Teaching Students to Teach Themselves

Why I abandoned lectures and built a learning system where students create knowledge together through environmental traces, discomfort, and radical self-direction

What you will take away, if you read up to the last line of this article:

• Traditional lectures are obsolete for modern learning

• Learning environments can be designed to trigger autonomous growth

• Real transformation requires reciprocal intensity and discomfort

(Watch the slide presentation of this article) 

I do not lecture. I have not for years. Partly because I am philosophically opposed to it, partly because I got tired of watching students scroll through their phones while pretending to take notes. Instead, I encourage my students to intentionally modify environments and watch the magic unfold. Before my students arrive to class, they have already encountered materials -- readings, videos, problem sets -- that modify their informational landscape. They show up having already wrestled with ideas, formed and shared opinions, gotten confused, gotten curious. Allegedly. Some show up having wrestled primarily with the snooze button. Class is not about me transferring knowledge from my head to theirs. It is about what emerges when prepared people collide with each other and the materials I have left scattered around the digital space.

The Framework

I call this approach Trace Pedagogy -- built on three integrated components. The flipped classroom provides the structural method: students prepare before class so sessions become active workspaces rather than passive reception halls. Self-Organizing Learning Environments (SOLEs) determine content delivery: students personalize their learning based on their wants and needs, creating tailor-made educational experiences at their own pace. Metamarks supply the catalytic element: the environmental traces students leave that trigger autonomous, reproducible, and scalable learning by themselves and others. Yes, I invented a new term. Every academic gets one. It is in the handbook.

Who This Is Really For

Let me be direct about something: my focus is not on the outliers. The handful of exceptional students will thrive anywhere -- they have track records showing they can teach themselves and adapt well in any learning environment. The few struggling students at the other end may simply not be interested in the method, the theme, or were forced to take my course against their will. I pay attention to both groups, but that is not where my passion lies. My passion is the median. The average student. Especially those who are struggling but have a strong desire to get better. This is where I focus most of my resources, energy, and attention. These are the students who make me care deeply about education -- the ones who show up wanting to improve but needing the right environment to unlock their potential. This is why I design Trace Pedagogy around the highest common denominator rather than setting a ceiling. I do not want to limit how far students can go. I trust that every student in my courses -- yes, every single one -- can produce and perform at the highest level possible, just like the best university students in the world. The structure exists to support that possibility, not cap it.

How It Actually Works

Contemporary education systems were designed for industrial-era standardization, not for today's rapidly changing world. My courses recognize that students can leverage technology and curiosity to learn collaboratively through exploration and discovery at their own pace, guided by minimal supervision but regular constructive feedback. And here is what students do not see: Trace Pedagogy is a continuous two-way exchange. What appears 'hands-off' in the classroom is actually the tip of the iceberg. Below the surface, I spend hours reviewing every single output students submit -- not skimming, actually reading and analyzing their work. I identify which ideas are gaining traction, which misconceptions are spreading, which students are struggling with particular concepts. Based on this analysis, I restructure the entire class session. This is why Trace Pedagogy requires roughly three times more preparation than traditional lectures. A lecture can be recycled. Your unique contributions cannot be.

The Flipped Component

The flipped classroom addresses a fundamental problem: lecture time is finite and inefficient for knowledge transmission. However, flipping alone often fails because students treat pre-class work as optional. I address this by making outputs -- graded weekly research-based responses -- the entry requirement for meaningful class participation. You cannot fake understanding when the entire session depends on what you discovered during preparation. If you show up unprepared, you are navigating a conversation where everyone else has already modified their understanding through engagement with materials you have not encountered. It is uncomfortable. That is intentional.

