#learningculture — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #learningculture, aggregated by home.social.
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neu auf #GadgetGedanken : 3T1G-15 Learn Today or Fade Away
Learn today or fade away: Why the ‚Busy Trap‘ kills innovation and how sharing knowledge builds vital reserves for the future. #3T1G
https://www.gadgetgedanken.de/2026/05/3t1g-15-learn-today-or-fade-away/
#3T1G #AI #BusyTrap #Collaboration #DigitalTransformation #Efficiency #FutureOfWork #KnowledgeSharing #Leadership #LearningCulture #Performance #ProfessionalGrowth #Reskilling #WorkCulture #WorkingOutLoud
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neu auf #GadgetGedanken : 3T1G-15 Learn Today or Fade Away
Learn today or fade away: Why the ‚Busy Trap‘ kills innovation and how sharing knowledge builds vital reserves for the future. #3T1G
https://www.gadgetgedanken.de/2026/05/3t1g-15-learn-today-or-fade-away/
#3T1G #AI #BusyTrap #Collaboration #DigitalTransformation #Efficiency #FutureOfWork #KnowledgeSharing #Leadership #LearningCulture #Performance #ProfessionalGrowth #Reskilling #WorkCulture #WorkingOutLoud
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neu auf #GadgetGedanken : 3T1G-15 Learn Today or Fade Away
Learn today or fade away: Why the ‚Busy Trap‘ kills innovation and how sharing knowledge builds vital reserves for the future. #3T1G
https://www.gadgetgedanken.de/2026/05/3t1g-15-learn-today-or-fade-away/
#3T1G #AI #BusyTrap #Collaboration #DigitalTransformation #Efficiency #FutureOfWork #KnowledgeSharing #Leadership #LearningCulture #Performance #ProfessionalGrowth #Reskilling #WorkCulture #WorkingOutLoud
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neu auf #GadgetGedanken : 3T1G-15 Learn Today or Fade Away
Learn today or fade away: Why the ‚Busy Trap‘ kills innovation and how sharing knowledge builds vital reserves for the future. #3T1G
https://www.gadgetgedanken.de/2026/05/3t1g-15-learn-today-or-fade-away/
#3T1G #AI #BusyTrap #Collaboration #DigitalTransformation #Efficiency #FutureOfWork #KnowledgeSharing #Leadership #LearningCulture #Performance #ProfessionalGrowth #Reskilling #WorkCulture #WorkingOutLoud
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neu auf #GadgetGedanken : 3T1G-15 Learn Today or Fade Away
Learn today or fade away: Why the ‚Busy Trap‘ kills innovation and how sharing knowledge builds vital reserves for the future. #3T1G
https://www.gadgetgedanken.de/2026/05/3t1g-15-learn-today-or-fade-away/
#3T1G #AI #BusyTrap #Collaboration #DigitalTransformation #Efficiency #FutureOfWork #KnowledgeSharing #Leadership #LearningCulture #Performance #ProfessionalGrowth #Reskilling #WorkCulture #WorkingOutLoud
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https://www.europesays.com/people/34555/ Quote of the day by Microsoft CEO Satya Nadella: ‘Success can cause people to unlearn the habits that…’ #ContinuousImprovement #EmployeeDiscipline #LeadershipStrategies #LearningCulture #Microsoft #OrganizationalBehavior #ProfessionalGrowth #SatyaNadella #SatyaNadellaQuotes #SuccessHabits
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Curiosity sharpens leaders. Comfort dulls skill. #leadership #mindset #growth #careers #learningculture #workethic #professionaldevelopment
https://stayingalive.in/thought-of-the-day/still-learning-still-moving.html -
Just published a revised account of how I used Deep Listening to start up the talk on improvisation and Joint Activity during incidents, at SRECon23 Americas.
This was on the Learning From Incidents website, but it is gone. So I updated and expanded my story.
#SRE #IncidentResponse #JointActivity #Improvisation #AdaptiveCapacity #Resilience #Reliability #SRECon #LearningCulture
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Just published a revised account of how I used Deep Listening to start up the talk on improvisation and Joint Activity during incidents, at SRECon23 Americas.
This was on the Learning From Incidents website, but it is gone. So I updated and expanded my story.
#SRE #IncidentResponse #JointActivity #Improvisation #AdaptiveCapacity #Resilience #Reliability #SRECon #LearningCulture
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Just published a revised account of how I used Deep Listening to start up the talk on improvisation and Joint Activity during incidents, at SRECon23 Americas.
This was on the Learning From Incidents website, but it is gone. So I updated and expanded my story.
#SRE #IncidentResponse #JointActivity #Improvisation #AdaptiveCapacity #Resilience #Reliability #SRECon #LearningCulture
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Just published a revised account of how I used Deep Listening to start up the talk on improvisation and Joint Activity during incidents, at SRECon23 Americas.
This was on the Learning From Incidents website, but it is gone. So I updated and expanded my story.
#SRE #IncidentResponse #JointActivity #Improvisation #AdaptiveCapacity #Resilience #Reliability #SRECon #LearningCulture
-
Just published a revised account of how I used Deep Listening to start up the talk on improvisation and Joint Activity during incidents, at SRECon23 Americas.
This was on the Learning From Incidents website, but it is gone. So I updated and expanded my story.
#SRE #IncidentResponse #JointActivity #Improvisation #AdaptiveCapacity #Resilience #Reliability #SRECon #LearningCulture
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Comparative analysis of workforce development models in the global malaria elimination agenda
The stagnation in global malaria mortality reduction has forced a re-evaluation of the tools and strategies currently deployed in high-burden countries.
While biological challenges such as insecticide resistance and parasite mutations are well-documented, a critical bottleneck remains the capacity of the human workforce to implement technical strategies with precision.
The transition from control to elimination requires a fundamental shift in workforce development.
It demands moving beyond the passive transmission of technical knowledge toward models that recognize the value of the health worker.
People who work for health, especially those who engage directly with communities, are likely to possess unique insights into local transmission dynamics and community behavior.
This analysis reviews four predominant capacity-building architectures currently active in the malaria landscape.
These initiatives are assessed based on their ability to scale to the district and community levels, their cost-effectiveness, and their capacity to validate and utilize the tacit knowledge held by local staff.
Malaria learning model 1. The academic massive open online course model
The most prominent example of the digital transmission model is the MalariaX series offered by Harvard University.
This initiative utilizes the Massive Open Online Course (MOOC) format to democratize access to high-level scientific knowledge.
Strengths
The primary strength of this model is the unparalleled quality of its technical content.
It provides participants in low-resource settings with direct access to global experts and the latest scientific evidence regarding vector biology, epidemiology, and immunology.
The digital format allows for infinite scalability in terms of access.
Anyone with an internet connection can technically access the material.
This eliminates the geographical barriers that often exclude peripheral health workers from elite training.
Limitations
The model suffers from the “know-do” gap.
While it effectively transmits theoretical knowledge, it lacks a structural mechanism to ensure this knowledge is applied to local realities.
The pedagogy relies heavily on passive consumption of video lectures which reinforces the hierarchy of “expert” versus “learner.”
It fails to account for the specific needs of local health workers who must adapt global scientific principles to context-specific challenges, such as unexpected climate shifts or community resistance.
The assessment mechanisms verify knowledge retention rather than the ability to navigate these local complexities.
Consequently, it undervalues the learner’s own experience and offers no channel for the “global expert” to learn from the “local expert” who is managing the disease daily.
Malaria learning model 2. The normative cascade training model
The World Health Organization (WHO) and national malaria programs typically rely on the cascade model to disseminate new guidelines.
This approach involves training a core group of master trainers at the national level who then train regional officers, who in turn train district and facility staff.
Strengths
This model ensures strong alignment with national policy and global normative guidance.
It maintains a clear chain of command and reinforces the authority of the Ministry of Health.
It is particularly effective for standardization, such as ensuring that a specific treatment protocol for severe malaria is introduced uniformly across the health system.
Weaknesses
The cascade model is plagued by the dilution of quality as training moves down the chain.
Information is frequently distorted or simplified by the time it reaches the community health worker.
Structurally, it treats the health worker as a passive vessel to be filled with instructions rather than a thinking professional who understands the local ecosystem.
It is also prohibitively expensive and logistically heavy.
It often relies on per diems that distort participant motivation and create a “training aristocracy” where access is determined by seniority rather than need.
Crucially, this model often interprets local adaptation as non-compliance.
It fails to recognize that frontline workers often deviate from protocols not out of ignorance but out of necessity, driven by supply chain ruptures or specific community demands that only they understand.
Malaria learning model 3. The fellowship model
Initiatives such as the African Leadership and Management Training for Impact in Malaria Eradication (ALAMIME) represent the fellowship model.
These programs target high-potential program managers for intensive, long-term leadership development, often in partnership with universities.
Strengths
This model addresses the critical “soft skills” gap identified in malaria elimination policy reviews.
It moves beyond technical biology to teach management, advocacy, and financial planning.
By focusing on African leadership, it actively works to decolonize the expertise hierarchy and fosters strong regional ownership.
The cohort-based approach builds deep professional bonds among future leaders of national malaria programs.
Weaknesses
The fundamental limitation is scalability and exclusivity.
These programs are resource-intensive and reach a small number of individuals per year.
While they produce high-quality leaders at the top, they cannot reach the critical mass of district and community personnel required to execute malaria strategies.
This reinforces a top-heavy leadership structure that ignores the need for “micro-leadership” at the facility level.
It overlooks the reality that a district nurse or community health worker must also exercise leadership and diplomacy every day to secure community trust.
By focusing on the elite, this model inadvertently devalues the significance of the leadership required at the last mile.
Malaria learning model 4. The field epidemiology training program model
The Field Epidemiology Training Program (FETP) functions as a learning-by-doing apprenticeship.
Residents work within the health system to investigate outbreaks and analyze surveillance data under the mentorship of experienced epidemiologists.
Strengths
This model closely aligns learning with work.
It is an “applied” model where the output of the training is often a tangible public health product.
It effectively builds data literacy and analytical capacity.
It grounds the learner in the reality of the field rather than the theory of the classroom.
Weaknesses
Like the fellowship model, the FETP is difficult to scale due to the requirement for intense, one-on-one mentorship.
It is a high-cost intervention per learner.
Furthermore, the rigorous focus on surveillance and epidemiology often overshadows the operational implementation challenges faced by generalist health workers.
While it produces excellent surveillance officers, it does not necessarily equip the broader workforce to utilize their own data for local decision-making.
It often extracts data for central analysis rather than empowering local staff to interpret the trends they witness daily.
This failure to devolve analytical power ignores the fact that local workers are often the first to notice anomalies, such as climate-driven shifts in vector behavior, long before they appear in national databases.
Four recommendations to strengthen malaria learning and capacity-building
The current landscape of malaria capacity building reveals a functional and epistemic schism.
The academic and normative models excel at defining what needs to be done but fail to support the workforce in how to do it within their specific constraints.
The fellowship and apprenticeship models build deep capacity but are structurally incapable of reaching the volume of workers necessary for elimination.
A significant gap exists for a model that combines the scalability of digital platforms with the implementation rigor of the apprenticeship approach.
To achieve malaria elimination, future initiatives need to:
- Move beyond knowledge verification to value validation.
- Recognize that local health workers are not the problem to be fixed but the owners of the solution.
- Utilize the existing workforce rather than parallel structures.
- Replace financial incentives with the professional motivation that comes from having one’s local knowledge recognized and used to solve the problems they face every day.
References
General context & the “know-do” gap
- Mwenesi, H., Mbogo, C., Casamitjana, N., Castro, M. C., Itoe, M. A., Okonofua, F., & Tanner, M. (2022). Rethinking human resources and capacity building needs for malaria control and elimination in Africa. PLOS Global Public Health, 2(5), e0000210.
https://doi.org/10.1371/journal.pgph.0000210 - World Health Organization. (2016). Global Technical Strategy for Malaria 2016–2030. Geneva: World Health Organization.
https://www.who.int/docs/default-source/documents/global-technical-strategy-for-malaria-2016-2030.pdf
Model 1: The academic MOOC model (MalariaX)
- Harvard University. MalariaX: Defeating Malaria from the Genes to the Globe. Harvard Online.
https://www.harvardonline.harvard.edu/course/malariax-defeating-malaria-genes-globe - Wirth, D. F., Casamitjana, N., Tanner, M., & Reich, M. R. (2018). Global action for training in malaria elimination. Malaria Journal, 17(1), 51.
https://doi.org/10.1186/s12936-018-2199-3
Model 2: The normative cascade model and incentives
- Dambisya, Y. M., & Matinhure, S. (2012). Policy Brief: Perceptions of per diems in the health sector: Evidence and implications. U4 Anti-Corruption Resource Centre.
https://www.cmi.no/publications/file/4082-perceptions-of-per-diems-in-the-health-sector.pdf - Maes, K., 2012. Volunteerism or Labor Exploitation? Harnessing the Volunteer Spirit to Sustain AIDS Treatment Programs in Urban Ethiopia. Human Organization 71, 54–64. https://doi.org/10.17730/humo.71.1.axm39467485m22w4
Model 3: The fellowship model (ALAMIME)
- ALAMIME. African Leadership and Management Training for Impact in Malaria Eradication. Makerere University School of Public Health.
https://alamime.musph.ac.ug/ - Couper, I., Ray, S., Blaauw, D., et al. (2018). Curriculum and training needs of mid-level health workers in Africa: a situational review from Kenya, Nigeria, South Africa and Uganda. BMC Health Services Research, 18(1), 553.
https://doi.org/10.1186/s12913-018-3362-9
Model 4: The Field Epidemiology Training Program (FETP)
- Centers for Disease Control and Prevention (CDC). Education and Training | Parasites.
https://www.cdc.gov/parasites/education_training/education-training.html - Neta, G., Brownson, R. C., & Chambers, D. A. (2018). Opportunities for Epidemiologists in Implementation Science: A Primer. American Journal of Epidemiology, 187(5), 899–910.
https://doi.org/10.1093/aje/kwx323
Strategic recommendations and value validation
- The Geneva Learning Foundation. (2024). Teach to Reach 10: Over 21,000 Health Workers Unite To Tackle Climate and Immunization Challenges. Health Policy Watch.
https://healthpolicy-watch.news/teach-to-reach-10-over-21000-health-workers-unite-to-tackle-climate-and-immunization-challenges/ - Sadki, R. (2025). When funding shrinks, impact must grow: the economic case for peer learning networks.
https://doi.org/10.59350/redasadki.20995
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Comparative analysis of workforce development models in the global malaria elimination agenda
The stagnation in global malaria mortality reduction has forced a re-evaluation of the tools and strategies currently deployed in high-burden countries.
