Most graduate schools and research institutes genuinely want to support their early-career researchers. With limited budgets and high expectations, they curate catalogues of transferable skills courses from time management and academic writing to leadership and project planning. They collect feedback immediately after the workshop, but what many still overlook is that these lessons often fade even more quickly than the initial excitement after the workshop.
Without deliberate reinforcement, insights from even the best-designed training often evaporate just as the Ebbinghaus Forgetting Curve predicts. This steep, research-backed decline in memory retention explains why short-term formats rarely stick.
Training coordinators juggle faculty schedules, feedback scores, and program requirements, doing their best to equip doctoral candidates and postdocs for life beyond the bench. On the other side are the researchers themselves pressed for time, overwhelmed by competing responsibilities, and unsure how to carve out space for skill-building between grant deadlines and lab meetings. Many are motivated. They sign up for these workshops hoping for change: to feel more in control, less scattered, more confident.
But here’s the hard truth: short-term training formats, especially the classic one- or two-day workshops, do not deliver behavioural change. That’s not an opinion. It’s both a biological reality and a research-backed finding.
And when it comes to learning, why do we so often forget what we just learned? That’s where the Ebbinghaus Forgetting Curve comes in.
And Anna’s story is a perfect example.
Table Of Contents:
- Anna and the 2-Day Workshop That Wasn’t Enough To Make It Stick
- What the Research Tells Us: Short-Term Workshops Don’t Deliver Change
- Why the Ebbinghaus Forgetting Curve Still Matters
- What Actually Works: Repetition, Real-World Context, and Reflection
- From Awareness to Change: What Researchers Really Need
- References:
Anna and the 2-Day Workshop That Wasn’t Enough To Make It Stick
Anna, a late-stage PhD student, had reached that all-too-familiar point: experiments piling up, thesis writing looming, responsibilities multiplying. She was overwhelmed, torn between the guilt of unwritten chapters and the demands of day-to-day lab work. So when she saw a two-day workshop on time and project management, she signed up. Yes, she needed the training credits. But more than that, she hoped this would be the thing to finally get her on track.
The workshop itself was good. Well-designed, practical, and packed with techniques that made sense. The facilitator had everyone put together a personal action plan by the end. Anna felt hopeful, even a little excited. She knew what she wanted to change.
But by Wednesday morning, she was back in the lab, and reality didn’t pause.
Her bench was full of experiments waiting to be rescued from neglect. During the workshop, she’d already been ducking out between breaks to check cultures, trying to keep her experiments from sliding. Now, there was no more room for catch-up. She had to hit the ground running. She told herself, “I’ll start implementing the plan on Monday.“
Then came the email: her supervisor needed her to present at the journal club. Thursday. Cue frantic prep. The action plan? Postponed. “I’ll start next week,” she promised herself. But next week brought more backlog. More obligations. The plan quietly slid into the “someday” tray next to the paper she meant to read and the “new system” she’d sworn she’d set up last month.
The problem wasn’t Anna. It wasn’t the workshop, either.
It was the mismatch between the expectations Anna had and what a short-format training could realistically deliver.
What the Research Tells Us: Short-Term Workshops Don’t Deliver Change
Anna’s story isn’t just a personal anecdote; it’s a case study in a broader pattern backed by research. In a revealing study published in PNAS in 2017, Feldon and colleagues examined the impact of boot camps and short-format training programs for PhD students in the life sciences. These were the kinds of training formats many graduate schools invest in with the best of intentions: intensive, expert-led, tightly packed workshops aimed at building essential research and productivity skills.
However, the findings were stark: there was no measurable improvement in participants’ actual research design or execution skills. Despite investing time, energy, and institutional resources, the outcomes didn’t shift. The paper’s title, “Null Effects of Boot Camps and Short-Format Training for PhD Students”, says it all.
This is exactly what Anna experienced. She walked away with a plan. She was engaged. She wanted change. But a few days later, she couldn’t remember half of what she’d learned, and the urgent needs of her research pulled her back into old patterns.
So why does this happen?
Part of the equation lies in the Ebbinghaus Forgetting Curve, a well-established phenomenon in memory science that shows how quickly new knowledge fades if it’s not reinforced. And that’s what we’ll unpack next.
Why the Ebbinghaus Forgetting Curve Still Matters
To understand why short-term trainings so often fail to produce lasting change, we need to take a closer look at how quickly we forget what we learn. First formulated by German psychologist Hermann Ebbinghaus in 1885, this curve maps how quickly the human brain forgets newly learned information. His experiments, painstakingly conducted on himself, involved memorising lists of meaningless syllables, such as “BOK” and “DAX,” and then tracking how long he could retain them over hours, days, and weeks.
What he found was striking: memory loss happens fast. Within just 24 hours, a significant portion of new information is forgotten. Without any reinforcement, the rate of forgetting accelerates, then gradually tapers off. This pattern, plotted as a steep downward curve, became known as the Ebbinghaus Forgetting Curve.
Despite being more than a century old, Ebbinghaus’s findings have stood the test of time. His forgetting curve has been replicated in modern cognitive science multiple times. And it has become a foundational concept in the science of learning and memory retention.
Still, not everyone has readily accepted it.
Some critics have taken issue with Ebbinghaus’s methodology. For one, he was his own sole test subject, raising questions of bias. He also used nonsensical syllables instead of meaningful content, which has prompted some to argue that his conclusions lack real-world relevance. Nick Shackleton-Jones, for example, argues that learning is deeply emotional, that we remember what we care about. According to this “Affective Context Theory,” Ebbinghaus’s approach amounted to psychological force-feeding, focusing on memorisation without context.