The Self-Organizing Component

The self-organizing component means I do not micromanage how you learn. You decide your pace, your focus within the broader topic, your angle of approach. Some students thrive immediately. Others -- especially those from educational systems built on memorization and passive reception -- spend the first few weeks thinking I have lost my mind. They are not entirely wrong. SOLEs risk leaving students directionless. I mitigate this through 'tailor-made scaffolds': structured frameworks that provide direction while allowing autonomy. Every assignment includes explicit guidance on skills to develop, questions to explore, and examples of strong work. Students build their own learning environments within intentionally designed boundaries. The assignments are demanding and require genuine intellectual effort. You cannot outsource them to AI, though you are welcome to use it as a leverage tool. After grading several hundred assignments, I have developed what I call 'AI detector superpowers'. I teach techniques like reverse engineering prompts, collective excitation through AI-assisted brainstorming, and creating custom scaffolds for specific learning goals. One student observed that I did not see AI as an enemy but rather used it as leverage to enhance their motivation to learn, calling the teaching style very futuristic. I prefer 'desperately trying to stay relevant in 2025', but I will accept 'Star Trek'-type of classroom in a heartbeat.

The Metamark Component

Here is where it gets interesting: students start leaving metamarks in the environment that other students encounter and respond to. Someone shares particularly incisive analysis in their output. Others read it, build on it, challenge it. Someone discovers a connection between this week's topic and last month's discussion. That connection becomes a new metamark in the shared environment, triggering further connections. The Canvas discussions accumulate strategic knowledge -- not just what to think but how to approach problems.

What makes metamarks fundamentally different from traditional assessment is transparency. Unlike exams that measure hidden individual progress at a single moment and keep those grades isolated, metamarks operate in full view. Everyone can see individual and collective advancement, judge progress for themselves, and learn directly from others' traces. This visibility creates progressive assessment rather than snapshot evaluation. Students gauge their own learning trajectory while simultaneously contributing to and benefiting from the group's accumulated knowledge. This transparency incentivizes contribution -- students recognize that their individual progress depends on the collective good, and the system is demonstrably fair because nothing is hidden.

This is where metamarks transform learning from additive to exponential. Traditional pedagogy treats each student's work as isolated: you complete assignments, receive grades, move on. Metamarks are documentations that make every contribution a potential catalyst. Your output does not just demonstrate your learning -- it modifies the environment for everyone who encounters it. This recursive process generates collective intelligence exceeding what any individual, including me, could produce alone. The metamark limitation is that traces can mislead as easily as guide. Poor analysis or misconceptions can propagate through the environment, as well as psychological cues. I address this through open individual, and honest, warming constructive feedback in every class: acknowledging specific contributions, naming what works and why, gently correcting what does not.

The Transformation Students Experience

The transformation is not smooth. One student admitted uncertainty about passing after struggling on the midterm. Another confessed it took substantial time before truly enjoying the class. These are descriptions of genuine intellectual growth, which is inherently uncomfortable. You do not expand your thinking while relaxed. What makes the discomfort worthwhile is developing capabilities you did not know you could possess. Students report dramatic improvements in time management -- they stop procrastinating because the structure makes delays immediately costly. One advised taking the course assignment by assignment, noting that despite struggling with procrastination initially, they challenged themselves to work hard and fixed bad habits with every discussion post and assignment. One student once classified me as a life coach who grades. Not bad definition whatsoever. The 21st century skills emerge organically through the structure. Interpersonal communication develops because class discussions demand articulating complex ideas clearly. Team collaboration becomes essential through group projects. Creative and critical thinking intensify because outputs require original analysis rather than summarizing sources.

The Scary Project

A signature element in my courses is what I call the 'Scary Project' -- a semester-long self-directed endeavor where students pursue something that simultaneously frightens and excites them. This assignment operationalizes three mindsets essential for navigating Trace Pedagogy: (i) grit (sustained commitment to long-term goals); (ii) growth (viewing challenges as opportunities rather than limitations); (iii) and divergent thinking (approaching problems from completely different perspectives). Students document their journey weekly, leaving traces not just of outcomes but of process -- the struggles, recalibrations, and insights that emerge when pushing beyond comfort zones. These documented traces become metamarks for themselves and classmates, showing how learning happens through repeated revisiting, remembering, reassessing, recalibrating, and reinforcing one's own environmental modifications.

Real-World Application

Everything in my courses is intentional. Every assignment addresses urgent, real-world problems. When students research financial literacy, they are building skills for managing their own resources. When they analyze sustainability challenges, they are preparing to work on the defining issue of their generation. The course content is never abstract -- it connects to problems they will encounter as professionals and citizens. Students do not just consume and produce content -- they build something together. Students who started the semester unable to articulate positions in discussion finish by leading complex conversations. Someone who initially struggled with academic writing produces work they are genuinely proud of.