While biological challenges such as insecticide resistance and parasite mutations are well-documented, a critical bottleneck remains the capacity of the human workforce to implement technical strategies with precision.
The transition from control to elimination requires a fundamental shift in workforce development.
It demands moving beyond the passive transmission of technical knowledge toward models that recognize the value of the health worker.
People who work for health, especially those who engage directly with communities, are likely to possess unique insights into local transmission dynamics and community behavior.
This analysis reviews four predominant capacity-building architectures currently active in the malaria landscape.
These initiatives are assessed based on their ability to scale to the district and community levels, their cost-effectiveness, and their capacity to validate and utilize the tacit knowledge held by local staff.
Malaria learning model 1. The academic massive open online course model
The most prominent example of the digital transmission model is the MalariaX series offered by Harvard University.
This initiative utilizes the Massive Open Online Course (MOOC) format to democratize access to high-level scientific knowledge.
Strengths
The primary strength of this model is the unparalleled quality of its technical content.
It provides participants in low-resource settings with direct access to global experts and the latest scientific evidence regarding vector biology, epidemiology, and immunology.
The digital format allows for infinite scalability in terms of access.
Anyone with an internet connection can technically access the material.
This eliminates the geographical barriers that often exclude peripheral health workers from elite training.
Limitations
The model suffers from the “know-do” gap.
While it effectively transmits theoretical knowledge, it lacks a structural mechanism to ensure this knowledge is applied to local realities.
The pedagogy relies heavily on passive consumption of video lectures which reinforces the hierarchy of “expert” versus “learner.”
It fails to account for the specific needs of local health workers who must adapt global scientific principles to context-specific challenges, such as unexpected climate shifts or community resistance.
The assessment mechanisms verify knowledge retention rather than the ability to navigate these local complexities.
Consequently, it undervalues the learner’s own experience and offers no channel for the “global expert” to learn from the “local expert” who is managing the disease daily.
Malaria learning model 2. The normative cascade training model
The World Health Organization (WHO) and national malaria programs typically rely on the cascade model to disseminate new guidelines.
This approach involves training a core group of master trainers at the national level who then train regional officers, who in turn train district and facility staff.
Strengths
This model ensures strong alignment with national policy and global normative guidance.
It maintains a clear chain of command and reinforces the authority of the Ministry of Health.
It is particularly effective for standardization, such as ensuring that a specific treatment protocol for severe malaria is introduced uniformly across the health system.
Weaknesses
The cascade model is plagued by the dilution of quality as training moves down the chain.
Information is frequently distorted or simplified by the time it reaches the community health worker.
Structurally, it treats the health worker as a passive vessel to be filled with instructions rather than a thinking professional who understands the local ecosystem.
It is also prohibitively expensive and logistically heavy.
It often relies on per diems that distort participant motivation and create a “training aristocracy” where access is determined by seniority rather than need.
Crucially, this model often interprets local adaptation as non-compliance.
It fails to recognize that frontline workers often deviate from protocols not out of ignorance but out of necessity, driven by supply chain ruptures or specific community demands that only they understand.
Malaria learning model 3. The fellowship model
Initiatives such as the African Leadership and Management Training for Impact in Malaria Eradication (ALAMIME) represent the fellowship model.
These programs target high-potential program managers for intensive, long-term leadership development, often in partnership with universities.
Strengths
This model addresses the critical “soft skills” gap identified in malaria elimination policy reviews.
It moves beyond technical biology to teach management, advocacy, and financial planning.
By focusing on African leadership, it actively works to decolonize the expertise hierarchy and fosters strong regional ownership.
The cohort-based approach builds deep professional bonds among future leaders of national malaria programs.
Weaknesses
The fundamental limitation is scalability and exclusivity.
These programs are resource-intensive and reach a small number of individuals per year.
While they produce high-quality leaders at the top, they cannot reach the critical mass of district and community personnel required to execute malaria strategies.
This reinforces a top-heavy leadership structure that ignores the need for “micro-leadership” at the facility level.
It overlooks the reality that a district nurse or community health worker must also exercise leadership and diplomacy every day to secure community trust.
By focusing on the elite, this model inadvertently devalues the significance of the leadership required at the last mile.
Malaria learning model 4. The field epidemiology training program model
The Field Epidemiology Training Program (FETP) functions as a learning-by-doing apprenticeship.
Residents work within the health system to investigate outbreaks and analyze surveillance data under the mentorship of experienced epidemiologists.
Strengths
This model closely aligns learning with work.
It is an “applied” model where the output of the training is often a tangible public health product.
It effectively builds data literacy and analytical capacity.
It grounds the learner in the reality of the field rather than the theory of the classroom.
Weaknesses
Like the fellowship model, the FETP is difficult to scale due to the requirement for intense, one-on-one mentorship.
It is a high-cost intervention per learner.
Furthermore, the rigorous focus on surveillance and epidemiology often overshadows the operational implementation challenges faced by generalist health workers.
While it produces excellent surveillance officers, it does not necessarily equip the broader workforce to utilize their own data for local decision-making.
It often extracts data for central analysis rather than empowering local staff to interpret the trends they witness daily.
This failure to devolve analytical power ignores the fact that local workers are often the first to notice anomalies, such as climate-driven shifts in vector behavior, long before they appear in national databases.
Four recommendations to strengthen malaria learning and capacity-building
The current landscape of malaria capacity building reveals a functional and epistemic schism.
The academic and normative models excel at defining what needs to be done but fail to support the workforce in how to do it within their specific constraints.
The fellowship and apprenticeship models build deep capacity but are structurally incapable of reaching the volume of workers necessary for elimination.
A significant gap exists for a model that combines the scalability of digital platforms with the implementation rigor of the apprenticeship approach.
To achieve malaria elimination, future initiatives need to:
- Move beyond knowledge verification to value validation.
- Recognize that local health workers are not the problem to be fixed but the owners of the solution.
- Utilize the existing workforce rather than parallel structures.
- Replace financial incentives with the professional motivation that comes from having one’s local knowledge recognized and used to solve the problems they face every day.
References
General context & the “know-do” gap
- Mwenesi, H., Mbogo, C., Casamitjana, N., Castro, M. C., Itoe, M. A., Okonofua, F., & Tanner, M. (2022). Rethinking human resources and capacity building needs for malaria control and elimination in Africa. PLOS Global Public Health, 2(5), e0000210.
https://doi.org/10.1371/journal.pgph.0000210 - World Health Organization. (2016). Global Technical Strategy for Malaria 2016–2030. Geneva: World Health Organization.
https://www.who.int/docs/default-source/documents/global-technical-strategy-for-malaria-2016-2030.pdf
Model 1: The academic MOOC model (MalariaX)
- Harvard University. MalariaX: Defeating Malaria from the Genes to the Globe. Harvard Online.
https://www.harvardonline.harvard.edu/course/malariax-defeating-malaria-genes-globe - Wirth, D. F., Casamitjana, N., Tanner, M., & Reich, M. R. (2018). Global action for training in malaria elimination. Malaria Journal, 17(1), 51.
https://doi.org/10.1186/s12936-018-2199-3
Model 2: The normative cascade model and incentives
- Dambisya, Y. M., & Matinhure, S. (2012). Policy Brief: Perceptions of per diems in the health sector: Evidence and implications. U4 Anti-Corruption Resource Centre.
https://www.cmi.no/publications/file/4082-perceptions-of-per-diems-in-the-health-sector.pdf - Maes, K., 2012. Volunteerism or Labor Exploitation? Harnessing the Volunteer Spirit to Sustain AIDS Treatment Programs in Urban Ethiopia. Human Organization 71, 54–64. https://doi.org/10.17730/humo.71.1.axm39467485m22w4
Model 3: The fellowship model (ALAMIME)
- ALAMIME. African Leadership and Management Training for Impact in Malaria Eradication. Makerere University School of Public Health.
https://alamime.musph.ac.ug/ - Couper, I., Ray, S., Blaauw, D., et al. (2018). Curriculum and training needs of mid-level health workers in Africa: a situational review from Kenya, Nigeria, South Africa and Uganda. BMC Health Services Research, 18(1), 553.
https://doi.org/10.1186/s12913-018-3362-9
Model 4: The Field Epidemiology Training Program (FETP)
- Centers for Disease Control and Prevention (CDC). Education and Training | Parasites.
https://www.cdc.gov/parasites/education_training/education-training.html - Neta, G., Brownson, R. C., & Chambers, D. A. (2018). Opportunities for Epidemiologists in Implementation Science: A Primer. American Journal of Epidemiology, 187(5), 899–910.
https://doi.org/10.1093/aje/kwx323
Strategic recommendations and value validation
- The Geneva Learning Foundation. (2024). Teach to Reach 10: Over 21,000 Health Workers Unite To Tackle Climate and Immunization Challenges. Health Policy Watch.
https://healthpolicy-watch.news/teach-to-reach-10-over-21000-health-workers-unite-to-tackle-climate-and-immunization-challenges/ - Sadki, R. (2025). When funding shrinks, impact must grow: the economic case for peer learning networks.
https://doi.org/10.59350/redasadki.20995
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We want growth. We avoid the discomfort that builds it. This tension shapes our path. #Leadership #Growth #Mindset #SelfAwareness #CareerGrowth #LearningCulture #ProfessionalGrowth #LeadershipDevelopment #CareerBuilding #SkillsMatter
https://medium.com/@mohindroo.sanjay66/the-hard-truth-about-growth-d6671d9fc2ad -
Văn hoá học tập là “chìa khóa” giúp ROX Group duy trì tăng trưởng bền vững, đoạt danh hiệu “Nơi làm việc tốt nhất Việt Nam” và “Doanh nghiệp xuất sắc châu Á”. 🚀📚 #ROXGroup #VanHoaHocTap #PhatTrienBenVung #LearningCulture #SustainableGrowth #Vietnam #Asia #TopWorkplace #DoanhNghiepXuatSac #NơiLamViecTotNhat
https://vietnamnet.vn/van-hoa-hoc-tap-chia-khoa-giup-rox-group-phat-trien-ben-vung-2464856.html
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Upskilling for emerging tech isn’t a future problem. It’s your job today. #Upskilling #EmergingTech #CIOLeadership #LearningCulture #TechReadiness #FutureOfWork #DigitalTransformation #SkillsAreStrategy #AlwaysLearning #TechLeadership
https://medium.com/@sanjay.mohindroo66/upskilling-for-emerging-tech-a-leaders-playbook-d145c4a54293 -
Upskilling for emerging tech isn’t a future problem. It’s your job today. #Upskilling #EmergingTech #CIOLeadership #LearningCulture #TechReadiness #FutureOfWork #DigitalTransformation #SkillsAreStrategy #AlwaysLearning #TechLeadership
https://medium.com/@sanjay.mohindroo66/upskilling-for-emerging-tech-a-leaders-playbook-d145c4a54293 -
Reverse mentorship isn’t a trend. It’s the smartest move you’ll make this year. #ReverseMentorship #GenZTechnologists #LeadershipShift #TechLeadership #FutureOfWork #InnovationCulture #ListenToGenZ #LearningCulture #BeginnerMindset #ModernWorkplace
https://medium.com/@sanjay.mohindroo66/reverse-mentorship-why-gen-z-is-the-teacher-you-didnt-know-you-needed-4c4180ffdccd -
Reverse mentorship isn’t a trend. It’s the smartest move you’ll make this year. #ReverseMentorship #GenZTechnologists #LeadershipShift #TechLeadership #FutureOfWork #InnovationCulture #ListenToGenZ #LearningCulture #BeginnerMindset #ModernWorkplace
https://medium.com/@sanjay.mohindroo66/reverse-mentorship-why-gen-z-is-the-teacher-you-didnt-know-you-needed-4c4180ffdccd -
Learning isn’t a checkbox—it’s a culture. Good leaders fuel curiosity. Weak leaders hand out carrots and wonder why the hamsters quit. 🐹🔥
Which kind are you working for?#LeadershipDevelopment #LearningCulture #IntrinsicMotivation #WorkplaceCulture #LeadBoldly #LeadershipStyles
http://leadboldly1.blog/2025/09/23/learning-isnt-a-checklist-its-a-culture/
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Upskilling for emerging tech isn’t a future problem. It’s your job today. #Upskilling #EmergingTech #CIOLeadership #LearningCulture #TechReadiness #FutureOfWork #DigitalTransformation #SkillsAreStrategy #AlwaysLearning #TechLeadership
https://medium.com/@sanjay.mohindroo66/upskilling-for-emerging-tech-a-leaders-playbook-d145c4a54293 -
Reverse mentorship isn’t a trend. It’s the smartest move you’ll make this year. #ReverseMentorship #GenZTechnologists #LeadershipShift #TechLeadership #FutureOfWork #InnovationCulture #ListenToGenZ #LearningCulture #BeginnerMindset #ModernWorkplace
https://medium.com/@sanjay.mohindroo66/reverse-mentorship-why-gen-z-is-the-teacher-you-didnt-know-you-needed-4c4180ffdccd -
Reverse mentorship isn’t a trend. It’s the smartest move you’ll make this year. #ReverseMentorship #GenZTechnologists #LeadershipShift #TechLeadership #FutureOfWork #InnovationCulture #ListenToGenZ #LearningCulture #BeginnerMindset #ModernWorkplace
https://medium.com/@sanjay.mohindroo66/reverse-mentorship-why-gen-z-is-the-teacher-you-didnt-know-you-needed-4c4180ffdccd -
Artificial intelligence, accountability, and authenticity: knowledge production and power in global health crisis
I know and appreciate Joseph, a Kenyan health leader from Murang’a County, for years of diligent leadership and contributions as a Scholar of The Geneva Learning Foundation (TGLF). Recently, he began submitting AI-generated responses to Teach to Reach Questions that were meant to elicit narratives grounded in his personal experience.
Seemingly unrelated to this, OpenAI just announced plans for specialized AI agents—autonomous systems designed to perform complex cognitive tasks—with pricing ranging from $2,000 monthly for a “high-income knowledge worker” equivalent to $20,000 monthly for “PhD-level” research capabilities.
This is happening at a time when traditional funding structures in global health, development, and humanitarian response face unprecedented volatility.
These developments intersect around fundamental questions of knowledge economics, authenticity, and power in global health contexts.
I want to explore three questions:
- What happens when health professionals in resource-constrained settings experiment with AI technologies within accountability systems that often penalize innovation?
- How might systems claiming to replicate human knowledge work transform the economics and ethics of knowledge production?
- And how should we navigate the tensions between technological adoption and authentic knowledge creation?
