5 surprising insights from the science of successful learning

The work of Reda Sadki offers a provocative, often counter-intuitive critique of how we learn, lead, and solve complex problems.

Here are five surprising insights from his body of work.

1. Text is superior to video for learning

In an era where educational technology is obsessed with video content, immersive simulations, and flashy multimedia, Sadki argues for the humble written word.

He asserts that the push for multimedia is often a “deception” that confuses engagement with entertainment.

In Richard Mayer’s research on multimedia for learning actually proves text works better, Sadki re-examines the foundational science of instructional design.

He points out that multimedia often creates “cognitive waste” by forcing the brain to split attention between visual and auditory streams.

He argues that well-structured text is “cognitively quiet” and far better suited for the high-level critical thinking required in complex fields.

He doubles down on this in Against chocolate-covered broccoli: text-based alternatives to expensive multimedia content.

Here, he describes multimedia as an economic dead end.

He argues that text is not only cheaper and easier to update but also creates a more equitable learning environment for professionals in low-bandwidth settings.

2. Gamification is a “disaster” for humanitarian learning

While many organizations rush to “gamify” learning with badges, points, and leaderboards, Sadki calls this trend a “dead end.”

He argues that gamification is simply “lipstick on the pig of behaviorism,” a discredited theory that treats learners like rats in a maze responding to stimuli.

In Why gamification is a disaster for humanitarian learning, he makes a blistering case that games fail to model the complexity of the real world.

He points out that the dominant culture of video games often relies on violence and competition, which are antithetical to humanitarian values.

He argues that professionals facing life-and-death decisions need critical reasoning skills, not the artificial dopamine hits of a game.

3. Low completion rates can be a sign of success, not failure

In the world of online courses, a low completion rate is usually seen as a failure of design.

Sadki flips this metric on its head.

He suggests that in professional settings, “completion” is a vanity metric, part of the legacy of education systems that kept learners in closed environments.

In Online learning completion rates in context: Rethinking success in digital learning networks, he argues that busy professionals often engage with learning to solve a specific problem.

Once they find the solution, they leave.

This “drop-off” is actually efficient learning in action.

He warns that optimizing for completion often leads to dumbing down content rather than increasing its impact.

4. The “transparency paradox”: health workers are using AI in secret

One of Sadki’s most startling recent observations comes from his work with frontline health workers.

He reveals that professionals in the Global South are already using advanced Artificial Intelligence (AI) tools, but they are forced to hide this fact.

In Artificial intelligence, accountability, and authenticity: knowledge production and power in global health crisis, he describes a “transparency paradox.”

Global health systems are often punitive.

If a health worker admits to using AI to help draft a report or analyze data, their work is devalued as “inauthentic,” even if the quality is higher.

This forces innovation underground and prevents organizations from learning how to effectively partner with AI.

He expands on the solution in A global health framework for Artificial Intelligence as co-worker to support networked learning and local action, arguing that we must legitimize AI as a “co-worker” rather than a cheat.

5. Cascade training is mathematically doomed to fail

Finally, Sadki uses simple mathematics to dismantle one of the most common methods of training in the world: the “cascade” model, where experts train trainers, who train others.

In Why does cascade training fail?, he demonstrates that information loss at every level of the cascade is inevitable.

He argues that this model persists not because it works, but because it is convenient for hierarchical organizations.

He offers a stark alternative in Calculating the relative effectiveness of expert coaching, peer learning, and cascade training, where he proves that peer learning networks are the only model capable of scaling without losing quality.

Online learning completion rates in context: Rethinking success in digital learning networks

The comprehensive analysis of 221 Massive Open Online Courses (MOOCs) by Katy Jordan provides crucial insights for health professionals navigating the rapidly evolving landscape of digital learning. Her study, published in the International Review of Research in Open and Distributed Learning, examined completion rates across diverse platforms including Coursera, Open2Study, and others from 78 institutions. 

• With median completion rates of just 12.6% (ranging from 0.7% to 52.1%), traditional metrics may suggest disappointment. Jordan’s multiple regression analysis revealed that while total enrollments have decreased over time, completion rates have actually increased. 
• The data showed striking patterns in how participants engage, with the first and second weeks proving critical, after which the proportion of active students and those submitting assessments remains remarkably stable, with less than 3% difference between them. 
• The research challenges common assumptions about “lurking” as a participation strategy and provides compelling evidence that course design factors significantly impact learning outcomes. 