What This Demands

From Students

Everything. Or at least, substantially more than typical courses. You need to complete outputs thoroughly, engage critically with materials, participate actively in discussions. Each class builds on previous work. If you fall behind, you are missing the environmental modifications that would have triggered your next insights. Active participation is essential. Turning on your camera, speaking up, contributing to discussions -- these are how you modify the shared environment. The course is conversation heavy, and it benefits everyone when people talk. Yes, this means you have to be visible and audible. I know. It is my least popular policy.

From Me

Trace Pedagogy requires reciprocal intensity. When students increase their effort, I must match it. If students submit thoughtful, complex outputs, I cannot respond with superficial feedback-- that would break the system. This creates a feedback loop where quality begets quality, but it also means I cannot coast. Ever. Students see me for three hours per week in class. They do not see the many hours I spend between sessions analyzing outputs, providing feedback, redesigning sessions, curating Canvas discussions, updating scaffolds, reaching out to struggling students, coordinating with guest speakers, and tracking individual progress on Scary Projects. I also strive to maintain a comfortable space where mistakes are learning opportunities rather than failures. This is not about being nice. It is about recognizing that Trace Pedagogy requires psychological safety. You cannot leave effective traces if you are terrified of being wrong.

The Honest Assessment

It is not easy. Multiple students emphasized: very challenging, takes significant effort, requires fairly advanced reading skills, demands active engagement throughout. But for students willing to navigate the discomfort, the payoff is substantial. Students describe enhanced communication abilities through extensive discussions and outputs encouraging collaborative work. They mention developing critical thinking through consistently challenging assignments requiring original analysis. The professional skills gained are highly sought after. Multiple students mention landing positions where employers specifically valued the collaborative approaches, AI integration techniques, and problem-solving frameworks developed in my courses.

Final Thoughts

Students who commit to navigating this structure -- who do the work, show up, and expect the same level of commitment from everyone -- experience genuine transformation. To those willing to tolerate the discomfort of actively building their own education rather than consuming someone else's, the results speak for themselves.

#TracePedagogy #FlippedClassroom #StudentCenteredLearning #HigherEdInnovation #CollectiveLearning #Metamark #StigmergyinEducation

The scariest place: Temple University Japan (TUJ) Cafeteria

By Marvin Starominski-Uehara, October 31st, 2024

Yes, you read it right. TUJ cafeteria is a scary place, a very scary one. It is so scary because it is not ordinary. It is not even unique since places like this are not supposed to exist. TUJ Cafeteria is a place where 99.99% of the world population have never experienced or can even image exist. You step in there and instantly feel out of place, something weird going on. On any given day, you will find in this cafeteria around two hundred college students from more than eighty countries and over a hundred different regions of the world casually walking around and having a good time with people who are, theoretically, so different from them. How is it possible that so many young adults from all these corners of the world can hang out together as if it is the most common thing to do, day in, day out?

Well, it might help to mention that in this environment, everyone has a very good command of verbal communication in English. I would also guess that more than half of those people bonding in this cafeteria are bilingual, and a third of them can speak multiple languages. Okay, you might be thinking now that all those young adults are a bunch of privileged individuals coming from elite education systems around the globe. I cannot deny that. Among these foreign students, there are children of political and business leaders who relocated to Tokyo. There are also many non-native English speakers whose parents invested heavily in international education for their children from a very young age. So, you might argue that this cafeteria is not representative of the global population because of the economic disparities within and between countries and regions. This is a fair point! I live in Miyazaki, one of the poorest prefectures in Japan (by Japanese standards), and I have yet to meet a student in my TUJ classes who was born and raised here.

But that is just the face value of the ‘scary’ diversity you feel when you are in this cafeteria. In this environment, there are also a number of students who come from low-income single-parent households. You will come across many students who decided to bet on themselves and take out loans to invest in their future. You will listen to many stories of personal struggles from students coming from marginalized, minority, and persecuted groups. These are real testimonials of resilience and perseverance, and they are not uncommon to be shared over casual conversations. So, there are many other elements, beyond the financial and economic ones, that explain the mix of people enjoying themselves in the TUJ Cafeteria. But this more nuanced understanding of this diverse community does not alleviate the anxiety one will certainly feel when being there for the very first time. It might even add more stress to those operating under expected rigid norms and attitudes. Like I said, TUJ Cafeteria is a scary place, a very scary one.