Artificial intelligence within punitive accountability structures of global health
For years, Joseph had shared thoughtful, context-rich contributions based on his direct experiences. All of a sudden, he was submitting generic mush with all the trappings of bad generative AI content.
Should we interpret this as disengagement from peer learning?
Given his history of diligence and commitment, I could not dismiss his exploration of AI tools as diminished engagement. Instead, I understood it as an attempt to incorporate new capabilities into his professional repertoire. This was confirmed when I got to chat with him on a WhatsApp call.
Our current Teach to Reach Questions system has not yet incorporated the use of AI. Our “old” system did not provide any way for Joseph to communicate what he was exploring.
Hence, the quality limitations in AI-generated narratives highlight not ethical failings but a developmental process requiring support rather than judgment.
But what does this look like when situated within global health accountability structures?
Health workers frequently operate within highly punitive systems where performance evaluation directly impacts funding decisions. International donors maintain extensive surveillance of program implementation, creating environments where experimentation carries significant risk. When knowledge sharing becomes entangled with performance evaluation, the incentives for transparency about AI “co-working” (i.e., collaboration between human and AI in work) diminish dramatically.
Seen through this lens, the question becomes not whether to prohibit AI-generated contributions but how to create environments where practitioners can explore technological capabilities without fear that disclosure will lead to automatic devaluation of their knowledge, regardless of its substantive quality. This heavily depends on the learning culture, which remains largely ignored or dismissed in global health.
The transparency paradox: disclosure and devaluation of artificial intelligence in global health
This case illustrates what might be called the “transparency paradox”—when disclosure or recognition of AI contribution triggers automatic devaluation regardless of substantive quality. Current attitudes create a problematic binary: acknowledge AI assistance and have contributions dismissed regardless of quality, or withhold disclosure and risk accusations of misrepresentation or worse.
This paradox creates perverse incentives against transparency, particularly in contexts where knowledge production undergoes intensive evaluation linked to resource allocation. The global health sector’s evaluation systems often emphasize compliance over innovation, creating additional barriers to technological experimentation. When every submission potentially affects funding decisions, incentives for technological experimentation become entangled with accountability pressures.
This dynamic particularly affects practitioners in Global South contexts, who face more intense scrutiny while having less institutional protection for experimentation. The punitive nature of global health accountability systems deserves particular emphasis. Health workers operate within hierarchical structures where performance is consistently monitored by both national governments and international donors. Surveillance extends from quantitative indicators to qualitative assessments of knowledge and practice.
In environments where funding depends on demonstrating certain types of knowledge or outcomes, the incentive to leverage artificial intelligence in global health may conflict with values of authenticity and transparency. This surveillance culture creates uniquely challenging conditions for technological experimentation. When performance evaluation drives resource allocation decisions, health workers face considerable risk in acknowledging technological assistance—even as they face pressure to incorporate emerging technologies into their practice.
The economics of knowledge in global health contexts
OpenAI’s announced “agents” represent a substantial evolution beyond simple chatbots or language models. If they are able to deliver what they just announced, these specialized systems would autonomously perform complex tasks simulating the cognitive work of highly-skilled professionals. The most expensive tier, priced at $20,000 monthly, purportedly offers “PhD-level” research capabilities, working continuously without the limitations of human scheduling or attention.
These claims, while unproven, suggest a potential future where knowledge work economics fundamentally change. For global health organizations operating in Geneva, where even a basic intern position for a recent master’s degree graduate cost more than 200 times that of a ChatGPT subscription, the economic proposition of systems working 24/7 for potentially comparable costs merits careful examination.
However, the global health sector has historically operated with significant labor stratification, where personnel in Global North institutions command substantially higher compensation than those working in Global South contexts. Local health workers often provide critical knowledge at compensation rates far below those of international consultants or staff at Northern institutions. This creates a different economic equation than suggested by Geneva-based comparisons. Many organizations have long relied on substantially lower local labor costs, often justified through capacity-building narratives that mask underlying power asymmetries.
Given this history, the risk that artificial intelligence in global health would replace local knowledge workers might initially appear questionable. Furthermore, the sector has demonstrated considerable resistance to technological adoption, particularly when it might disrupt established operational patterns. However, this analysis overlooks how economic pressures interact with technological change during periods of significant disruption.
The recent decisions of many government to donors to suddenly and drastically cut funding and shut down programs illustrates how rapidly even established funding structures can collapse. In such environments, organizations face existential questions about maintaining operational capacity, potentially creating conditions where technological substitution becomes more attractive despite institutional resistance.
A new AI divide
ChatGPT and other generative AI tools were initially “geo-locked”, making them more difficult to access from outside Europe and North America.
Now, the stratified pricing structure of OpenAI’s announced agents raises profound equity concerns. With the most sophisticated capabilities reserved for those able to pay high costs for the most capable agents, we face the potential emergence of an “AI divide” that threatens to reinforce existing knowledge power imbalances.
This divide presents particular challenges for global health organizations working across diverse contexts. If advanced AI capabilities remain the exclusive province of Northern institutions while Southern partners operate with limited or no AI augmentation, how might this affect knowledge dynamics already characterized by significant inequities?
The AI divide extends beyond simple access to include quality differentials in available systems. Even as simple AI tools become widely available, sophisticated capabilities that genuinely enhance knowledge work may remain concentrated within well-resourced institutions. This could lead to a scenario where practitioners in resource-constrained settings use rudimentary AI tools that produce low-quality outputs, further reinforcing perceptions of capability gaps between North and South.
Confronting power dynamics in AI integration
Traditional knowledge systems in global health position expertise in academic and institutional centers, with information flowing outward to practitioners who implement standardized solutions. This existing structure reflects and reinforces global power imbalances.
The integration of AI within these systems could either exacerbate these inequities—by further concentrating knowledge production capabilities within well-resourced institutions—or potentially disrupt them by enabling more distributed knowledge creation processes.
Joseph’s journey demonstrates this tension. His adoption of AI tools might be viewed as an attempt to access capabilities otherwise reserved for those with greater institutional resources. The question becomes not whether to allow such adoption, but how to ensure it serves genuine knowledge democratization rather than simply producing more sophisticated simulations of participation.
These emerging dynamics require us to fundamentally rethink how knowledge is valued, created, and shared within global health networks. The transparency paradox, economic pressures, and emerging AI divide suggest that technological integration will not occur within neutral space but rather within contexts already characterized by significant power asymmetries.
Developing effective responses requires moving beyond simple prescriptions about AI adoption toward deeper analysis of how these technologies interact with existing power structures—and how they might be intentionally directed toward either reinforcing or transforming these structures.
My framework for Artificial Intelligence as co-worker to support networked learning and local action is intended to contribute to such efforts.
Illustration: The Geneva Learning Foundation Collection © 2025
References
Frehywot, S., Vovides, Y., 2024. Contextualizing algorithmic literacy framework for global health workforce education. AIH 0, 4903. https://doi.org/10.36922/aih.4903
Hazarika, I., 2020. Artificial intelligence: opportunities and implications for the health workforce. International Health 12, 241–245. https://doi.org/10.1093/inthealth/ihaa007
John, A., Newton-Lewis, T., Srinivasan, S., 2019. Means, Motives and Opportunity: determinants of community health worker performance. BMJ Glob Health 4, e001790. https://doi.org/10.1136/bmjgh-2019-001790
Newton-Lewis, T., Munar, W., Chanturidze, T., 2021. Performance management in complex adaptive systems: a conceptual framework for health systems. BMJ Glob Health 6, e005582. https://doi.org/10.1136/bmjgh-2021-005582
Newton-Lewis, T., Nanda, P., 2021. Problematic problem diagnostics: why digital health interventions for community health workers do not always achieve their desired impact. BMJ Glob Health 6, e005942. https://doi.org/10.1136/bmjgh-2021-005942
Artificial Intelligence and the health workforce: Perspectives from medical associations on AI in health (OECD Artificial Intelligence Papers No. 28), 2024. , OECD Artificial Intelligence Papers. https://doi.org/10.1787/9a31d8af-en
Sadki, R. (2025). A global health framework for Artificial Intelligence as co-worker to support networked learning and local action. Reda Sadki. https://doi.org/10.59350/gr56c-cdd51
#accountability #accountabilityOverloads #ArtificialIntelligence #compliance #conservatism #globalHealth #healthWorkers #HRH #incentives #innovation #learningCulture #performanceMonitoring #TeachToReach
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Artificial intelligence, accountability, and authenticity: knowledge production and power in global health crisis
I know and appreciate Joseph, a Kenyan health leader from Murang’a County, for years of diligent leadership and contributions as a Scholar of The Geneva Learning Foundation (TGLF). Recently, he began submitting AI-generated responses to Teach to Reach Questions that were meant to elicit narratives grounded in his personal experience.
Seemingly unrelated to this, OpenAI just announced plans for specialized AI agents—autonomous systems designed to perform complex cognitive tasks—with pricing ranging from $2,000 monthly for a “high-income knowledge worker” equivalent to $20,000 monthly for “PhD-level” research capabilities.
This is happening at a time when traditional funding structures in global health, development, and humanitarian response face unprecedented volatility.
These developments intersect around fundamental questions of knowledge economics, authenticity, and power in global health contexts.
I want to explore three questions:
- What happens when health professionals in resource-constrained settings experiment with AI technologies within accountability systems that often penalize innovation?
- How might systems claiming to replicate human knowledge work transform the economics and ethics of knowledge production?
- And how should we navigate the tensions between technological adoption and authentic knowledge creation?
Artificial intelligence within punitive accountability structures of global health
For years, Joseph had shared thoughtful, context-rich contributions based on his direct experiences. All of a sudden, he was submitting generic mush with all the trappings of bad generative AI content.
Should we interpret this as disengagement from peer learning?
Given his history of diligence and commitment, I could not dismiss his exploration of AI tools as diminished engagement. Instead, I understood it as an attempt to incorporate new capabilities into his professional repertoire. This was confirmed when I got to chat with him on a WhatsApp call.
Our current Teach to Reach Questions system has not yet incorporated the use of AI. Our “old” system did not provide any way for Joseph to communicate what he was exploring.
Hence, the quality limitations in AI-generated narratives highlight not ethical failings but a developmental process requiring support rather than judgment.
But what does this look like when situated within global health accountability structures?
Health workers frequently operate within highly punitive systems where performance evaluation directly impacts funding decisions. International donors maintain extensive surveillance of program implementation, creating environments where experimentation carries significant risk. When knowledge sharing becomes entangled with performance evaluation, the incentives for transparency about AI “co-working” (i.e., collaboration between human and AI in work) diminish dramatically.
Seen through this lens, the question becomes not whether to prohibit AI-generated contributions but how to create environments where practitioners can explore technological capabilities without fear that disclosure will lead to automatic devaluation of their knowledge, regardless of its substantive quality. This heavily depends on the learning culture, which remains largely ignored or dismissed in global health.
The transparency paradox: disclosure and devaluation of artificial intelligence in global health
This case illustrates what might be called the “transparency paradox”—when disclosure or recognition of AI contribution triggers automatic devaluation regardless of substantive quality. Current attitudes create a problematic binary: acknowledge AI assistance and have contributions dismissed regardless of quality, or withhold disclosure and risk accusations of misrepresentation or worse.
This paradox creates perverse incentives against transparency, particularly in contexts where knowledge production undergoes intensive evaluation linked to resource allocation. The global health sector’s evaluation systems often emphasize compliance over innovation, creating additional barriers to technological experimentation. When every submission potentially affects funding decisions, incentives for technological experimentation become entangled with accountability pressures.
This dynamic particularly affects practitioners in Global South contexts, who face more intense scrutiny while having less institutional protection for experimentation. The punitive nature of global health accountability systems deserves particular emphasis. Health workers operate within hierarchical structures where performance is consistently monitored by both national governments and international donors. Surveillance extends from quantitative indicators to qualitative assessments of knowledge and practice.
In environments where funding depends on demonstrating certain types of knowledge or outcomes, the incentive to leverage artificial intelligence in global health may conflict with values of authenticity and transparency. This surveillance culture creates uniquely challenging conditions for technological experimentation. When performance evaluation drives resource allocation decisions, health workers face considerable risk in acknowledging technological assistance—even as they face pressure to incorporate emerging technologies into their practice.
The economics of knowledge in global health contexts
OpenAI’s announced “agents” represent a substantial evolution beyond simple chatbots or language models. If they are able to deliver what they just announced, these specialized systems would autonomously perform complex tasks simulating the cognitive work of highly-skilled professionals. The most expensive tier, priced at $20,000 monthly, purportedly offers “PhD-level” research capabilities, working continuously without the limitations of human scheduling or attention.
These claims, while unproven, suggest a potential future where knowledge work economics fundamentally change. For global health organizations operating in Geneva, where even a basic intern position for a recent master’s degree graduate cost more than 200 times that of a ChatGPT subscription, the economic proposition of systems working 24/7 for potentially comparable costs merits careful examination.
However, the global health sector has historically operated with significant labor stratification, where personnel in Global North institutions command substantially higher compensation than those working in Global South contexts. Local health workers often provide critical knowledge at compensation rates far below those of international consultants or staff at Northern institutions. This creates a different economic equation than suggested by Geneva-based comparisons. Many organizations have long relied on substantially lower local labor costs, often justified through capacity-building narratives that mask underlying power asymmetries.
Given this history, the risk that artificial intelligence in global health would replace local knowledge workers might initially appear questionable. Furthermore, the sector has demonstrated considerable resistance to technological adoption, particularly when it might disrupt established operational patterns. However, this analysis overlooks how economic pressures interact with technological change during periods of significant disruption.
The recent decisions of many government to donors to suddenly and drastically cut funding and shut down programs illustrates how rapidly even established funding structures can collapse. In such environments, organizations face existential questions about maintaining operational capacity, potentially creating conditions where technological substitution becomes more attractive despite institutional resistance.
A new AI divide
ChatGPT and other generative AI tools were initially “geo-locked”, making them more difficult to access from outside Europe and North America.
Now, the stratified pricing structure of OpenAI’s announced agents raises profound equity concerns. With the most sophisticated capabilities reserved for those able to pay high costs for the most capable agents, we face the potential emergence of an “AI divide” that threatens to reinforce existing knowledge power imbalances.
This divide presents particular challenges for global health organizations working across diverse contexts. If advanced AI capabilities remain the exclusive province of Northern institutions while Southern partners operate with limited or no AI augmentation, how might this affect knowledge dynamics already characterized by significant inequities?