These findings reveal important patterns that can transform how we approach professional learning in global health contexts.

Beyond traditional completion metrics

For global health epidemiologists accustomed to face-to-face training with financial incentives and dedicated time away from work, these completion rates might initially appear appalling. In traditional capacity building programs, participants receive per diems, travel stipends, and paid time away from work. They are removed from their work environment, and their presence in the activities is often assumed to be evidence of both participation (often without any actual process metrics) and learning (with measurement often limited to “smile sheets” that measure sentiment or intent, not learning). Outcomes such as “completion” are rarely measured. Instead, attendance remains the key metric. In fact, completion rates are often confused with attendance. From this perspective, even the highest reported MOOC completion rate of 52.1% could be interpreted as a dismal failure.

However, this interpretation fundamentally misunderstands the different dynamics at play in digital learning environments. Unlike traditional training where external incentives and protected time create artificial conditions for participation, MOOCs operate in the reality of participants’ everyday professional lives. They typically do not require participants to stop work in order to learn, for example. The fact that up to half of enrollees in some courses complete them despite competing priorities, no financial incentives, and no dedicated work time represents remarkable commitment rather than failure.

What drives completion?

The accumulating evidence from MOOCs reveals three significant factors affecting completion:

The critical engagement period occurs within the first two weeks, after which participant behavior stabilizes.

This insight aligns with what emerging networked learning approaches have demonstrated in practice.

Rather than judging digital learning by metrics designed for classroom settings, we must recognize that participation patterns may reflect authentic integration with professional practice.

The measure of success should not necessarily be focused solely on how many complete the formal course. Rather, we should be considering how learning connects to real-world problem-solving and contributes to sustained professional networks.

Moving beyond MOOCs: peer learning networks

The Geneva Learning Foundation’s learning-to-action model offers a distinctly different model from conventional MOOCs. While MOOCs typically deliver standardized content to individual learners who progress independently, the Foundation’s digital learning initiatives are fundamentally network-based and practice-oriented. Rather than focusing on content consumption, their approach creates structured environments where health professionals connect, collaborate, and co-create knowledge while addressing real challenges in their work.

These learning networks differ from MOOCs in several key ways:

The Foundation’s experience with over 60,000 health professionals across 137 countries demonstrates that when learning is connected to practice through networked approaches, different metrics of success emerge:

• Knowledge application: Practitioners implement solutions directly in their contexts
• Network formation: Sustainable learning relationships develop beyond formal “courses”
• Knowledge creation: Participants contribute to collective understanding
• System impact: Changes cascade through health systems

Implications for global health training and learning

For epidemiologists and health professionals designing learning initiatives, these findings suggest several strategic shifts:

The future of professional learning, beyond completion rates

The research and practice point to a fundamental evolution in how we approach professional learning in global health. Rather than replicating traditional per diem-driven training models online, the most effective approaches harness the power of networks, enabling health professionals to learn continuously through structured peer interaction.

This perspective helps explain why seemingly low completion rates should not necessarily be viewed as failure. When digital learning is designed to create lasting networks of practice, knowledge emerges through collaborative action. Completion metrics therefore capture only a fraction of the impact.

For health systems facing complex challenges that include climate change, pandemic response, and health workforce shortages, this networked approach to learning offers a promising path forward—one that transforms how knowledge is created, shared, and applied to improve health outcomes globally.

Reference

• Jordan, K., 2015. Massive open online course completion rates revisited: Assessment, length and attrition. IRRODL 16. https://doi.org/10.19173/irrodl.v16i3.2112

Sculpture: The Geneva Learning Foundation Collection © 2025

#climateAndHealth #completionRates #learningMetrics #MOOCs #networkedLearning #onlineEducation #onlineLearning #professionalLearning

Interesting synopsis of how #netflix algorithms rate your shows by #completionrates from @neilhimself (who is being a tad quiet here in the #Fediverse camp)

https://www.tumblr.com/teledyn/749684887413456896/its-a-good-thing-they-did-because-neils-reply-is?source=share