Over time, this can lead to a sense of marginalisation, where your contributions feel undervalued, and your cultural perspective feels out of place. It’s certainly not that these scholars lack ideas or insight; it’s that the academic system often fails to make room for how those ideas are expressed.

We have found that these challenges can make academic life feel like a constant uphill battle, especially when the very structures meant to support learning and innovation exclude our ways of thinking and being. Yet, rather than remain silent or adapt unquestioningly, we have been actively seeking new ways to engage with academia in ways that honour both our cultural identities and scholarly ambitions. This is where our latest research began: with a shared desire to not only survive academia, but to reshape it. Through community, reflection, and the careful integration of generative AI, we began to imagine what a more just and inclusive academic future could look like.

Read the paper

Writing together, thinking together: a decolonising vision for academic writing

Our new paper offers a timely vision of the future: one where academic spaces are reimagined as inclusive, relational, and linguistically diverse, and where generative AI is embraced not as a threat to academic integrity and rigour, but as a partner in knowledge creation. To develop this vision of academia, we combined the Southern African philosophy of Ubuntu (a philosophy that says, “I am because we are”) with collaborative autoethnography and the strategic use of generative AI to reframe generative AI as a relational tool for epistemic justice. As noted in another blog post, epistemic justice is about fairness: it ensures that everyone’s voice and knowledge are equally respected, no matter where they come from or how they express themselves. In our vision of a more just and inclusive academic future, multilingual scholars will feel empowered to contribute fully, confidently, and in ways that honour their linguistic and cultural identities within global scholarly conversations.

One of the most important parts of our study was how we chose to think about and use generative AI. Ubuntu reminded us that we’re shaped by our relationships with others, and that knowledge and growth are shared, not owned by any one person. In many academic settings, writing is treated as something you do alone. Seeing academic writing through the Ubuntu philosophy, however, we saw knowledge creation and dissemination as something academia should do together. In our group, we gave each other feedback not to criticise, but to support and learn from one another. In this spirit, generative AI became more than just a helper. It became a kind of thinking partner that joined us in our conversations, helping us express our ideas more clearly while still keeping our voices true to who we are. Our generative AI use empowered us while also honouring our identities as multilingual speakers engaging with global academia.

At its heart, our work is about challenging the status quo in academia: we aim to decolonise how knowledge can be created and shared in academia. As shown in our figure below, we started with Ubuntu, a philosophy that puts relationships, community, and shared responsibility at the centre. From there, we used a method called collaborative autoethnography, which allowed us to tell our personal stories, learn from each other in a supportive, reflective way, and explore the cultural complexities present within academia. Then we brought in generative AI, not to make our writing faster, but to help us express our ideas more clearly, question academic norms, and speak up in ways that felt true to ourselves. These three elements aren’t separate steps. Like threads in a tapestry, they are woven together to create a new way of doing research. Together, they helped us imagine a more inclusive kind of academic voice: one that’s ethical, shared, and shaped by many perspectives, not just one. The dots in the diagram show how these ideas flow between people, values, and technology, all working together to build a better future for academic work.

Stories of reclamation and agency

One of the most vivid examples from the study involves the translation of a Chinese idiom which, when processed through a conventional tool, was reduced to a flat literalism: “seeing flowers in the mist, looking at the moon in the water”. While technically accurate, the translation missed the metaphorical essence of the idiom. When Ziqi, one of the authors, posed the same phrase to ChatGPT, the response captured both the poetic beauty and interpretive depth she needed by offering: “The situation is shrouded in mystery, constantly shifting, and challenging to grasp”. In that moment, the idiom didn’t just survive translation, it transcended it. For Ziqi, this wasn’t merely a linguistic success; it was a profound moment of affirmation. Her cultural ways of knowing embedded in the metaphor’s symbolism and rhythm didn’t have to be abandoned or diluted to be legible in academic English. They could be translated with meaning, not despite it.

For others in the group, generative AI proved equally transformative in different contexts. It supported the generation of constructive feedback, assisted in structuring complex presentations, and offered clarity around dense theoretical frameworks. In Redi’s case of balancing the demands of doctoral research with motherhood, generative AI became an unexpected ally in maintaining wellbeing. Whether generating weekly schedules, planning meals, or brainstorming research questions, it helped her lighten the cognitive load, carving out space for reflection, family, and rest.

Importantly, though, our paper isn’t a love letter to generative AI. We are acutely aware of the ethical tensions. Generative AI tools are shaped by the biases of their training data, data which are often steeped in colonial logics, linguistic hierarchies, and Western-centric perspectives. The risk of overreliance or uncritical adoption is real. Yet, what shines through in our reflections is not techno-optimism, but intentionality. We didn’t blindly accept what generative AI offered. Instead, we engaged with it critically, revising, interrogating, and adapting output to ensure the content preserved cultural nuance and scholarly integrity.