The AI divide extends beyond simple access to include quality differentials in available systems. Even as simple AI tools become widely available, sophisticated capabilities that genuinely enhance knowledge work may remain concentrated within well-resourced institutions. This could lead to a scenario where practitioners in resource-constrained settings use rudimentary AI tools that produce low-quality outputs, further reinforcing perceptions of capability gaps between North and South.
Confronting power dynamics in AI integration
Traditional knowledge systems in global health position expertise in academic and institutional centers, with information flowing outward to practitioners who implement standardized solutions. This existing structure reflects and reinforces global power imbalances.
The integration of AI within these systems could either exacerbate these inequities—by further concentrating knowledge production capabilities within well-resourced institutions—or potentially disrupt them by enabling more distributed knowledge creation processes.
Joseph’s journey demonstrates this tension. His adoption of AI tools might be viewed as an attempt to access capabilities otherwise reserved for those with greater institutional resources. The question becomes not whether to allow such adoption, but how to ensure it serves genuine knowledge democratization rather than simply producing more sophisticated simulations of participation.
These emerging dynamics require us to fundamentally rethink how knowledge is valued, created, and shared within global health networks. The transparency paradox, economic pressures, and emerging AI divide suggest that technological integration will not occur within neutral space but rather within contexts already characterized by significant power asymmetries.
Developing effective responses requires moving beyond simple prescriptions about AI adoption toward deeper analysis of how these technologies interact with existing power structures—and how they might be intentionally directed toward either reinforcing or transforming these structures.
My framework for Artificial Intelligence as co-worker to support networked learning and local action is intended to contribute to such efforts.
Illustration: The Geneva Learning Foundation Collection © 2025
References
Frehywot, S., Vovides, Y., 2024. Contextualizing algorithmic literacy framework for global health workforce education. AIH 0, 4903. https://doi.org/10.36922/aih.4903
Hazarika, I., 2020. Artificial intelligence: opportunities and implications for the health workforce. International Health 12, 241–245. https://doi.org/10.1093/inthealth/ihaa007
John, A., Newton-Lewis, T., Srinivasan, S., 2019. Means, Motives and Opportunity: determinants of community health worker performance. BMJ Glob Health 4, e001790. https://doi.org/10.1136/bmjgh-2019-001790
Newton-Lewis, T., Munar, W., Chanturidze, T., 2021. Performance management in complex adaptive systems: a conceptual framework for health systems. BMJ Glob Health 6, e005582. https://doi.org/10.1136/bmjgh-2021-005582
Newton-Lewis, T., Nanda, P., 2021. Problematic problem diagnostics: why digital health interventions for community health workers do not always achieve their desired impact. BMJ Glob Health 6, e005942. https://doi.org/10.1136/bmjgh-2021-005942
Artificial Intelligence and the health workforce: Perspectives from medical associations on AI in health (OECD Artificial Intelligence Papers No. 28), 2024. , OECD Artificial Intelligence Papers. https://doi.org/10.1787/9a31d8af-en
Sadki, R. (2025). A global health framework for Artificial Intelligence as co-worker to support networked learning and local action. Reda Sadki. https://doi.org/10.59350/gr56c-cdd51
#accountability #accountabilityOverloads #ArtificialIntelligence #compliance #conservatism #globalHealth #healthWorkers #HRH #incentives #innovation #learningCulture #performanceMonitoring #TeachToReach
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Investing in learning culture fuels personal growth and gives companies strategic agility. Are we ready to adapt in fast-changing markets?
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Why answer Teach to Reach Questions?
Have you ever wished you could talk to another health worker who has faced the same challenges as you? Someone who found a way to keep helping people, even when things seemed impossible? That’s exactly the kind of active learning that Teach to Reach Questions make possible. They make peer learning easy for everyone who works for health.
What are Teach to Reach Questions?
Once you join Teach to Reach (what is it?), you’ll receive questions about real-world challenges that matter to health professionals.
How does it work?
- You choose what to share: Answer only questions where you have actual experience. No need to respond to everything – focus on what matters to you.
- Share specific moments: Instead of general information, we ask about real situations you’ve faced. What exactly happened? What did you do? How did you know it worked?
- Learn from others: Within weeks, you’ll receive a collection of experiences shared by health workers from over 70 countries. See how others solved problems similar to yours.
What’s different about these questions?
Unlike typical surveys that just collect data, Teach to Reach Questions are active learning that:
- Focus on your real-world experience.
- Help you reflect on what worked (and what didn’t).
- Connect you to solutions from other health workers.
- Give back everything shared to help everyone learn.
See what we give back to the community. Get the English-language collection of Experiences shared from Teach to Reach 10. The new compendium includes over 600 health worker experiences about immunisation, climate change, malaria, NTDs, and digital health. A second collection of more than 600 experiences shared by French-speaking participants is also available.
What’s in it for you?
Peer learning happens when we learn from each other. Your answers can help others – and their answers can help you.
- Get recognized: You’ll be honored as a Teach to Reach Contributor and receive certification.
- Learn practical solutions: See how other health workers tackle challenges like yours.
- Make connections: At Teach to Reach, you’ll meet others who have been sharing and learning about the same issues.
- Access support: Global partners will share how they can support solutions you and other health workers develop.
A health worker’s experience
Here is what on community health worker from Kenya said:
“When flooding hit our area, I felt so alone trying to figure out how to keep helping people. Through Teach to Reach, I learned that a colleague in another country had faced the same problem. Their solution helped me prepare better for the next flood. Now I’m sharing my experience to help others.”
Think about how peer learning could help you when more than 23,000 health professionals are asked to share their experience on a challenge that matters to you.
Ready to start?
- Request your invitation to Teach to Reach now.
- Look for questions in your inbox.
- Share your experience on topics you know about.
- Receive the complete collection of shared experiences.
- Join us in December to meet others face-to-face.
Remember: Your experience, no matter how small it might seem to you, could be exactly what another health worker needs to hear.
The sooner you join, the more you’ll learn from colleagues worldwide.
Together, we can turn what each of us knows into knowledge that helps everyone.
Listen to the Teach to Reach podcast:
- in English on RSS , Apple, Spotify, YouTube or Amazon podcast services.
- En français sur les services de podcast par RSS, Apple, Spotify, YouTube ou Amazon.
Is your organisation interested in learning from health workers? Learn more about becoming a Teach to Reach partner.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
#continuousLearning #experientialLearning #fieldBasdLearning #healthWorkers #learningCulture #learningStrategy #methodology #pedagogy #peerLearning #TeachToReach #TeachToReachQuestions #TheGenevaLearningFoundation
-
Why answer Teach to Reach Questions?
Have you ever wished you could talk to another health worker who has faced the same challenges as you? Someone who found a way to keep helping people, even when things seemed impossible? That’s exactly the kind of active learning that Teach to Reach Questions make possible. They make peer learning easy for everyone who works for health.
What are Teach to Reach Questions?
Once you join Teach to Reach (what is it?), you’ll receive questions about real-world challenges that matter to health professionals.
How does it work?
- You choose what to share: Answer only questions where you have actual experience. No need to respond to everything – focus on what matters to you.
- Share specific moments: Instead of general information, we ask about real situations you’ve faced. What exactly happened? What did you do? How did you know it worked?
- Learn from others: Within weeks, you’ll receive a collection of experiences shared by health workers from over 70 countries. See how others solved problems similar to yours.
What’s different about these questions?
Unlike typical surveys that just collect data, Teach to Reach Questions are active learning that:
- Focus on your real-world experience.
- Help you reflect on what worked (and what didn’t).
- Connect you to solutions from other health workers.
- Give back everything shared to help everyone learn.
See what we give back to the community. Get the English-language collection of Experiences shared from Teach to Reach 10. The new compendium includes over 600 health worker experiences about immunisation, climate change, malaria, NTDs, and digital health. A second collection of more than 600 experiences shared by French-speaking participants is also available.
What’s in it for you?
Peer learning happens when we learn from each other. Your answers can help others – and their answers can help you.
- Get recognized: You’ll be honored as a Teach to Reach Contributor and receive certification.
- Learn practical solutions: See how other health workers tackle challenges like yours.
- Make connections: At Teach to Reach, you’ll meet others who have been sharing and learning about the same issues.
- Access support: Global partners will share how they can support solutions you and other health workers develop.
A health worker’s experience
Here is what on community health worker from Kenya said:
“When flooding hit our area, I felt so alone trying to figure out how to keep helping people. Through Teach to Reach, I learned that a colleague in another country had faced the same problem. Their solution helped me prepare better for the next flood. Now I’m sharing my experience to help others.”
Think about how peer learning could help you when more than 23,000 health professionals are asked to share their experience on a challenge that matters to you.
Ready to start?
- Request your invitation to Teach to Reach now.
- Look for questions in your inbox.
- Share your experience on topics you know about.
- Receive the complete collection of shared experiences.
- Join us in December to meet others face-to-face.
Remember: Your experience, no matter how small it might seem to you, could be exactly what another health worker needs to hear.
The sooner you join, the more you’ll learn from colleagues worldwide.
Together, we can turn what each of us knows into knowledge that helps everyone.
Listen to the Teach to Reach podcast:
- in English on RSS , Apple, Spotify, YouTube or Amazon podcast services.
- En français sur les services de podcast par RSS, Apple, Spotify, YouTube ou Amazon.
Is your organisation interested in learning from health workers? Learn more about becoming a Teach to Reach partner.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
#continuousLearning #experientialLearning #fieldBasdLearning #healthWorkers #learningCulture #learningStrategy #methodology #pedagogy #peerLearning #TeachToReach #TeachToReachQuestions #TheGenevaLearningFoundation
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In a rural health center in Kenya, a community health worker develops an innovative approach to reaching families who have been hesitant about vaccination.
Meanwhile, in a Brazilian city, a nurse has gotten everyone involved – including families and communities – onboard to integrate information about HPV vaccination into cervical cancer screening.
These valuable insights might once have remained isolated, their potential impact limited to their immediate contexts.
But through Teach to Reach – a peer learning platform, network, and community hosted by The Geneva Learning Foundation – these experiences become part of a larger tapestry of knowledge that transforms how health workers learn and adapt their practices worldwide.
Since January 2021, the event series has grown to connect over 21,000 health professionals from more than 70 countries, reaching its tenth edition with 21,398 participants in June 2024.
Scale matters, but this level of engagement begs the question: how and why does it work?
The challenge in global health is not just about what people need to learn – it is about reimagining how learning happens and gets applied in complex, rapidly-changing environments to improve performance, improve health outcomes, and prepare the next generation of leaders.
Traditional approaches to professional development, built around expert-led training and top-down knowledge transfer, often fail to create lasting change.
They tend to ignore the rich knowledge that exists in practice – what we know when we are there every day, side-by-side with the community we serve – and the complex ways that learning actually occurs in professional networks and communities.
Teach to Reach is one component in The Geneva Learning Foundation’s emergent model for learning and change.
This article describes the pedagogical patterns that Teach to Reach brings to life.
A new vision for digital-first, networked professional learning
Teach to Reach represents a shift in how we think about professional learning in global health.
Its pedagogical pattern draws from three complementary theoretical frameworks that together create a more complete understanding of how professionals learn and how that learning translates into improved practice.
At its foundation lies Bill Cope’s and Mary Kalantzis’s New Learning framework, which recognizes that knowledge creation in the digital age requires new approaches to learning and assessment.
Teach to Reach then integrates insights from Watkins and Marsick’s research on the strong relationship between learning culture (a measure of the capacity for change) and performance and George Siemens’s learning theory of connectivism to create something syncretic: a learning approach that simultaneously builds individual capability, organizational capacity, and network strength.
Active knowledge making
The prevailing model of professional development often treats learners as empty vessels to be filled with expert knowledge.
Drawing from constructivist learning theory, it positions health workers as knowledge creators rather than passive recipients.
When a community health worker in Kenya shares how they’ve adapted vaccination strategies for remote communities, they are not just describing their work – they’re creating valuable knowledge that others can learn from and adapt.
The role of experts is even more significant in this model: experts become “Guides on the side”, listening to challenges and their contexts to identify what expert knowledge is most likely to be useful to a specific challenge and context.
(This is the oft-neglected “downstream” to the “upstream” work that goes into the creation of global guidelines.)
This principle manifests in how questions are framed.
Instead of asking “What should you do when faced with vaccine hesitancy?” Teach to Reach asks “Tell us about a time when you successfully addressed vaccine hesitancy in your community.” This subtle shift transforms the learning dynamic from theoretical to practical, from passive to active.
Collaborative intelligence
The concept of collaborative intelligence, inspired by social learning theory, recognizes that knowledge in complex fields like global health is distributed across many individuals and contexts.
No single expert or institution holds all the answers.
By creating structures for health workers to share and learn from each other’s experiences, Teach to Reach taps into what cognitive scientists call “distributed cognition” – the idea that knowledge and understanding emerge from networks of people rather than individual minds.
This plays out practically in how experiences are shared and synthesized.
When a nurse in Brazil shares their approach to integrating COVID-19 vaccination with routine immunization, their experience becomes part of a larger tapestry of knowledge that includes perspectives from diverse contexts and roles.
Metacognitive reflection
Metacognition – thinking about thinking – is crucial for professional development, yet it is often overlooked in traditional training.
Teach to Reach deliberately builds in opportunities for metacognitive reflection through its question design and response framework.
When participants share experiences, they are prompted not just to describe what happened, but to analyze why they made certain decisions and what they learned from the experience.
This reflective practice helps health workers develop deeper understanding of their own practice and decision-making processes.It transforms individual experiences into learning opportunities that benefit both the sharer and the wider community.
Recursive feedback
Learning is not linear – it is a cyclical process of sharing, reflecting, applying, and refining.
Teach to Reach’s model of recursive feedback, inspired by systems thinking, creates multiple opportunities for participants to engage with and build upon each other’s experiences.
This goes beyond communities of practice, because the community component is part of a broader, dynamic and ongoing process.
Executing a complex pedagogical pattern
The pedagogical pattern of Teach to Reach come to life through a carefully designed implementation framework over a six-month period, before, during, and after the live event.
This extended timeframe is not arbitrary – it is based on research showing that sustained engagement over time leads to deeper learning and more lasting change than one-off learning events.
The core of the learning process is the Teach to Reach Questions – weekly prompts that guide participants through progressively more complex reflection and sharing.These questions are crafted to elicit not just information, but insight and understanding.
They follow a deliberate sequence that moves from description to analysis to reflection to application, mirroring the natural cycle of experiential learning.
Communication as pedagogy
In Teach to Reach, communication is not just about delivering information – it is an integral part of the learning process.
The model uses what scholars call “pedagogical communication” – communication designed specifically to facilitate learning.