But here’s the thing: these critiques, while worth noting, don’t dismantle the core insight. Modern studies, such as those replicated by Jaap Murre and Joeri Dros, have reaffirmed Ebbinghaus’s results, even when using more meaningful materials, like poetry. Memory still fades unless it is actively recalled and reinforced.
This makes the Ebbinghaus Forgetting Curve not only valid but essential for anyone involved in designing or attending training programs. Because if your training design is not accounting for how rapidly information decays, you’re setting participants up for a very human kind of failure.
And that’s exactly what Anna encountered. She didn’t forget because she wasn’t committed. She forgot because she’s human. Because life happened. And because the structure of the training didn’t provide her with the follow-up, reinforcement, or reflection time needed to retain and apply what she’d learned.
What Actually Works: Repetition, Real-World Context, and Reflection
Let’s go back to Anna. Because this time, instead of a two-day crash course, she signs up for something very different: Fast Forward – a structured, seven-week program focused on project management and personal productivity. It’s not an information download, it’s a guided process.
Each week, Anna dives into a single topic. She learns a specific set of techniques, applies it to her current workload, and reflects on the outcome. There are check-ins with peers, facilitated discussions during sessions, and assignments that receive personal feedback from trainers, tutors, and peers, not just a check mark for submission, but guidance on how to improve. It’s intense, but she’s also not alone. She’s learning alongside others, navigating the same academic pressures, some of whom are slightly ahead in their careers. That peer insight? Invaluable. It normalises the struggle and broadens her toolbox.
Importantly, this isn’t a one-off event. It’s a rhythm. A habit-forming cadence of learning, applying, reflecting, and sharing. Those same concepts that would have been covered in a whirlwind two-day workshop? Here, they’re spaced out deliberately, repeated in different contexts, and tied directly to Anna’s actual work.
By the end of seven weeks, Anna isn’t “done.” But she’s changed.
She’s seen what works for her and what doesn’t. She’s tested tools against the real messiness of lab life. And, perhaps most importantly, she has developed a support network of peers who share the same language of burnout, deadlines, and trying to stay afloat in academia.
This is what effective training looks like when you take the Ebbinghaus Forgetting Curve seriously. It’s designed not just for knowledge delivery, but for retention and behavioural change. That means:
- Spaced repetition: revisiting concepts over time instead of cramming them into one session.
- Real-life application: techniques aren’t just discussed, they’re implemented immediately in participants’ ongoing projects.
- Peer learning: shared experiences reinforce understanding and accountability.
- Feedback and reflection: every step includes structured time to think, question, and adapt.
That’s the difference between “feeling inspired” and actually changing how you work.
And for graduate schools or research institutes serious about making their training programs effective, this kind of format isn’t a luxury; it’s a necessity.
From Awareness to Change: What Researchers Really Need
Too often, short-format workshops are designed as if the learning process ends when the Zoom call concludes or the flipchart is rolled up. But real change, especially for time-pressed researchers, isn’t sparked by a single burst of insight. It’s sustained through structure, reinforcement, and relevance.
That’s precisely why our training programs are different.
They’re grounded in adult learning psychology and the science of behavioural change. Every element is purposeful, from the pacing to the peer exchanges to the reflective assignments. We’ve designed these programs to maximise the odds that what’s learned becomes what’s lived.
We incorporate essential principles, such as the Ebbinghaus Forgetting Curve, not just to inform our teaching, but also to design against it. Because if we know that forgetting is inevitable without reinforcement, then reinforcement must be part of the plan, not an afterthought.
And for researchers like Anna and many others, who juggle a thousand things, we’ve seen what a difference that makes.
If you’re a training coordinator, program lead, or research group head seeking a more effective way to support your early-career researchers, we’d be delighted to discuss.
Explore how our structured, long-form training formats, like our 7-week Fast-Forward Project Management and Personal Productivity program or our 9-week Resilience Training for Researchers, can actually deliver the change your researchers need.
Book a call today to discuss how we can tailor a solution that fits your institution’s goals and researchers’ real-world needs.
References:
Ebbinghaus, H. (1913). Memory: A Contribution to Experimental Psychology (H. A. Ruger & C. E. Bussenius, Trans.). Teachers College, Columbia University. (Original work published 1885)
Feldon, D. F., Jeong, S., Peugh, J., Roksa, J., Maahs-Fladung, C., Shenoy, A., & Oliva, M. (2017). Null effects of boot camps and short-format training for PhD students in life sciences. Proceedings of the National Academy of Sciences, 114(37), 9854–9858. https://doi.org/10.1073/pnas.1705783114
Murre, J. M. J., & Dros, J. (2015). Replication and analysis of Ebbinghaus’ forgetting curve. PLOS ONE, 10(7), e0120644. https://doi.org/10.1371/journal.pone.0120644
Shackleton-Jones, N. (2019). How People Learn: Designing Education and Training That Works to Improve Performance. Kogan Page.
Dr. Nadine Sinclair
Nadine is a trusted advisor to corporate and academic leaders and one of the Managing Directors of Mind Matters. Before embarking on her entrepreneurial journey, she was a project manager with McKinsey & Company. A scientist by training and at heart, she conducted her doctoral research at the Max Planck Institute for Biophysical Chemistry. Nadine brings close to 30,000 hours of experience in managing projects for research institutions, research foundations, pharmaceutical and biotech companies (including many Fortune 500) and governments. She continues to build her expertise with over 1,000 hours of project management each year. As a neuro leadership expert, she bridges the gap between science and business practices, leveraging the latest insights from neuroscience and behavioural economics to create breakthroughs for her clients.