Implications for academia

What we did wasn’t about quietly fitting in or changing ourselves to match the usual expectations of academic writing. It’s something more powerful: it was an act of academic reclamation. We used generative AI thoughtfully and with care, not to erase our voices, but to amplify them. Our voices are shaped by different cultures, languages, and ways of thinking, and these types of voices don’t always fit neatly into the typical mould of English-speaking academia. By working with generative AI, not just relying on it, we found ways to express our ideas more clearly without losing who we are. We’re not just trying to keep up, we’re helping to change what academic writing can be. We’re showing that it’s possible to honour cultural and linguistic diversity in research, and that there’s real value in broadening what counts as a “legitimate” academic voice. In doing so, we’re not just joining the conversation, we’re reshaping it. Prompt by prompt, paragraph by paragraph, we’re building an academic world that listens to more voices, tells more stories, and reflects more diverse ways of knowing.

Our study calls on educators, institutions, publishers, and policy-makers to rethink what counts as “good writing” and whose voices are heard in academic discourses. It invites everyone to question the academic orthodoxy that frames multilingual ways of thinking as flawed or generative AI use as inherently dishonest. It shows that when used ethically and reflexively, generative AI can level the playing field, not by simplifying scholars’ ideas, but by enabling them to be expressed more fully. By integrating Ubuntu, collaborative autoethnography, and generative AI, we empowered each other and contributed to decolonising the academy by advancing non-traditional voices. Our research presents a compelling vision for a more inclusive academy: one where multilingualism is celebrated, not hidden, and where academic voice is something to be reclaimed, not earned through conformity. As Lynette notes in the paper:

I have also had many discussions with colleagues in other countries who seem to believe that the use of generative AI has led to the loss of academic rigour or critical thinking in students’ work. They either lament that they cannot clearly detect AI written work with tools such as Turnitin, or claim that whenever they see the words “delve” or “tapestry” they know that it is written by AI and should therefore be considered as cheating. […] I see this viewpoint as a form of academic orthodoxy, where written academic work is considered “rigorous” only when it has been written as it has always been. […] I wonder whether the same debates were circulating in academia when the typewriter was invented and those who used to write academic missives by hand thought that the typewriter would be a danger to academic rigour?

By the way, Lynette also shared two other studies at this year’s HERDSA conference. Follow the links below to explore those studies in more detail.

The transformative power of pseudonym choice

The AI Literacy Framework

If you are interested in learning more about this study, you can also listen to this podcast about the paper.

Questions to ponder

Whose standards define “good” academic writing? How do linguistic norms in academia privilege certain voices while marginalising others? In what ways might generative AI disrupt or reinforce these norms, and what responsibilities do scholars have in shaping its use?

Can technology be decolonial? Given that most generative AI tools are trained on predominantly Western data sources, is it possible for them to support decolonial knowledge practices? What conditions would need to be met for generative AI to serve as a truly inclusive and relational academic partner?

What does ethical generative AI use look like? Reflecting on the Ubuntu-inspired approach described in the post, how can scholars use generative AI tools ethically, without losing their cultural specificity or scholarly voice? How might institutions better support this kind of critical and agentive generative AI engagement?

Call for abstracts for our book on positionality and reflexivity in research!

by Lynette Pretorius

Posted: 10 June, 202510 December, 2025

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Dr Lynette Pretorius

Dr Lynette Pretorius is an award-winning educator and researcher specialising in doctoral education, AI literacy, research literacy, academic identity, and student wellbeing.

We are seeking expressions of interest for our new book provisionally titled Positionality & Reflexivity in Research (Editors: Sun Yee Yip and Lynette Pretorius from Monash University).

Whose research is it? Who owns it? Whose interests does it serve? Who benefits from it? Who has designed its questions and framed its scope? Who will carry it out? Who will write it up? How will its results be disseminated?
(Smith, 2021, p. 10)

Research across various knowledge traditions has challenged the notions of neutrality and objectivity, increasingly recognising that framing a research problem is inextricably linked to those granted the power to participate in knowledge creation within the institutional spaces of the academy and who have access to that knowledge.