This manifests in several ways:
- Personal and warm tone that creates psychological safety for sharing
- Clear calls to action that guide participants through the learning process
- Multiple touchpoints that reinforce learning and maintain engagement
- Progressive engagement that builds complexity gradually
Learning culture and performance
Watkins and Marsick’s work helps us understand why Teach to Reach’s approach is so effective.
Learning culture – the set of organizational values, practices, and systems that support continuous learning – is crucial for translating individual insights into improved organizational performance.
Teach to Reach deliberately builds elements of strong learning cultures into its design.
Furthermore, the Geneva Learning Foundation’s research found that continuous learning is the weakest dimension of learning culture in immunization – and probably global health.
Hence, Teach to Reach itself provides a mechanism to strengthen specifically this dimension.
Take the simple act of asking questions about real work experiences.
This is not just about gathering information – it’s about creating what Watkins and Marsick call “inquiry and dialogue,” a fundamental dimension of learning organizations.
When health workers share their experiences, they are not just describing what happened.
They are engaging in a form of collaborative inquiry that helps everyone involved develop deeper understanding.
Networks of knowledge
George Siemens’s connectivism theory provides another crucial lens for understanding Teach to Reach’s effectiveness.
In today’s world, knowledge is not just what is in our heads – it is distributed across networks of people and resources.
Teach to Reach creates and strengthens these networks through its unique approach to asynchronous peer learning.
The process begins with carefully designed questions that prompt health workers to share specific experiences.
But it does not stop there.
These experiences become nodes in a growing network of knowledge, connected through themes, challenges, and solutions.
When a health worker in India reads about how a colleague in Nigeria addressed a particular challenge, they are not just learning about one solution – they are becoming part of a network that makes everyone’s practice stronger.
From theory to practice
What makes Teach to Reach particularly powerful is how it fuses multiple theories of learning into a practical model that works in real-world conditions.
The model recognizes that learning must be accessible to health workers dealing with limited connectivity, heavy workloads, and diverse linguistic and cultural contexts.
New Learning’s emphasis on multimodal meaning-making supports the use of multiple communication channels ensuring accessibility.
Learning culture principles guide the creation of supportive structures that make continuous learning possible even in challenging conditions.
Connectivist insights inform how knowledge is shared and distributed across the network.
Creating sustainable change
The real test of any learning approach is whether it creates sustainable change in practice.
By simultaneously building individual capability, organizational capacity, and network strength, it creates the conditions for continuous improvement and adaptation.
Health workers do not just learn new approaches – they develop the capacity to learn continuously from their own experience and the experiences of others.
Organizations do not just gain new knowledge – they develop stronger learning cultures that support ongoing innovation.
And the broader health system gains not just a collection of good practices, but a living network of practitioners who continue to learn and adapt together.
Looking forward
As global health challenges have become more complex, the need for more effective approaches to professional learning becomes more urgent.
Teach to Reach’s pedagogical model, grounded in complementary theoretical frameworks and proven in practice, offers valuable insights for anyone interested in creating impactful professional learning experiences.
The model suggests that effective professional learning in complex fields like global health requires more than just good content or engaging delivery.
It requires careful attention to how learning cultures are built, how networks are strengthened, and how individual learning connects to organizational and system performance.
Most importantly, it reminds us that the most powerful learning often happens not through traditional training but through thoughtfully structured opportunities for professionals to learn from and with each other.
In this way, Teach to Reach is a demonstration of what becomes possible when we reimagine how professional learning happens in service of better health outcomes worldwide.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
https://redasadki.me/2024/10/30/what-is-the-pedagogy-of-teach-to-reach/
#continuousLearning #globalHealth #learningCulture #learningStrategy #learningTheory #pedagogicalPatterns #peerLearning #TeachToReach #TheGenevaLearningFoundation
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In a rural health center in Kenya, a community health worker develops an innovative approach to reaching families who have been hesitant about vaccination.
Meanwhile, in a Brazilian city, a nurse has gotten everyone involved – including families and communities – onboard to integrate information about HPV vaccination into cervical cancer screening.
These valuable insights might once have remained isolated, their potential impact limited to their immediate contexts.
But through Teach to Reach – a peer learning platform, network, and community hosted by The Geneva Learning Foundation – these experiences become part of a larger tapestry of knowledge that transforms how health workers learn and adapt their practices worldwide.
Since January 2021, the event series has grown to connect over 21,000 health professionals from more than 70 countries, reaching its tenth edition with 21,398 participants in June 2024.
Scale matters, but this level of engagement begs the question: how and why does it work?
The challenge in global health is not just about what people need to learn – it is about reimagining how learning happens and gets applied in complex, rapidly-changing environments to improve performance, improve health outcomes, and prepare the next generation of leaders.
Traditional approaches to professional development, built around expert-led training and top-down knowledge transfer, often fail to create lasting change.
They tend to ignore the rich knowledge that exists in practice – what we know when we are there every day, side-by-side with the community we serve – and the complex ways that learning actually occurs in professional networks and communities.
Teach to Reach is one component in The Geneva Learning Foundation’s emergent model for learning and change.
This article describes the pedagogical patterns that Teach to Reach brings to life.
A new vision for digital-first, networked professional learning
Teach to Reach represents a shift in how we think about professional learning in global health.
Its pedagogical pattern draws from three complementary theoretical frameworks that together create a more complete understanding of how professionals learn and how that learning translates into improved practice.
At its foundation lies Bill Cope’s and Mary Kalantzis’s New Learning framework, which recognizes that knowledge creation in the digital age requires new approaches to learning and assessment.
Teach to Reach then integrates insights from Watkins and Marsick’s research on the strong relationship between learning culture (a measure of the capacity for change) and performance and George Siemens’s learning theory of connectivism to create something syncretic: a learning approach that simultaneously builds individual capability, organizational capacity, and network strength.
Active knowledge making
The prevailing model of professional development often treats learners as empty vessels to be filled with expert knowledge.
Drawing from constructivist learning theory, it positions health workers as knowledge creators rather than passive recipients.
When a community health worker in Kenya shares how they’ve adapted vaccination strategies for remote communities, they are not just describing their work – they’re creating valuable knowledge that others can learn from and adapt.
The role of experts is even more significant in this model: experts become “Guides on the side”, listening to challenges and their contexts to identify what expert knowledge is most likely to be useful to a specific challenge and context.
(This is the oft-neglected “downstream” to the “upstream” work that goes into the creation of global guidelines.)
This principle manifests in how questions are framed.
Instead of asking “What should you do when faced with vaccine hesitancy?” Teach to Reach asks “Tell us about a time when you successfully addressed vaccine hesitancy in your community.” This subtle shift transforms the learning dynamic from theoretical to practical, from passive to active.
Collaborative intelligence
The concept of collaborative intelligence, inspired by social learning theory, recognizes that knowledge in complex fields like global health is distributed across many individuals and contexts.
No single expert or institution holds all the answers.
By creating structures for health workers to share and learn from each other’s experiences, Teach to Reach taps into what cognitive scientists call “distributed cognition” – the idea that knowledge and understanding emerge from networks of people rather than individual minds.
This plays out practically in how experiences are shared and synthesized.
When a nurse in Brazil shares their approach to integrating COVID-19 vaccination with routine immunization, their experience becomes part of a larger tapestry of knowledge that includes perspectives from diverse contexts and roles.
Metacognitive reflection
Metacognition – thinking about thinking – is crucial for professional development, yet it is often overlooked in traditional training.
Teach to Reach deliberately builds in opportunities for metacognitive reflection through its question design and response framework.
When participants share experiences, they are prompted not just to describe what happened, but to analyze why they made certain decisions and what they learned from the experience.
This reflective practice helps health workers develop deeper understanding of their own practice and decision-making processes.It transforms individual experiences into learning opportunities that benefit both the sharer and the wider community.
Recursive feedback
Learning is not linear – it is a cyclical process of sharing, reflecting, applying, and refining.
Teach to Reach’s model of recursive feedback, inspired by systems thinking, creates multiple opportunities for participants to engage with and build upon each other’s experiences.
This goes beyond communities of practice, because the community component is part of a broader, dynamic and ongoing process.
Executing a complex pedagogical pattern
The pedagogical pattern of Teach to Reach come to life through a carefully designed implementation framework over a six-month period, before, during, and after the live event.
This extended timeframe is not arbitrary – it is based on research showing that sustained engagement over time leads to deeper learning and more lasting change than one-off learning events.
The core of the learning process is the Teach to Reach Questions – weekly prompts that guide participants through progressively more complex reflection and sharing.These questions are crafted to elicit not just information, but insight and understanding.
They follow a deliberate sequence that moves from description to analysis to reflection to application, mirroring the natural cycle of experiential learning.
Communication as pedagogy
In Teach to Reach, communication is not just about delivering information – it is an integral part of the learning process.
The model uses what scholars call “pedagogical communication” – communication designed specifically to facilitate learning.
This manifests in several ways:
- Personal and warm tone that creates psychological safety for sharing
- Clear calls to action that guide participants through the learning process
- Multiple touchpoints that reinforce learning and maintain engagement
- Progressive engagement that builds complexity gradually
Learning culture and performance
Watkins and Marsick’s work helps us understand why Teach to Reach’s approach is so effective.
Learning culture – the set of organizational values, practices, and systems that support continuous learning – is crucial for translating individual insights into improved organizational performance.
Teach to Reach deliberately builds elements of strong learning cultures into its design.
Furthermore, the Geneva Learning Foundation’s research found that continuous learning is the weakest dimension of learning culture in immunization – and probably global health.
Hence, Teach to Reach itself provides a mechanism to strengthen specifically this dimension.
Take the simple act of asking questions about real work experiences.
This is not just about gathering information – it’s about creating what Watkins and Marsick call “inquiry and dialogue,” a fundamental dimension of learning organizations.
When health workers share their experiences, they are not just describing what happened.
They are engaging in a form of collaborative inquiry that helps everyone involved develop deeper understanding.
Networks of knowledge
George Siemens’s connectivism theory provides another crucial lens for understanding Teach to Reach’s effectiveness.
In today’s world, knowledge is not just what is in our heads – it is distributed across networks of people and resources.
Teach to Reach creates and strengthens these networks through its unique approach to asynchronous peer learning.
The process begins with carefully designed questions that prompt health workers to share specific experiences.
But it does not stop there.
These experiences become nodes in a growing network of knowledge, connected through themes, challenges, and solutions.
When a health worker in India reads about how a colleague in Nigeria addressed a particular challenge, they are not just learning about one solution – they are becoming part of a network that makes everyone’s practice stronger.
From theory to practice
What makes Teach to Reach particularly powerful is how it fuses multiple theories of learning into a practical model that works in real-world conditions.
The model recognizes that learning must be accessible to health workers dealing with limited connectivity, heavy workloads, and diverse linguistic and cultural contexts.
New Learning’s emphasis on multimodal meaning-making supports the use of multiple communication channels ensuring accessibility.
Learning culture principles guide the creation of supportive structures that make continuous learning possible even in challenging conditions.
Connectivist insights inform how knowledge is shared and distributed across the network.
Creating sustainable change
The real test of any learning approach is whether it creates sustainable change in practice.
By simultaneously building individual capability, organizational capacity, and network strength, it creates the conditions for continuous improvement and adaptation.
Health workers do not just learn new approaches – they develop the capacity to learn continuously from their own experience and the experiences of others.
Organizations do not just gain new knowledge – they develop stronger learning cultures that support ongoing innovation.
And the broader health system gains not just a collection of good practices, but a living network of practitioners who continue to learn and adapt together.
Looking forward
As global health challenges have become more complex, the need for more effective approaches to professional learning becomes more urgent.
Teach to Reach’s pedagogical model, grounded in complementary theoretical frameworks and proven in practice, offers valuable insights for anyone interested in creating impactful professional learning experiences.
The model suggests that effective professional learning in complex fields like global health requires more than just good content or engaging delivery.
It requires careful attention to how learning cultures are built, how networks are strengthened, and how individual learning connects to organizational and system performance.
Most importantly, it reminds us that the most powerful learning often happens not through traditional training but through thoughtfully structured opportunities for professionals to learn from and with each other.
In this way, Teach to Reach is a demonstration of what becomes possible when we reimagine how professional learning happens in service of better health outcomes worldwide.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
https://redasadki.me/2024/10/30/what-is-the-pedagogy-of-teach-to-reach/
#continuousLearning #globalHealth #learningCulture #learningStrategy #learningTheory #pedagogicalPatterns #peerLearning #TeachToReach #TheGenevaLearningFoundation
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It was James Gleick who noted in his book “Faster: The Acceleration of Just About Everything” the societal shift towards valuing speed over depth:
“We have become a quick-reflexed, multitasking, channel-flipping, fast-forwarding species. We don’t completely understand it, and we’re not altogether happy about it.”
In global health, there’s a growing tendency to demand ever-shorter summaries of complex information.
“Can you condense this into four pages?”“Is there an executive summary?”
These requests, while stemming from real time constraints, reveal fundamental misunderstandings about the nature of knowledge and learning.
Worse, they contribute to perpetuating existing global health inequities.
Here is why – and a few ideas of what we can do about it.
The drive for brevity
The push for shortened summaries is understandable on the surface.
Some clinical researchers, for example, undeniably face increasing time pressures.
Many are swamped due to underlying structural issues, such as healthcare professional shortages.
This is the result of a significant shift over time, leaving less time for deep engagement with new information.
If we accept these changes, we lose far more than time.
Why does learning require time, depth, and context?
True understanding and the ability to apply knowledge in diverse contexts demands deep engagement, reflection, and often, struggle with our own assumptions and mental models.
Consider the process of learning a new language.
No one expects to become fluent by reading a few pages of grammar rules.
Mastery requires immersion, practice, making mistakes, and gradually building competence over time.
The same principle applies to making sense of multifaceted global health issues.
5 risks of executive summaries
Here are five risks of demanding summaries of everything:
- Oversimplification: Complex health challenges often cannot be adequately captured in a few pages. Crucial nuances and context-specific details get lost. Those ‘details’ may actually be the ‘how’ of what makes the difference for those leading change to achieve results.
- Losing context: Information that can be easily summarized (quantitative data, broad generalizations) gets prioritized over more nuanced, qualitative, or context-specific knowledge.
- Stunting critical thinking: The habit of relying on summaries can atrophy our capacity for deep, critical engagement with complex ideas.
- Overconfidence: It assumes that learning is primarily about information transfer, rather than a process of engagement, reflection, and application. Reading a summary can give the false impression that one has grasped a topic, leading to overconfidence in decision-making.
- Devaluing local knowledge: Rich, contextual experiences from health workers and communities often do not lend themselves to easy summarization.