TUJ Cafeteria is scary because it is not what the world is but what it should be. Most parents would be totally overwhelmed stepping into this cafeteria. They would have little to no clue of what is happening in this environment. How can so many different looks, different clothes, different genders, different colors, different languages, and struggles co-exist? How is that even possible? This is not how 99.99% of the parents around the globe, including myself, grew up. This is not what we were told. This is far removed from what we have ever experienced and even imagined in our wildest dreams of diversity or just enjoying a glamorous cosmopolitan lifestyle. But here is the flip side: most of these same parents, like me, would be incredibly proud to see their children confidently navigating a world that values people for who they truly are, what they say, and how they act with respect and empathy toward everyone around them, especially the most vulnerable and marginalized. Sure, culture, physical traits, beliefs, and nationalities all shape who we are, what we believe, how we connect, and what we can dream of. But these institutional labels that are supposedly meant to help us feel more comfortable while growing into a predictable world of rules and customs are unceremoniously left behind the doors of those entering into TUJ Cafeteria. And for many of us, being stripped of what we have believed and experienced throughout our lives is quite unnerving. AT TUJ Cafeteria, 99.99% of the world population is asked to be naked. How much money you or your family have does not matter. What does matter, and what really helps you navigate diversity with confidence and make the most of it, is how proactive you can be, how willing you are to listen and learn, to compromise, to turn ideas into actions that help communities beyond those doors become less divided and more united. TUJ Cafeteria is indeed a very scary place, a place where dreams are never too scary to be dreamed of and achieved. And as a student of mine recently said in class: ‘Experiencing diversity can change the trajectory of your life. It really can!’

The Origins of the Stigmergy Network Theory

In my mid-twenties, after returning home from work, the janitor of the building complex I lived in asked me to call the police immediately as my mother had just been run over and was in hospital. After some frantic searches around public hospitals, I found her and learned she was clinically fine, but the shock of this experience led me to visit days later the exact location where she was hit by a motorcycle early evening. From this informal ‘inspection’ and conversations with residents and business owners, I learned that road accidents involving pedestrians occurred frequently at this intersection; however, no structural measures had been taken to mitigate these known risks. This experience then left me wondering i) What if I could share the risks, and evidence, of this intersection with a large audience in an easy, safe, and trusted way? What if I could learn what had happened before and monitor the structural and nonstructural measures taken by local officials -- and residents -- to mitigate these risks? How about creating something like this SenseCityVity project?

Ten years later, a toddler in Queensland died after being neglected and abused. That piece of news ‘hit me’ very hard as I had just become a father the year before. Pondering on what I could do to help this vulnerable group, as well as caretakers, I put together a research proposal to develop a mobile application that would collect ‘perceived risk inputs’ and provide, as a ‘weighted probabilistic output’, a set of recommendations for prevention and early intervention. Unfortunately, I have never had a chance to pursue this project titled: ‘Reducing the Cost Error of False Risks with Artificial Intelligence’. The main takeaway from this unrealized project was leading my curiosity to the field -- and potentials -- of artificial intelligence in the context of Error Management Theory so that I could incorporate those learnings into my future research projects.

I wrote the research proposal on child maltreatment because around that same time I was looking into the inherent and residual risks associated with the 2010/2011 Queensland Floods for my doctoral thesis. During my initial investigations on the early signs of this evolving risk, I came across a post shared in a forum from a concerned citizen urging residents living downstream the Brisbane River to evacuate due to the imminent water release from the Wivenhoe Dam. I became particularly interested in this message as it was uploaded days before the release of the official warning by authorities. As the underlying themes of my dissertation were risk perception and decision making, I could not stop wondering whether the number of deaths and missing victims would have been different, despite hindsight bias and related ‘behavioral traps’, had this post reached the people it needed to. How could this online forum have ensured that such an individual is reputable and trustworthy? How could this individual increase the trustworthiness of the piece of information he/she was sharing online? How could at-risk communities be informed about an emerging threat by an outlier? How could such an outlier be ‘intelligently’ validated through an automated classification and ranking system? This set of questions led me to explore the possibilities that heuristics, or rules of thumb, and networks create for informing individual risk perception and shaping decision making under uncertainty, which I later included in my thesis and served for my assessment on the role of eyewitnesses in spurring collective action during the COVID-19 pandemic titled: ‘Powering Social Media: Simple Guide for the Most Vulnerable to Make Emergencies Visible’.