To address the presence and impact of knowledge makers on the forms that knowledge takes, social science research has introduced “position” and often “positionality statements” as genres in which researchers typically consider certain social identities, including but not limited to race, class, gender, sexual orientation, and (dis)ability. A researcher’s positionality can influence all aspects of the research process, including study design, research questions, data collection, and analysis and understanding one’s positionality can shape the outcomes and trustworthiness of the results (Yip, 2023). While traditionally a common feature in qualitative research, some researchers have recently also argued for its relevance in quantitative research (Jamieson et al., 2022).

Reflexivity, the process of critically examining one’s assumptions, biases, and perspectives and how they might impact the research process, is considered a fundamental element in addressing a researcher’s positionality. It challenges researchers to critically analyse their positionality—their role, assumptions, and influence on the research process—and to reflect on how their engagement shapes their understanding of the issue under investigation, their research design, findings, and theories they develop and the communication of results (Addyman, 2025; Smith, 2021).

Yet, despite the growing recognition of the importance of positionality and reflexivity, there remains a surprising lack of evidence in resulting publications of researchers explicitly addressing their lived experiences in the field and how they practice reflexivity. This lack of transparency obscures the iterative and adaptive role that reflexivity plays in shaping research practices, insights, and contributions to theory development. By conceptualising their positionality and embracing reflexivity more effectively, researchers can examine their impact on the research process, reveal their work’s relational and emotional dynamics, and contribute in academically rigorous and practically relevant ways.

Given the increasing demand for researchers to disclose their positions in relation to the research they conduct and articulate their reflexivity practices, we invite chapters that offer profound and critical insights into personal experiences of examining positionalities and engaging in reflexivity within your research. This may pertain to your PhD projects or beyond.

We suggest that the chapter address (but is not limited to) the following guiding questions:

What is your research about?
What motivated you to embark on this research?
What is your position or standpoint in relation to your research?
How does your position impact different aspects of your research? e.g. research design, methodology, findings/results, theorisation etc.
How did you practice reflexivity? What strategies did you adopt/not adopt? Why did you utilise these strategies? In what ways are they helpful/unhelpful? What are the challenges? How did you address these challenges/overcome them?
What did you learn in the process?
How has this shaped your future practice?

Please express your interest by submitting an abstract/chapter proposal of no more than 500 words by clicking on the button below. You can also refer to this list, which we regularly update to reflect relevant published work on this topic.

Submit your abstract

All abstracts must be submitted by the 31st of July 2025. Notices of abstract acceptance will be emailed to authors by the 30th of September 2025.

If your abstract is accepted, you will develop your chapter, bearing in mind the following features:

Write in the first-person narrative style.
Chapters should be between 5,000 and 6,000 words, including abstract, references, footnotes, figures, and tables.
Include a 200-word abstract at the start of the chapter
Use APA 7 referencing style.

The full manuscript is due on 31 January 2026 and will be subjected to rigorous peer review.

If you have any questions regarding the expression of interest process, please email:
Dr Sun Yee Yip at sunyee.yip@monash.edu

Learn the basics of generative AI

by Lynette Pretorius

Posted: 2 June, 202510 December, 2025

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The AI Literacy Lab

Republished from The AI Literacy Lab.

The AI Literacy Lab is an interdisciplinary collaboration of educators and researchers investigating the implications of generative AI for teaching, learning, and scholarly inquiry.

Generative AI is reshaping the world, one image, paragraph, and data point at a time. Whether you’re a curious newcomer, an educator trying to keep up with the latest trends, or a student dipping your toes into artificial intelligence, you’re in the right place. Let’s unpack what generative AI actually is, why it matters, and how you can begin your learning journey with a few hand-picked videos.

What is generative AI?

Generative AI refers to a class of artificial intelligence that can create new content like text, images, music, code, and more. Think of it as a creative partner trained on vast amounts of data. These systems learn patterns, styles, and structures, and then use that knowledge to generate novel outputs that often feel surprisingly human-like.

Why should you care?

Generative AI isn’t just a tech trend, it’s a shift in how we produce knowledge, express creativity, and interact with machines. For educators, it’s reshaping pedagogy. For students, it’s changing how assignments are written and evaluated. For researchers, it’s opening up new methods of inquiry, simulation, and communication.

How do you use generative AI?

Prompt design is crucial when using generative AI because the quality of your prompt directly shapes the relevance, clarity, and creativity of the AI’s response. Well-crafted prompts help you guide generative AI more effectively, turning it into a powerful tool for learning, research, and problem-solving.

Developing AI literacy

Understanding the basics isn’t just about staying relevant; it’s about becoming literate in a rapidly evolving digital world. AI literacy is now a key component of digital citizenship, academic integrity, and lifelong learning.

Want to learn more? These posts are a good start:

Fostering AI literacy as students, teachers, and researchers

The AI Literacy Framework for higher education