The expectation that complex local realities can always be distilled into brief summaries for consumption by decision-makers (often in the Global North) perpetuates existing power structures in global health.
The ability to demand summaries often comes from positions of power.
This can lead to privileging certain voices (those who can produce polished summaries) over others (those with deep, context-specific knowledge that resists easy summarization).
This knowledge then gets sidelined in favor of more easily digestible but potentially less relevant information.
10 ways to value and engage with knowledge in global health
Addressing the “summary culture” requires more than better time management.
It calls for a fundamental rethinking of how we value and engage with knowledge in global health.
Instead of defaulting to demands for ever-shorter summaries, we need to rethink how we engage with knowledge in global health.
- Prioritize productive diversity over reductive simplicity: Sometimes, it is better to engage deeply many different ideas than to seek one reductive generalization.
- Value local expertise: Prioritize knowledge from those closest to the issues, even when it does not fit neatly into summary format.
- Value diverse knowledge forms: Recognize that not all valuable knowledge can be easily summarized. Create space for stories, case studies, and rich qualitative data.
- Improve information design: Instead of just shortening, focus on presenting information in more accessible and engaging ways that do not sacrifice complexity.
- Create new formats: Develop ways of sharing information that balance accessibility with depth and nuance.
- Pause and reflect: What might be lost in the condensing? Are you truly seeking efficiency, or avoiding the discomfort of engaging with complex, potentially challenging ideas? Are you willing to advocate for systemic changes that truly value deep learning and diverse knowledge sources?
- Challenge the demand: When asked for summaries, push back (respectfully) and explain why certain information resists easy summarization.
- Foster critical engagement: Encourage professionals to develop skills in quickly assessing and engaging with complex information, rather than providing pre-digested summaries.
- Educate funders and decision-makers: Help those in power understand the value of engaging with complexity and diverse knowledge forms.
- Rethink the economy of time allocation: Advocate for systemic changes that value time spent on deep learning and reflection as core to effective practice and leadership.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/08/27/brevitys-burden-the-executive-summary-trap-in-global-health/
#decolonization #globalHealth #JamesGleick #learningCulture #learningStrategy #natureOfKnowledge
-
It was James Gleick who noted in his book “Faster: The Acceleration of Just About Everything” the societal shift towards valuing speed over depth:
“We have become a quick-reflexed, multitasking, channel-flipping, fast-forwarding species. We don’t completely understand it, and we’re not altogether happy about it.”
In global health, there’s a growing tendency to demand ever-shorter summaries of complex information.
“Can you condense this into four pages?”“Is there an executive summary?”
These requests, while stemming from real time constraints, reveal fundamental misunderstandings about the nature of knowledge and learning.
Worse, they contribute to perpetuating existing global health inequities.
Here is why – and a few ideas of what we can do about it.
We lose more than time in the race to brevity
The push for shortened summaries is understandable on the surface.
Some clinical researchers, for example, undeniably face increasing time pressures.
Many are swamped due to underlying structural issues, such as healthcare professional shortages.
This is the result of a significant shift over time, leaving less time for deep engagement with new information.
If we accept these changes, we lose far more than time.
Why does learning require time, depth, and context?
True understanding and the ability to apply knowledge in diverse contexts demands deep engagement, reflection, and often, struggle with our own assumptions and mental models.
Consider the process of learning a new language.
No one expects to become fluent by reading a few pages of grammar rules.
Mastery requires immersion, practice, making mistakes, and gradually building competence over time.
The same principle applies to making sense of multifaceted global health issues.
5 risks of executive summaries
Here are five risks of demanding summaries of everything:
- Oversimplification: Complex health challenges often cannot be adequately captured in a few pages. Crucial nuances and context-specific details get lost. Those ‘details’ may actually be the ‘how’ of what makes the difference for those leading change to achieve results.
- Losing context: Information that can be easily summarized (quantitative data, broad generalizations) gets prioritized over more nuanced, qualitative, or context-specific knowledge.
- Stunting critical thinking: The habit of relying on summaries can atrophy our capacity for deep, critical engagement with complex ideas.
- Overconfidence: It assumes that learning is primarily about information transfer, rather than a process of engagement, reflection, and application. Reading a summary can give the false impression that one has grasped a topic, leading to overconfidence in decision-making.
- Devaluing local knowledge: Rich, contextual experiences from health workers and communities often do not lend themselves to easy summarization.
The expectation that complex local realities can always be distilled into brief summaries for consumption by decision-makers (often in the Global North) perpetuates existing power structures in global health.
The ability to demand summaries often comes from positions of power.
This can lead to privileging certain voices (those who can produce polished summaries) over others (those with deep, context-specific knowledge that resists easy summarization).
This knowledge then gets sidelined in favor of more easily digestible but potentially less relevant information.
10 ways to value and engage with knowledge in global health
Addressing the “summary culture” requires more than better time management.
It calls for a fundamental rethinking of how we value and engage with knowledge in global health.
Instead of defaulting to demands for ever-shorter summaries, we need to rethink how we engage with knowledge.
Here are 10 practical ways to do so.
- Prioritize productive diversity over reductive simplicity: Sometimes, it is better to engage deeply many different ideas than to seek one reductive generalization.
- Value local expertise: Prioritize knowledge from those closest to the issues, even when it does not fit neatly into summary format.
- Value diverse knowledge forms: Recognize that not all valuable knowledge can be easily summarized. Create space for stories, case studies, and rich qualitative data.
- Improve information design: Instead of just shortening, focus on presenting information in more accessible and engaging ways that do not sacrifice complexity.
- Create new formats: Develop ways of sharing information that balance accessibility with depth and nuance.
- Pause and reflect: What might be lost in the condensing? Are you truly seeking efficiency, or avoiding the discomfort of engaging with complex, potentially challenging ideas? Are you willing to advocate for systemic changes that truly value deep learning and diverse knowledge sources?
- Challenge the demand: When asked for summaries, push back (respectfully) and explain why certain information resists easy summarization.
- Foster critical engagement: Encourage professionals to develop skills in quickly assessing and engaging with complex information, rather than providing pre-digested summaries.
- Educate funders and decision-makers: Help those in power understand the value of engaging with complexity and diverse knowledge forms.
- Rethink the economy of time allocation: Advocate for systemic changes that value time spent on deep learning and reflection as core to effective practice and leadership.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
https://redasadki.me/2024/08/27/brevitys-burden-the-executive-summary-trap-in-global-health/
#decolonization #globalHealth #JamesGleick #learningCulture #learningStrategy #natureOfKnowledge
-
It was James Gleick who noted in his book “Faster: The Acceleration of Just About Everything” the societal shift towards valuing speed over depth:
“We have become a quick-reflexed, multitasking, channel-flipping, fast-forwarding species. We don’t completely understand it, and we’re not altogether happy about it.”
In global health, there’s a growing tendency to demand ever-shorter summaries of complex information.
“Can you condense this into four pages?”“Is there an executive summary?”
These requests, while stemming from real time constraints, reveal fundamental misunderstandings about the nature of knowledge and learning.
Worse, they contribute to perpetuating existing global health inequities.
Here is why – and a few ideas of what we can do about it.
We lose more than time in the race to brevity
The push for shortened summaries is understandable on the surface.
Some clinical researchers, for example, undeniably face increasing time pressures.
Many are swamped due to underlying structural issues, such as healthcare professional shortages.
This is the result of a significant shift over time, leaving less time for deep engagement with new information.
If we accept these changes, we lose far more than time.
Why does learning require time, depth, and context?
True understanding and the ability to apply knowledge in diverse contexts demands deep engagement, reflection, and often, struggle with our own assumptions and mental models.
Consider the process of learning a new language.
No one expects to become fluent by reading a few pages of grammar rules.
Mastery requires immersion, practice, making mistakes, and gradually building competence over time.
The same principle applies to making sense of multifaceted global health issues.
5 risks of executive summaries
Here are five risks of demanding summaries of everything:
- Oversimplification: Complex health challenges often cannot be adequately captured in a few pages. Crucial nuances and context-specific details get lost. Those ‘details’ may actually be the ‘how’ of what makes the difference for those leading change to achieve results.
- Losing context: Information that can be easily summarized (quantitative data, broad generalizations) gets prioritized over more nuanced, qualitative, or context-specific knowledge.
- Stunting critical thinking: The habit of relying on summaries can atrophy our capacity for deep, critical engagement with complex ideas.
- Overconfidence: It assumes that learning is primarily about information transfer, rather than a process of engagement, reflection, and application. Reading a summary can give the false impression that one has grasped a topic, leading to overconfidence in decision-making.
- Devaluing local knowledge: Rich, contextual experiences from health workers and communities often do not lend themselves to easy summarization.
The expectation that complex local realities can always be distilled into brief summaries for consumption by decision-makers (often in the Global North) perpetuates existing power structures in global health.
The ability to demand summaries often comes from positions of power.
This can lead to privileging certain voices (those who can produce polished summaries) over others (those with deep, context-specific knowledge that resists easy summarization).
This knowledge then gets sidelined in favor of more easily digestible but potentially less relevant information.
10 ways to value and engage with knowledge in global health
Addressing the “summary culture” requires more than better time management.
It calls for a fundamental rethinking of how we value and engage with knowledge in global health.
Instead of defaulting to demands for ever-shorter summaries, we need to rethink how we engage with knowledge.
Here are 10 practical ways to do so.
- Prioritize productive diversity over reductive simplicity: Sometimes, it is better to engage deeply many different ideas than to seek one reductive generalization.
- Value local expertise: Prioritize knowledge from those closest to the issues, even when it does not fit neatly into summary format.
- Value diverse knowledge forms: Recognize that not all valuable knowledge can be easily summarized. Create space for stories, case studies, and rich qualitative data.
- Improve information design: Instead of just shortening, focus on presenting information in more accessible and engaging ways that do not sacrifice complexity.
- Create new formats: Develop ways of sharing information that balance accessibility with depth and nuance.
- Pause and reflect: What might be lost in the condensing? Are you truly seeking efficiency, or avoiding the discomfort of engaging with complex, potentially challenging ideas? Are you willing to advocate for systemic changes that truly value deep learning and diverse knowledge sources?
- Challenge the demand: When asked for summaries, push back (respectfully) and explain why certain information resists easy summarization.
- Foster critical engagement: Encourage professionals to develop skills in quickly assessing and engaging with complex information, rather than providing pre-digested summaries.
- Educate funders and decision-makers: Help those in power understand the value of engaging with complexity and diverse knowledge forms.
- Rethink the economy of time allocation: Advocate for systemic changes that value time spent on deep learning and reflection as core to effective practice and leadership.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
https://redasadki.me/2024/08/27/brevitys-burden-the-executive-summary-trap-in-global-health/
#decolonization #globalHealth #JamesGleick #learningCulture #learningStrategy #natureOfKnowledge
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The Nigeria Immunization Collaborative: Early learning from a novel sector-wide approach model for zero-dose challenges
Less than three weeks after its launch, the Nigeria Immunization Collaborative – a partnership between the Geneva Learning Foundation, the National Primary Health Care Development Agency (NPHCDA), and UNICEF – has already connected over 4,000 participants from all 36 states and more than 300 Local Government Areas (LGAs).
The Collaborative is part of the Movement for Immunization Agenda 2030 (IA2030).
In the Collaborative’s first peer learning exercise that concluded on 6 August 2024, over 600 participants conducted root cause analyses of immunization barriers in their communities.
Participants engaged in a two-week intensive process of analyzing immunization challenges, conducting root cause analyses, and developing actionable plans to address these issues.
They did this without having to stop their daily work or travel, a key characteristic of The Geneva Learning Foundation’s model to support work-based learning.
Watch the General Assembly of the Nigeria Immunization Collaborative on 6 August 2024
https://www.youtube.com/watch?v=zicqexzachA
What are health workers saying about the Collaborative?
For Mariam Mustapha, a participant from Kano State, the Collaborative is “multiple individuals that perform a task”, united around a shared purpose.
She highlighted the importance of engaging with community members, noting, “These people from the community, most of them, they don’t have enough knowledge or they are receiving misinformation about immunization and vaccines.”
The peer learning exercise employed a structured approach, asking participants to explain their immunization challenge, conduct a “5 Whys” analysis to identify root causes, and develop actionable plans within their scope of work.
How does the Collaborative help health workers?
This method proved enlightening for many participants.
John Emmanuel, a community health worker from Bauchi State, shared his experience: “I just discovered that over the years, I have been superficial in my approach. I’ve been one sided. I’ve been actually peripheral in my approach. So during the root cause analysis, I was able to identify the broader perspective of identifying the challenge and then fixing it as it affects my job here in the community.”
The Collaborative also fostered connections between health workers across different regions of Nigeria.
Mohammed Nasir Umar, a JSI HPV program associate in Zamfara State, noted the value of this cross-pollination of ideas: “The root cause analysis really widened my horizon on how I think around the challenges. The ‘5 Whys’ techniques approach was really, really helpful.”
Participants identified a range of immunization challenges, including vaccine hesitancy, lack of information and awareness, sociocultural and religious factors, reaching zero-dose children, incomplete immunization, healthcare worker issues, logistical challenges, political interference, poor documentation, and community trust issues.
But then each one started asking ‘why’, stopping only once they found a root cause that they are in a position to do something about.
Esther Sharma, working with NPHCDA in a local government area, identified a critical issue in her facility: “The reason why people turn out low for immunization is because there are no health workers in the facilities to attend to them when they get here.”
Her solution involves ensuring consistent staffing during immunization days, which should encourage more community members to seek vaccination services.
How are new stakeholders participating in the Collaborative?
The Collaborative also welcomed participation from organizations not traditionally involved in immunization services.
Angela Emmanuel, a nurse and founder of the Emmanuel Cancer Foundation in Lagos, found value in the exercise for her work on HPV vaccination and cancer prevention.
She emphasized the need for a more educational approach: “Our motive should be education. Our motive should be the awareness, not just asking them to take this vaccine.”
Chijioke Kaduru, a public health physician who served as a Guide for the Collaborative, reflected: “While some of these challenges are similar in many settings, the local context and the nuances that shape these challenges clearly make them a good opportunity to engage, to interact, to understand them better, and to start to also see the ideas that colleagues have about how to solve those problems.”
By connecting frontline health workers, fostering critical thinking, and encouraging the development of locally-tailored solutions, the Nigeria Immunization Collaborative represents a potentially scalable model for strengthening health systems and improving immunization coverage.
As the exercise concludes, participants are poised to implement their action plans in their respective communities.
How are government workers participating in the Collaborative?