Towards the end of my doctorate, and due to my growing interest in finding ways to efficiently collect and ‘intelligently’ rectify and validate individual risk perception for decision making, I audited ‘statistics’, ‘machine learning’, ‘algorithms’, and ‘artificial intelligence’ courses at the University of Queensland (UQ). Around that time, I was looking for a suitable location to test the hypotheses and limitations of the ideas I had in mind. After consulting with machine learning scholars in the U.S., I thought about designing a supervised machine learning application to help border agents detect high-risk travelers (note: I clearly understand such a project falls into the type of ‘social profiling’ and can further heighten social inequalities and indiscriminately target the most vulnerable, which is the reason why the European Union and many countries banned this type of artificial intelligence projects. However, my intent with this project is to further investigate not only the potentials but also the limits and risks of breakthrough discoveries and disruptive technology and how, I believe, they intersect with my specific research interests. The title of this proposal is ‘Detecting High Risk Threats and Improving Border Cross Experience with Machine Learning’.)

After the submission of my dissertation, UQ awarded me further scholarship to stay in Australia for another year, which made me the first UQ graduate student to be awarded with the Career Development Scholarship, so that I could continue pursuing alternative avenues to build bridges between the market and academia. I then joined UQ Ventures and, together with a doctoral candidate in the School of Engineering, co-founded a startup to help online marketplaces classify and rank reviews using Natural Language Processing to offer a better experience to their users. This enterprise attracted the attention of many engineering students from different programs across Queensland as well as CSIRO, which selected us as the first UQ startup to join their ON Prime accelerator program. CSIRO awarded us further monetary support after our team excelled in incorporating the design thinking principles, they had equipped us with, into testing and validating our ‘Minimum Viable Product’, or simple prototype. In the meantime, I had the privilege to meet many key stakeholders in the startup community in Brisbane and Sydney, including angel investors, venture capitalists, and decision makers like the then NSW’s Minister for Innovation, Science and Technology, the honorary Member of Parliament Matthew Kean. Unfortunately, this endeavor came to an abrupt ending when my co-founder and I realized that the timeline for funding this enterprise was not aligned with our family financial obligations once our scholarships expired. Nevertheless, the lessons from this transformational experience taught, and instilled in, me valuable soft skills, which I have since then applied in developing my project-, inquiry-based classes, as well as the way I approach and collaborate with my colleagues.

Finally, during the summer break of the Olympics in Tokyo, I spent most of my time sitting in a coffee shop trying to figure out whether there were any patterns that would help me explain and understand some of the most relevant and global political events occurring at that time. During this inquiry, I came across the work of Francis Heylighen and the provocative, and somewhat radical, book ‘Binding Chaos’ of Heather Marsh. Many of their research and propositions were quite original but it was the concept of ‘stigmergy’, which I had never heard of, that caught my attention. I then decided to conduct my own research on what stigmergy entailed and whether it would help me understand and, at least, explain some of the complexities I was witnessing around the globe. The more I explored the fundamentals of this ‘indirect coordination by autonomous agents in a mediated environment’, the more it helped me evaluate some of the contemporary social and political phenomena around me from a different and novel perspective. I have then started questioning whether it would be possible to replicate the autonomous and exploratory acts of ‘ants and termites’ on building and maintaining highly complex evolving systems by quickly responding and recovering from unexpected and massive environmental disturbances. This is when my epistemological -- and ontological -- interest for ‘human stigmergy’ was born and I became increasingly determined to explore its possibilities -- and limitations -- in explaining, predicting, and transforming our risk societies into resilient ones. The result of this inquiry led me to design the fundamentals of the ‘Stigmergy Network Theory’.