A key focus of the final session was the presentation of root cause analyses by government workers from the Federal and State Primary Health Care Development Agencies.
These presentations provided valuable insights into the challenges faced at various levels of the health system and the innovative solutions being developed.
Maimuna Tata, a deputy in-charge at a health facility in Bunkura local government area of Kano State, presented her analysis of why routine immunization sessions were not being conducted at her facility.
Through her “5 Whys” analysis, she uncovered a systemic issue: “The health facility is newly built and was commissioned after the 2024 micro plan exercise and needs to undergo several processes for provision of routine immunization.”
Tata’s proposed solution demonstrated the kind of innovative thinking the Collaborative aimed to foster: “Instead of them coming for outreach session in the settlement, I think the vaccine should be channeled to the health facility so that the health facility can conduct the sessions. And at the end of the day, we will now be submitting our reports to the health facility, that is the model health facility, pending the time the health facility will be recorded or will be updated in the server.”
Esther Sharma, working with NPHCDA in a local government area, identified a critical staffing issue: “The reason why people turn out low for immunization is because there are no health workers in the facilities to attend to them when they get here. I am the routine immuunization focal person where I currently work and when I went there newly, I asked a lot of people, why don’t they come to the hospital for immunization? And they said when they come, they don’t find anybody to attend to them.”
Her solution involves ensuring consistent staffing during immunization days, which she reported has already encouraged more community members to seek vaccination services.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
#Collaborative #ImmunizationAgenda2030 #learningCulture #Nigeria #NPHCDA #peerLearning #rootCauseAnalysis #socialLearning #TheGenevaLearningFoundation
-
The Nigeria Immunization Collaborative: Early learning from a novel sector-wide approach model for zero-dose challenges
Less than three weeks after its launch, the Nigeria Immunization Collaborative – a partnership between the Geneva Learning Foundation, the National Primary Health Care Development Agency (NPHCDA), and UNICEF – has already connected over 4,000 participants from all 36 states and more than 300 Local Government Areas (LGAs).
The Collaborative is part of the Movement for Immunization Agenda 2030 (IA2030).
In the Collaborative’s first peer learning exercise that concluded on 6 August 2024, over 600 participants conducted root cause analyses of immunization barriers in their communities.
Participants engaged in a two-week intensive process of analyzing immunization challenges, conducting root cause analyses, and developing actionable plans to address these issues.
They did this without having to stop their daily work or travel, a key characteristic of The Geneva Learning Foundation’s model to support work-based learning.
Watch the General Assembly of the Nigeria Immunization Collaborative on 6 August 2024
https://www.youtube.com/watch?v=zicqexzachA
What are health workers saying about the Collaborative?
For Mariam Mustapha, a participant from Kano State, the Collaborative is “multiple individuals that perform a task”, united around a shared purpose.
She highlighted the importance of engaging with community members, noting, “These people from the community, most of them, they don’t have enough knowledge or they are receiving misinformation about immunization and vaccines.”
The peer learning exercise employed a structured approach, asking participants to explain their immunization challenge, conduct a “5 Whys” analysis to identify root causes, and develop actionable plans within their scope of work.
How does the Collaborative help health workers?
This method proved enlightening for many participants.
John Emmanuel, a community health worker from Bauchi State, shared his experience: “I just discovered that over the years, I have been superficial in my approach. I’ve been one sided. I’ve been actually peripheral in my approach. So during the root cause analysis, I was able to identify the broader perspective of identifying the challenge and then fixing it as it affects my job here in the community.”
The Collaborative also fostered connections between health workers across different regions of Nigeria.
Mohammed Nasir Umar, a JSI HPV program associate in Zamfara State, noted the value of this cross-pollination of ideas: “The root cause analysis really widened my horizon on how I think around the challenges. The ‘5 Whys’ techniques approach was really, really helpful.”
Participants identified a range of immunization challenges, including vaccine hesitancy, lack of information and awareness, sociocultural and religious factors, reaching zero-dose children, incomplete immunization, healthcare worker issues, logistical challenges, political interference, poor documentation, and community trust issues.
But then each one started asking ‘why’, stopping only once they found a root cause that they are in a position to do something about.
Esther Sharma, working with NPHCDA in a local government area, identified a critical issue in her facility: “The reason why people turn out low for immunization is because there are no health workers in the facilities to attend to them when they get here.”
Her solution involves ensuring consistent staffing during immunization days, which should encourage more community members to seek vaccination services.
How are new stakeholders participating in the Collaborative?
The Collaborative also welcomed participation from organizations not traditionally involved in immunization services.
Angela Emmanuel, a nurse and founder of the Emmanuel Cancer Foundation in Lagos, found value in the exercise for her work on HPV vaccination and cancer prevention.
She emphasized the need for a more educational approach: “Our motive should be education. Our motive should be the awareness, not just asking them to take this vaccine.”
Chijioke Kaduru, a public health physician who served as a Guide for the Collaborative, reflected: “While some of these challenges are similar in many settings, the local context and the nuances that shape these challenges clearly make them a good opportunity to engage, to interact, to understand them better, and to start to also see the ideas that colleagues have about how to solve those problems.”
By connecting frontline health workers, fostering critical thinking, and encouraging the development of locally-tailored solutions, the Nigeria Immunization Collaborative represents a potentially scalable model for strengthening health systems and improving immunization coverage.
As the exercise concludes, participants are poised to implement their action plans in their respective communities.
How are government workers participating in the Collaborative?
A key focus of the final session was the presentation of root cause analyses by government workers from the Federal and State Primary Health Care Development Agencies.
These presentations provided valuable insights into the challenges faced at various levels of the health system and the innovative solutions being developed.
Maimuna Tata, a deputy in-charge at a health facility in Bunkura local government area of Kano State, presented her analysis of why routine immunization sessions were not being conducted at her facility.
Through her “5 Whys” analysis, she uncovered a systemic issue: “The health facility is newly built and was commissioned after the 2024 micro plan exercise and needs to undergo several processes for provision of routine immunization.”
Tata’s proposed solution demonstrated the kind of innovative thinking the Collaborative aimed to foster: “Instead of them coming for outreach session in the settlement, I think the vaccine should be channeled to the health facility so that the health facility can conduct the sessions. And at the end of the day, we will now be submitting our reports to the health facility, that is the model health facility, pending the time the health facility will be recorded or will be updated in the server.”
Esther Sharma, working with NPHCDA in a local government area, identified a critical staffing issue: “The reason why people turn out low for immunization is because there are no health workers in the facilities to attend to them when they get here. I am the routine immuunization focal person where I currently work and when I went there newly, I asked a lot of people, why don’t they come to the hospital for immunization? And they said when they come, they don’t find anybody to attend to them.”
Her solution involves ensuring consistent staffing during immunization days, which she reported has already encouraged more community members to seek vaccination services.
Image: The Geneva Learning Foundation Collection © 2024
Share this:
#Collaborative #ImmunizationAgenda2030 #learningCulture #Nigeria #NPHCDA #peerLearning #rootCauseAnalysis #socialLearning #TheGenevaLearningFoundation
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Experience-sharing sessions in the Movement for Immunization Agenda 2030: A novel approach to localize global health collaboration
As immunization programs worldwide struggle to recover from pandemic disruptions, the Movement for Immunization Agenda 2030 (IA2030) offers a novel, practitioner-led approach to accelerate progress towards global vaccination goals.
From March to June 2022, the Geneva Learning Foundation (TGLF) conducted the first Full Learning Cycle (FLC) of the Movement for IA2030, engaging 6,185 health professionals from low- and middle-income countries.
A cornerstone of this programme was a series of 44 experience-sharing sessions held between 7 March and 13 June 2022. These sessions brought together between 20 and 400 practitioners per session to discuss and solve real-world immunization challenges.
IA2030 case study 16, by Charlotte Mbuh and François Gasse, offers valuable insights from these experience-sharing session:
- what we learned from the experiences themselves and how it can help practitioners; and
- what we learned about the significance and potential of the peer learning process itself.
Download the full case study: IA2030 Case study 16. Continuum from knowledge to performance. The Geneva Learning Foundation.
For every challenge shared during the experience sharing sessions, there was always at least one member who had encountered or was encountering the same challenge and had carried out measures to resolve it.
These sessions provided a space to share practical stories that are making a difference – and supported participants in considering their relevance to their own situations.
Experience sharing also helped build confidence and motivation.
Members were able to identify with experiences shared, realizing they were not alone in facing similar challenges.
The sessions covered a wide range of critical immunization topics.
For instance, a participant from Nigeria discussed strategies for reaching zero-dose children in Borno state.
Facing the challenge of reaching approximately 600,000 unvaccinated children, the presenter received practical suggestions from peers, including developing a zero-dose reduction operational plan, leveraging new vaccine introductions, and partnering with the private sector for evening vaccination services.
In another session, a subnational Ministry of Health staff member from Côte d’Ivoire presented challenges related to cross-border immunization campaigns.
Peers shared experiences of organizing cross-border meetings to identify unvaccinated children, synchronize efforts, and involve community representatives in the process.
Such context-specific, experience-based advice exemplifies the unique value of peer learning in addressing complex health system challenges.
The case study of 44 sessions highlights how these sessions fostered multiple types of learning simultaneously.
Participants reported learning from each other’s experiences, experiencing the power of solving problems together across distances, feeling a growing sense of belonging to a community, and connecting across country borders and health system levels.
A district-level Ministry of Health staff member from Ghana encapsulated the impact: “I have linked up with expert vaccinators worldwide through experience sharing and twinning. I have become more competent and knowledgeable in the area of immunization, and work confidently.”
This sentiment was echoed by many participants who found value not only in acquiring new knowledge but also in expanding their professional networks and gaining confidence in their problem-solving abilities.
The case study also reveals the adaptability of the approach in responding to unique contexts.
This resilience underscores the potential of digital platforms to democratize access to expertise and foster global collaboration.
However, the study also identifies areas for improvement.
- Participants expressed a desire for more follow-up support and opportunities to continue their peer learning groups beyond the initial sessions.
- Additionally, the need for better integration of community engagement strategies was identified as a key area for future development.
To contextualize these findings, we can turn to a 2022 study by Watkins et al., which evaluated a prototype of these experience-sharing sessions known as Immunization Training Challenge Hackathons (ITCH), conducted in 2020.
The ITCH methodology, developed by The Geneva Learning Foundation (TGLF), informed the design of the 2022 IA2030 Movement sessions.
Watkins et al. found that the ITCH approach fostered four simultaneous types of learning: peer, remote, social, and networked.
- Peer Learning: This involves participants learning directly from each other’s experiences and knowledge. In the context of immunization, imagine a scenario where a vaccination program manager from rural India shares their successful strategy for improving vaccine cold chain management with a colleague facing similar challenges in sub-Saharan Africa. This direct exchange of practical, context-specific knowledge can complement more theoretical training, as it is based on real-world application.
- Remote Learning: This refers to the ability to learn and solve problems collaboratively across geographical distances. For an immunization specialist, this might seem counterintuitive, as many believe that hands-on, in-person training is essential. However, the ITCH sessions demonstrated that meaningful learning can occur remotely. For example, a team in Bangladesh could describe their approach to overcoming vaccine hesitancy, and a team in Nigeria could immediately adapt and apply those strategies to their local context, all without the need for costly and time-consuming travel.
- Social Learning: This concept emphasizes the importance of learning within a network. In the immunization field, professionals often work in isolation, especially at sub-national levels. The ITCH sessions created a sense of belonging to a global network, community, and platform of immunization practitioners. This social aspect can boost motivation, reduce feelings of isolation, and foster a collective approach to problem-solving that transcends individual or even national boundaries.
- Networked Learning: This type of learning emerges from connections made across different levels of health systems and across country borders. For an epidemiologist, this might be analogous to how disease surveillance networks function across borders. In the ITCH context, it means that a district-level immunization officer could learn from and share ideas with national-level policymakers from other countries, fostering a more holistic understanding of immunization challenges and solutions.
These four types of learning operate simultaneously during ITCH sessions, creating a synergistic effect.
For instance, a participant might learn a new cold chain management technique (peer learning) from a colleague in another country (remote learning), feel supported by the global community in implementing this new technique (social learning), and then share their adaptation of this technique with others across various levels of the health system (networked learning).
From an epidemiological perspective, this approach to learning could be compared to how we understand disease transmission and intervention effectiveness.
Just as multiple factors contribute to disease spread and control, these multiple learning types contribute to knowledge dissemination and capacity building in the immunization field.
The value of this approach lies in its potential to rapidly disseminate practical, context-specific knowledge and solutions across a global network of immunization professionals.
This can lead to faster adoption of best practices, more innovative problem-solving, and ultimately, improvements in immunization program performance that could contribute to better disease control outcomes.
While this approach may seem unconventional compared to traditional training methods in the immunization field, the evidence presented by Watkins et al. suggests that it can be a powerful complement to existing capacity-building efforts, particularly in resource-constrained settings where access to formal training opportunities may be limited.
This multifaceted approach allowed participants to not only acquire new knowledge but also to expand their professional networks and gain confidence in their problem-solving abilities—findings that align closely with the outcomes observed in the 2022 IA2030 Movement sessions.
The Watkins study emphasized the importance of building confidence and motivation through peer learning experiences, a theme strongly echoed in the Mbuh case study.
Furthermore, Watkins et al. highlighted the potential of this approach to create a “space of possibility” for innovation and problem-solving, which is evident in the diverse and creative solutions shared during the 2022 sessions.
Both studies underscore the significance of peer-led, digital learning experiences in accelerating progress towards global health goals.
By fostering peer learning and digital collaboration, these approaches empower health workers to turn global strategies into effective local action.
References
Mbuh, C., Gasse, F., Jones, I., Sadki, R., Brooks, A., Zha, M., Steed, I., Sequeira, J., Churchill, S., Kovanovic, V., 2022. IA2030 Case study 16. Continuum from knowledge to performance. The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.7014392
Watkins, K.E., Sandmann, L.R., Dailey, C.A., Li, B., Yang, S.-E., Galen, R.S., Sadki, R., 2022. Accelerating problem-solving capacities of sub-national public health professionals: an evaluation of a digital immunization training intervention. BMC Health Serv Res 22, 736. https://doi.org/10.1186/s12913-022-08138-4
Image: The Geneva Learning Foundation Collection © 2024
Share this:
#CharlotteMbuh #continuousLearning #FrançoisGasse #FullLearningCycle #IA2030 #IA2030CaseStudies #ImmunizationAgenda2030 #ITCH #KarenEWatkins #learningCulture #MovementForImmunizationAgenda2030 #networkedLearning #peerLearning #remoteLearning #TheGenevaLearningFoundation
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The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.
In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.
Imagine a digital platform intended to train health workers at scale.
Their theory of change rests on a few key assumptions:
- Offering simplified, mobile-friendly courses will make training more accessible to health workers.
- Incorporating videos and case studies will keep learners engaged.
- Quizzes and knowledge checks will ensure learning happens.
- Certificates, continuing education credits, and small incentives will motivate course completion.
- Growing the user base through marketing and partnerships is the path to impact.
On the surface, this seems sensible.
Mobile optimization recognizes health workers’ technological realities.
Multimedia content seems more engaging than pure text.
Assessments appear to verify learning.
Incentives promise to drive uptake.
Scale feels synonymous with success.
While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.
This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.
It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.
It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.
It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.
Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.
Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.
Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.
They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.
A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.
The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.
This view is not only paternalistic and insulting, but it is also fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.
Health workers may dutifully click through courses, but genuine transformative learning remains elusive.
The alternative lies in a learning agenda grounded in advances of the last three decades learning science.
These advances remain largely unknown or ignored in global health.
This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.
It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.
It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.
It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.
Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.
Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/06/30/learn-health-but-beware-of-the-behaviorist-trap/
#behaviorism #eLearning #healthTraining #HealthLearn #HRH #HumanResourcesForHealth #learningCulture #learningStrategy #workforceDevelopment
-
The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.
In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.
Imagine a digital platform intended to train health workers at scale.
Their theory of change rests on a few key assumptions:
- Offering simplified, mobile-friendly courses will make training more accessible to health workers.
- Incorporating videos and case studies will keep learners engaged.
- Quizzes and knowledge checks will ensure learning happens.
- Certificates, continuing education credits, and small incentives will motivate course completion.
- Growing the user base through marketing and partnerships is the path to impact.
On the surface, this seems sensible.
Mobile optimization recognizes health workers’ technological realities.
Multimedia content seems more engaging than pure text.
Assessments appear to verify learning.
Incentives promise to drive uptake.
Scale feels synonymous with success.
While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.
This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.
It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.
It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.
It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.
Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.
Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.
Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.
They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.
A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.
The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.
This view is not only paternalistic and insulting, but it is also fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.
Health workers may dutifully click through courses, but genuine transformative learning remains elusive.
The alternative lies in a learning agenda grounded in advances of the last three decades learning science.
These advances remain largely unknown or ignored in global health.
This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.
It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.
It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.
It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.
Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.
Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/06/30/learn-health-but-beware-of-the-behaviorist-trap/
#behaviorism #eLearning #healthTraining #HealthLearn #HRH #HumanResourcesForHealth #learningCulture #learningStrategy #workforceDevelopment
-
The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.
In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.
Imagine a digital platform intended to train health workers at scale.
Their theory of change rests on a few key assumptions:
- Offering simplified, mobile-friendly courses will make training more accessible to health workers.
- Incorporating videos and case studies will keep learners engaged.
- Quizzes and knowledge checks will ensure learning happens.
- Certificates, continuing education credits, and small incentives will motivate course completion.
- Growing the user base through marketing and partnerships is the path to impact.
On the surface, this seems sensible.
Mobile optimization recognizes health workers’ technological realities.
Multimedia content seems more engaging than pure text.
Assessments appear to verify learning.
Incentives promise to drive uptake.
Scale feels synonymous with success.
While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.
This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.
It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.
It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.
It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.
Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.
Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.
Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.
They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.
A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.
The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.
This view is not only paternalistic and insulting, but it is also fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.
Health workers may dutifully click through courses, but genuine transformative learning remains elusive.
The alternative lies in a learning agenda grounded in advances of the last three decades learning science.
These advances remain largely unknown or ignored in global health.
This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.
It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.
It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.
It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.
Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.
Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/06/30/learn-health-but-beware-of-the-behaviorist-trap/
#behaviorism #eLearning #healthTraining #HealthLearn #HRH #HumanResourcesForHealth #learningCulture #learningStrategy #workforceDevelopment
-
The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.
In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.
Imagine a digital platform intended to train health workers at scale.
Their theory of change rests on a few key assumptions:
- Offering simplified, mobile-friendly courses will make training more accessible to health workers.
- Incorporating videos and case studies will keep learners engaged.
- Quizzes and knowledge checks will ensure learning happens.
- Certificates, continuing education credits, and small incentives will motivate course completion.
- Growing the user base through marketing and partnerships is the path to impact.
On the surface, this seems sensible.
Mobile optimization recognizes health workers’ technological realities.
Multimedia content seems more engaging than pure text.
Assessments appear to verify learning.
Incentives promise to drive uptake.
Scale feels synonymous with success.
While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.
This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.
It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.
It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.
It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.
Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.
Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.
Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.
They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.
A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.
The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.
This view is not only paternalistic and insulting, but it is also fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.
Health workers may dutifully click through courses, but genuine transformative learning remains elusive.
The alternative lies in a learning agenda grounded in advances of the last three decades learning science.
These advances remain largely unknown or ignored in global health.
This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.
It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.
It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.
It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.
Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.
Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/06/30/learn-health-but-beware-of-the-behaviorist-trap/
#behaviorism #eLearning #healthTraining #HealthLearn #HRH #HumanResourcesForHealth #learningCulture #learningStrategy #workforceDevelopment
-
The global health community has long grappled with the challenge of providing effective, scalable training to health workers, particularly in resource-constrained settings.
In recent years, digital learning platforms have emerged as a potential solution, promising to deliver accessible, engaging, and impactful training at scale.
Imagine a digital platform intended to train health workers at scale.
Their theory of change rests on a few key assumptions:
- Offering simplified, mobile-friendly courses will make training more accessible to health workers.
- Incorporating videos and case studies will keep learners engaged.
- Quizzes and knowledge checks will ensure learning happens.
- Certificates, continuing education credits, and small incentives will motivate course completion.
- Growing the user base through marketing and partnerships is the path to impact.
On the surface, this seems sensible.
Mobile optimization recognizes health workers’ technological realities.
Multimedia content seems more engaging than pure text.
Assessments appear to verify learning.
Incentives promise to drive uptake.
Scale feels synonymous with success.
While well-intentioned, such a platform risks falling into the trap of a behaviorist learning agenda.
This is an approach that, despite its prevalence, is a pedagogical dead-end with limited potential for driving meaningful, sustained improvements in health worker performance and health outcomes.
It is a paradigm that views learners as passive recipients of information, where exposure equals knowledge acquisition.
It is a model that privileges standardization over personalization, content consumption over knowledge creation, and extrinsic rewards over intrinsic motivation.
It fails to account for the rich diversity of prior experiences, contexts, and challenges that health workers bring to their learning.
Most critically, it neglects the higher-order skills – the critical thinking, the adaptive expertise, the self-directed learning capacity – that are most predictive of real-world performance.
Clicking through screens of information about neonatal care, for example, is not the same as developing the situational judgment to adapt guidelines to a complex clinical scenario, nor the reflective practice to continuously improve.
Moreover, the metrics typically prioritized by behaviorist platforms – user registrations, course completions, assessment scores – are often vanity metrics.
They create an illusion of progress while obscuring the metrics that truly matter: behavior change, performance improvement, and health outcomes.
A health worker may complete a generic course on neonatal care, for example, but this does not necessarily translate into the situational judgment to adapt guidelines to complex clinical scenarios, nor the reflective practice to continuously improve.
The behaviorist paradigm’s emphasis on information transmission and standardized content may stem from an implicit assumption that health workers at the community level do not require higher-order critical thinking skills – that they simply need a predetermined set of knowledge and procedures.
This view is not only paternalistic and insulting, but it is also fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
Even if such a platform achieves its growth targets, it is unlikely to realize its impact goals.
Health workers may dutifully click through courses, but genuine transformative learning remains elusive.
The alternative lies in a learning agenda grounded in advances of the last three decades learning science.
These advances remain largely unknown or ignored in global health.
This approach positions health workers as active, knowledgeable agents, rich in experience and expertise.
It designs learning experiences not merely to transmit information, but to foster critical reflection, dialogue, and problem-solving.
It replaces generic content with authentic, context-specific challenges, and isolated study with collaborative sense-making in peer networks.
It recognizes intrinsic motivation – the desire to grow, to serve, to make a difference – as the most potent driver of learning.
Here, success is measured not in superficial metrics, but in meaningful outcomes: capacity to lead change in facilities and communities that leads to tangible improvements in the quality of care.
Global health leaders faces a choice: to settle for the illusion of progress, or to invest in the deep, difficult work of authentic learning and systemic change, commensurate with the complexity and urgency of the task at hand.
Image: The Geneva Learning Foundation Collection © 2024
https://redasadki.me/2024/06/30/learn-health-but-beware-of-the-behaviorist-trap/
#behaviorism #eLearning #healthTraining #HealthLearn #HRH #HumanResourcesForHealth #learningCulture #learningStrategy #workforceDevelopment
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Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.
Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.
In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:
“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone] has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”
https://youtube.com/live/uvv-g0lXy4c
In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”
https://youtube.com/live/nCB20y49hBI
However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.
When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.
They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.
The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.
Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.
This view is fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.
Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.
They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.
To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.
By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.
We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.
The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.
It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.
By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.
Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.
By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.
This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.
It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.
It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.
Image: The Geneva Learning Foundation Collection © 2024
#adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning
-
Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.
Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.
In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:
“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone] has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”
https://youtube.com/live/uvv-g0lXy4c
In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”
https://youtube.com/live/nCB20y49hBI
However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.
When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.
They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.
The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.
Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.
This view is fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.
Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.
They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.
To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.
By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.
We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.
The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.
It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.
By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.
Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.
By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.
This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.
It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.
It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.
Image: The Geneva Learning Foundation Collection © 2024
#adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning
-
Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.
Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.
In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:
“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone] has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”
https://youtube.com/live/uvv-g0lXy4c
In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”
https://youtube.com/live/nCB20y49hBI
However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.
When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.
They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.
The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.
Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.
This view is fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.
Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.
They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.
To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.
By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.
We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.
The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.
It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.
By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.
Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.
By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.
This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.
It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.
It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.
Image: The Geneva Learning Foundation Collection © 2024
#adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning
-
Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.
Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.
In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:
“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone] has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”
https://youtube.com/live/uvv-g0lXy4c
In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”
https://youtube.com/live/nCB20y49hBI
However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.
When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.
They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.
The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.
Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.
This view is fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.
Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.
They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.
To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.
By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.
We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.
The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.
It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.
By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.
Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.
By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.
This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.
It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.
It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.
Image: The Geneva Learning Foundation Collection © 2024
#adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning
-
Many health leaders are highly analytical, adaptive learners who thrive on solving complex problems in dynamic, real-world contexts.
Their expertise is grounded in years of field experience, where they have honed their ability to rapidly generate insights, test ideas, and innovate solutions in collaboration with diverse stakeholders.
In January 2021, as countries were beginning to introduce new COVID-19 vaccines, Kate O’Brien, who leads WHO’s immunization efforts, connected global learning to local action:
“For COVID-19 vaccines […] there are just too many lessons that are being learned, especially according to different vaccine platforms, different communities of prioritization that need to be vaccinated. So [everyone] has got to be able to scale, has got to be able to deal with complexity, has got to be able to do personal, local innovation to actually overcome the challenges.”
https://youtube.com/live/uvv-g0lXy4c
In an Insights Live session with the Geneva Learning Foundation in 2022, she made a compelling case that “the people who are working in the program at that most local level have to be able to adapt, to be agile, to innovate things that will work in that particular setting, with those leaders in the community, with those families.”
https://youtube.com/live/nCB20y49hBI
However, unlike Kate O’Brien, some senior leaders in global health disconnect their own learning practices and their assumptions about how others learn best.
When it comes to designing learning initiatives for their teams or organizations, these leaders may default to a more simplistic, behaviorist approach.
They may equate learning with the acquisition and application of specific skills or knowledge, and thus focus on creating structured, content-driven training programs.
The appeal of behaviorist platforms – with their promise of efficient, scalable delivery and easily measured outcomes – can be seductive in the resource-constrained, results-driven world of global health.
Furthermore, leaders may hold assumptions that health workers – especially those at the community level – do not require higher-order critical thinking skills, that they simply need a predetermined set of knowledge and procedures.
This view is fundamentally misguided.
A robust body of scientific evidence on learning culture and performance demonstrates that the most effective organizations are those that foster continuous learning, critical reflection, and adaptive problem-solving at all levels.
Health workers at the frontlines face complex, unpredictable challenges that demand situational judgment, creative thinking, and the ability to learn from experience.
Failing to cultivate these capacities not only underestimates the potential of these health workers, but it also constrains the performance and resilience of health systems as a whole.
The problem is that this approach fails to cultivate the very qualities that make these leaders effective learners and problem-solvers.
Behaviorist techniques, with their emphasis on passive information absorption and narrow, pre-defined outcomes, do not foster the critical thinking, creativity, and collaborative capacity needed to tackle complex health challenges.
They may produce short-term gains in narrow domains, but they cannot develop the adaptive expertise required for long-term impact in ever-shifting contexts.
To help health leaders recognize this disconnect, it is useful to engage them in reflective dialogue about their own learning processes.
By unpacking real-world examples of how they have solved thorny problems or generated novel insights, we can highlight the sophisticated cognitive strategies and collaborative dynamics at play.
We can show how they constantly question assumptions, synthesize diverse perspectives, and iterate solutions – all skills that are essential for navigating complexity, but are poorly served by rigid, content-focused training.
The goal is not to dismiss the need for foundational knowledge or skills, but rather to emphasize that in the face of evolving challenges, adaptive learning capacity is the real differentiator.
It is the ability to think critically, to imagine new possibilities, to learn from failure, and to co-create with others that drives meaningful change.
By tying this insight directly to leaders’ own experiences and values, we can inspire them to champion learning approaches that mirror the richness and dynamism of their personal growth journeys.
Ultimately, the most impactful health organizations will be those that not only equip people with essential skills, but that also nurture the underlying cognitive and collaborative capacities needed to continually learn, adapt, and innovate.
By recognizing and leveraging the powerful learning practices they themselves embody, health leaders can shape organizational cultures and strategies that truly empower people to navigate complexity and drive transformative change.
This shift requires letting go of the illusion of control and predictability that behaviorism offers, and instead embracing the messiness and uncertainty of real learning.
It means creating space for experimentation, reflection, and dialogue, and trusting in people’s inherent capacity to grow and create.
It is a challenging transition, but one that health leaders are uniquely positioned to lead – if they can bridge the gap between how they learn and how they seek to enable others’ learning.
Image: The Geneva Learning Foundation Collection © 2024
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#adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning
