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47 results for “redasadki”

  1. Reda Sadki @[email protected] ·

    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:

    1. Move beyond knowledge verification to value validation.
    2. Recognize that local health workers are not the problem to be fixed but the owners of the solution.
    3. Utilize the existing workforce rather than parallel structures.
    4. 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

    Model 1: The academic MOOC model (MalariaX)

    Model 2: The normative cascade model and incentives

    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)

    Strategic recommendations and value validation

    #globalHealth #globalMalariaEliminationAgenda #HRH #learningCulture #learningStrategy #malaria #workforceDevelopment
    #workforcedevelopment #malaria #learningstrategy #learningculture #hrh #globalmalariaeliminationagenda
  2. Reda Sadki @[email protected] ·

    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:

    1. Move beyond knowledge verification to value validation.
    2. Recognize that local health workers are not the problem to be fixed but the owners of the solution.
    3. Utilize the existing workforce rather than parallel structures.
    4. 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

    Model 1: The academic MOOC model (MalariaX)

    Model 2: The normative cascade model and incentives

    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)

    Strategic recommendations and value validation

    #globalHealth #globalMalariaEliminationAgenda #HRH #learningCulture #learningStrategy #malaria #workforceDevelopment
    #globalhealth #globalmalariaeliminationagenda #hrh #learningculture #learningstrategy #malaria
  3. Reda Sadki @[email protected] ·

    A survey of learners on a large, authoritative global health learning platform has me pondering once again the perils of relying too heavily on learner preferences when designing educational experiences.

    One survey question intended to ask learners for their preferred learning method.

    The list of options provided includes a range of items.

    (Some would make the point that the list conflates learning resources and learning methods, but let us leave that aside for now.)

    Respondents’ top choices (source) were videos, slides, and downloadable documents.

    At first glance, this seems perfectly reasonable.

    After all, should we not give learners what they want?

    As it happens, the main resources offered by this platform are videos, slides, and other downloadable documents.

    (If we asked learners who participate in our peer learning programmes for their preference, they would likely say that they prefer… peer learning.)

    Beyond this availability bias, there is a more significant problem with this approach: learner preferences often have little correlation with actual learning outcomes.

    And learners are especially bad at self-evaluating what learning methods and resources are most conducive to effective learning.

    The scientific literature is quite clear on this point.

    Bjork’s 2013 article on self-regulated learning emphatically states that: “learners are often prone to illusions of competence during learning, and these illusions can be remarkably compelling.”

    The study by Deslauriers et al. (2019) provides a compelling demonstration that while students express a strong preference for traditional lectures over active learning methods, they actually learn significantly more from the active approaches they claim to dislike.

    This disconnect between preference and efficacy is not surprising when we consider how learning actually works.

    Effective learning requires effort, struggle, and sometimes discomfort as we grapple with new ideas and challenge our existing mental models.

    It is not always an enjoyable process in the moment, even if the long-term results are deeply rewarding.

    Furthermore, learners (like all of us) are subject to various cognitive biases that can lead them astray when evaluating their own learning.

    The illusion of explanatory depth, for example, can cause us to overestimate how well we understand a topic after passively consuming information about it.

    None of this is to say we should ignore learner perspectives entirely.

    Motivation and engagement do matter for learning.

    But we need to be thoughtful about how we solicit and interpret learner feedback.

    Asking about preferences for specific content formats (videos, slides, etc.) tells us very little about the actual learning activities and cognitive processes involved.

    A more productive approach might be to focus on understanding learners’ goals, challenges, and contexts.

    What are they trying to achieve?

    What obstacles do they face?

    What constraints shape their learning environment?

    With this information, we can design evidence-based learning experiences that truly meet their needs – even if they don’t always match their stated preferences.

    As learning professionals, our job is not to give learners what they think they want.

    It is to create the conditions for transformative learning experiences that expand their capabilities and perspectives.

    This often means pushing learners out of their comfort zones and challenging their assumptions about how learning should look and feel.

    Bjork, R. A., Dunlosky, J., & Kornell, N. (2013). Self-regulated learning: Beliefs, techniques, and illusions. Annual Review of Psychology, 64, 417-444. https://doi.org/10.1146/annurev-psych-113011-143823

    Deslauriers, L., McCarty, L.S., Miller, K., Callaghan, K., Kestin, G., 2019. Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences 201821936. https://doi.org/10.1073/pnas.1821936116

    https://redasadki.me/2024/06/30/why-asking-learners-what-they-want-is-a-recipe-for-confusion/

    #globalHealth #learningMethods #learningStrategy #learningStyles

    #globalhealth #learningmethods #learningstrategy #learningstyles
  4. Reda Sadki @[email protected] ·

    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:

    1. Offering simplified, mobile-friendly courses will make training more accessible to health workers.
    2. Incorporating videos and case studies will keep learners engaged.
    3. Quizzes and knowledge checks will ensure learning happens.
    4. Certificates, continuing education credits, and small incentives will motivate course completion.
    5. 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

    #behaviorism #elearning #healthtraining #healthlearn #hrh #humanresourcesforhealth
  5. Reda Sadki @[email protected] ·

    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

    https://redasadki.me/2024/06/30/why-health-leaders-who-are-critical-thinkers-choose-rote-learning-for-others/

    #adaptiveLearning #coCreation #criticalThinking #healthLearning #immunization #ImmunizationAgenda2030 #KateOBrien #leadership #learningCulture #learningStrategy #peerLearning

    #adaptivelearning #cocreation #criticalthinking #healthlearning #immunization #immunizationagenda2030
  6. Reda Sadki @[email protected] ·

    Continuous learning is lacking in immunization.

    This lack may be an underestimated barrier to the “Big Catch-Up” and finding zero-dose children

    This was a key finding presented at Gavi’s Zero-Dose Learning Hub (ZDLH) webinar “Equity in Action: Local Strategies for Reaching Zero-Dose Children and Communities” on 24 January 2024.

    The finding is based on analysis large-scale measurements conducted by the Geneva Learning Foundation in 2020 and 2022, with more than 10,000 immunization staff from all levels of the health system, job categories, and contexts, responding from over 90 countries.

    YearnContinuous learningDialogue & InquiryTeam learningEmbedded SystemsEmpowered PeopleSystem ConnectionStrategic Leadership202038303.614.68–4.814.685.104.83202261853.764.714.864.934.725.234.93TGLF learning culture and performance global measurements (2020 and 2022) uising the Dimensions of Learning Organization Questionnaire (DLOQ)

    What does this finding actually mean?

    In immunization, the following gaps in continuous learning are likely to be hindering performance.

    1. Relatively few learning opportunities for immunization staff
    2. Limitations on the ability for staff to experiment and take risks 
    3. Low tolerance for failure when trying something new
    4. A focus on completing immunization tasks rather than developing skills and future capacity
    5. Lack of encouragement for on-the-job learning 

    This gap hurts more than ever when adapting strategies to reach “zero-dose” children.

    These are children who have not been reached when immunization staff carry out what they usually do.

    The traditional learning model is one in which knowledge is codified into lengthy guidelines that are then expected to trickle down from the national team to the local levels, with local staff competencies focused on following instructions, not learning, experimenting, or preparing for the future.

    For many immunization staff, this is the reference model that has helped eradicate polio, for example, and to achieve impressive gains that have saved millions of children’s lives.

    It can therefore be difficult to understand why closing persistent equity gaps and getting life-saving vaccines to every child would now require transforming this model.

    Yet, there is growing evidence that peer learning and experience sharing between health workers does help surface creative, context-specific solutions tailored to the barriers faced by under-immunized communities. 

    Such learning can be embedded into work, unlike formal training that requires staff to stop work (reducing performance to zero) in order to learn.

    Yet the predominant culture does little to motivate or empower these workers to recognize or reward such work-based learning.

    Furthermore, without opportunities to develop skills, try new approaches, and learn from both successes and failures, staff may become demotivated and ineffective. 

    This is not an argument to invest in formal training.

    Investment in formal training has failed to measurably translate into improved immunization performance.

    Worse, the per diem economy of extrinsic incentives for formal training has, in some places, led to absurdity: some health workers may earn more by sitting in classrooms than from doing their work.

    With a weak culture of learning, the system likely misses out on practices that make a difference.

    This is the “how” that bridges the gap between best practice and what it takes to apply it in a specific context.

    The same evidence also demonstrates a consistently-strong correlation between strengthened continuous learning and performance.

    Investment in continuous learning is simple, costs surprisingly little given its scalability and effectiveness.

    Calculating the relative effectiveness of expert coaching, peer learning, and cascade training

    How does the scalability of peer learning compare to expert-led coaching ‘fellowships’?

    That means investment in continuous learning is already proven to result in improved performance.

    We call this “learning-based work”.

    References

    Watkins, K.E. and Marsick, V.J., 2023. Chapter 4. Learning informally at work: Reframing learning and development. In Rethinking Workplace Learning and Development. Edward Elgar Publishing. Excerpt: https://redasadki.me/2023/11/04/how-we-reframed-learning-and-development-learning-based-complex-work/

    The Geneva Learning Foundation. From exchange to action: Summary report of Gavi Zero-Dose Learning Hub inter-country exchanges. Geneva: The Geneva Learning Foundation, 2023. https://doi.org/10.5281/zenodo.10132961

    The Geneva Learning Foundation. Motivation, Learning Culture and Immunization Programme Performance: Practitioner Perspectives (IA2030 Case Study 7) (1.0); Geneva: The Geneva Learning Foundation, 2022. https://doi.org/10.5281/zenodo.7004304

    Image: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/03/03/why-lack-of-continuous-learning-is-the-achilles-heel-of-immunization/

    #continuousLearning #DLOQ #Gavi #immunization #KarenEWatkins #learningCulture #performance #TheBigCatchUp #zeroDoseChildren #ZeroDoseLearningHubZDLH_

    #continuouslearning #dloq #gavi #immunization #karenewatkins #learningculture
  7. Reda Sadki @[email protected] ·

    By connecting practitioners to learn from each other, peer learning facilitates collaborative development.

    How does it compare to expert-led coaching and mentoring “fellowships” that are seen as the ‘gold standard’ for professional development in global health?

    Scalability in global health matters. (See this article for a comparison of other aspects.)

    Simplified mathematical modeling can compare the scalability of expert coaching (“fellowships”) and peer learning

    Let N be the total number of learners and M be the number of experts available. Assuming that each expert can coach K learners effectively:

    For N>>M×KN>>M×K, it is evident that expert coaching is costly and difficult to scale.

    Expert coaching “fellowships” require the availability of experts, which is often optimistic in highly specialized fields.

    The number of learners (N) greatly exceeds the product of the number of experts (M) and the capacity per expert (K).

    Scalability of one-to-one peer learning

    By comparison, peer learning turns the conventional model on its head by transforming each learner into a potential coach who can provide peer feedback.

    This has significant advantages in scalability.

    Let N be the total number of learners. Assuming a peer-to-peer model, where each learner can learn from any other learner:

    In this context, the number of learning interactions scales quadratically with the number of learners. This means that if the number of learners doubles, the total number of learning interactions increases by a factor of four. This quadratic relationship highlights the significant increase in interactions (and potential scalability challenges) as more learners participate in the model.

    However, this one-to-one model is difficult to implement: not every learner is going to interact with every other learner in meaningful ways.

    A more practical ‘triangular’ peer learning model with no upper limit to scalability

    In The Geneva Learning Foundation’s peer learning model, learners give feedback to three peers, and receive feedback from three peers. This is a structured, time-bound process of peer review, guided by an expert-designed rubric.

    When each learner gives feedback to 3 different learners and receives feedback from 3 different learners, the model changes significantly from the one-to-one model where every learner could potentially interact with every other learner. In this specific configuration, the total number of interactions can be calculated based on the number of learners N, with each learner being involved in 6 interactions (3 given + 3 received).

    The total number of interactions per learner is six. However, since each interaction involves two learners (the giver and the receiver of feedback), we do not need to double-count these interactions for the total count in the system. Hence, the total number of interactions for each learner is directly 6, without further adjustments for double-counting.

    Therefore, the total number of learning interactions in the system can be represented as:

    Given this setup, the complexity or scalability of the system in terms of learning interactions relative to the number of participants N is linear. This is because the total number of interactions increases directly in proportion to the number of learners. Thus, the Big O notation would be:

    This indicates that the total number of learning interactions scales linearly with the number of learners. In this configuration, as the number of learners increases, the total number of interactions increases at a linear rate, which is more scalable and manageable than the quadratic rate seen in the peer-to-peer model where every learner interacts with every other learner. Learn more: There is no scale.

    Illustration: The Geneva Learning Foundation © 2024

    https://redasadki.me/2024/02/28/how-does-peer-learning-compare-to-expert-led-coaching-fellowships/

    #coaching #CollectiveIntelligence #fellowships #globalHealth #mathematicalModeling #peerLearning

    #coaching #collectiveintelligence #fellowships #globalhealth #mathematicalmodeling #peerlearning
  8. Reda Sadki @[email protected] ·

    A formula for calculating learning efficacy, (E), considering the importance of each criterion and the specific ratings for peer learning, is:

    This abstract formula provides a way to quantify learning efficacy, considering various educational criteria and their relative importance (weights) for effective learning.

    Variable DefinitionDescription SScalabilityAbility to accommodate a large number of learners IInformation fidelityQuality and reliability of information CCost effectivenessFinancial efficiency of the learning method FFeedback qualityQuality of feedback received UUniformityConsistency of learning experience Summary of five variables that contribute to learning efficacy

    Weights for each variables are derived from empirical data and expert consensus.

    All values are on a scale of 0-4, with a “4” representing the highest level.

    ScalabilityInformation fidelityCost-benefitFeedback qualityUniformity4.003.004.003.001.00Assigned weights

    Here is a summary table including all values for each criterion, learning efficacy calculated with weights, and Efficacy-Scale Score (ESS) for peer learning, cascade training, and expert coaching.

    The Efficacy-Scale Score (ESS) can be calculated by multiplying the efficacy (E) of a learning method by the number of learners (N).

    This table provides a detailed comparison of the values for each criterion across the different learning methods, the calculated learning efficacy values considering the specified weights, and the Efficacy-Scale Score (ESS) for each method.

    Type of learningScalabilityInformation fidelityCost effectivenessFeedback qualityUniformityLearning efficacy# of learnersEfficacy-Scale ScorePeer learning4.002.504.002.501.003.2010003200Cascade training2.001.002.000.500.501.40500700Expert coaching0.504.001.004.003.002.2060132

    Of course, there are many nuances in individual programmes that could affect the real-world effectiveness of this simple model. The model, grounded in empirical data and simplified to highlight core determinants of learning efficacy, leverages statistical weighting to prioritize key educational factors, acknowledging its abstraction from the multifaceted nature of educational effectiveness and assumptions may not capture all nuances of individual learning scenarios.

    Peer learning

    The calculated learning efficacy for peer learning, , is 3.20. This value reflects the weighted assessment of peer learning’s strengths and characteristics according to the provided criteria and their importance.

    By virtue of scalability, ESS for peer learning is 24 times higher than expert coaching.

    Cascade training

    For Cascade Training, the calculated learning efficacy, , is approximately 1.40. This reflects the weighted assessment based on the provided criteria and their importance, indicating lower efficacy compared to peer learning.

    Cascade training has a higher ESS than expert coaching, due to its ability to achieve scale.

    Learn more: Why does cascade training fail?

    Expert coaching

    For Expert Coaching, the calculated learning efficacy, , is approximately 2.20. This value indicates higher efficacy than cascade training but lower than peer learning.

    However, the ESS is the lowest of the three methods, primarily due to its inability to scale. Read this article for a scalability comparison between expert coaching and peer learning.

    Image: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/02/27/calculating-the-relative-effectiveness-of-expert-coaching-peer-learning-and-cascade-training/

    #cascadeTraining #expertCoaching #fellowship #mathematicalModeling #peerLearning

    #cascadetraining #expertcoaching #fellowship #mathematicalmodeling #peerlearning
  9. Reda Sadki @[email protected] ·

    Cascade training remains widely used in global health.

    Cascade training can look great on paper: an expert trains a small group who, in turn, train others, thereby theoretically scaling the knowledge across an organization.

    It attempts to combine the advantages of expert coaching and peer learning by passing knowledge down a hierarchy.

    However, despite its promise and persistent use, cascade training is plagued by several factors that often lead to its failure.

    This is well-documented in the field of learning, but largely unknown (or ignored) in global health.

    What are the mechanics of this known inefficacy?

    Here are four factors that contribute to the failure of cascade training

    1. Information loss

    Consider a model where an expert holds a knowledge set K. In each subsequent layer of the cascade, α percentage of the knowledge is lost:

    • Where is the knowledge at the nth level of the cascade. As n grows, exponentially decreases, leading to severe information loss.
    • Each layer in the cascade introduces a potential for misunderstanding the original information, leading to the training equivalent of the ‘telephone game’.

    2. Lack of feedback

    In a cascade model, only the first layer receives feedback from an actual expert.

    • Subsequent layers have to rely on their immediate ‘trainers,’ who might not have the expertise to correct nuanced mistakes.
    • The hierarchical relationship between trainer and trainee is different from peer learning, in which it is assumed that everyone has something to learn from others, and expertise is produced through collaborative learning.

    3. Skill variation

    • Not everyone is equipped to teach others.
    • The people who receive the training first are not necessarily the best at conveying it to the next layer, leading to unequal training quality.

    4. Dilution of responsibility

    • As the cascade flows down, the sense of responsibility for the quality and fidelity of the training dilutes.
    • The absence of feedback to drive a quality development process exacerbates this.

    Image: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/02/26/why-does-cascade-training-fail/

    #cascadeTraining #learningScience #pedagogy

    #cascadetraining #learningscience #pedagogy
  10. Reda Sadki @[email protected] ·

    Here is a summary of the key points from the article “Nobody ever gets credit for fixing problems that never happened: creating and sustaining process improvement”.

    Overview

    • Many companies invest heavily in process improvement programs, yet few efforts actually produce significant results. This is called the “improvement paradox”.
    • The problem lies not with the specific tools, but rather how the introduction of new programs interacts with existing organizational structures and dynamics.
    • Using system dynamics modeling, the authors studied implementation challenges in depth through over a dozen case studies. Their models reveal insights into why improvement programs often fail.

    Core causal loops

    • The “Work Harder” loop – managers pressure people to spend more time working to immediately boost throughput and close performance gaps. But this is only temporary.
    • The “Work Smarter” loop – managers encourage improvement activities which enhance process capability over time for more enduring gains, but there is a delay before benefits are seen.
    • The “Reinvestment” reinforcing loop – successfully improving capability frees up more time for further improvement. But the reverse vicious cycle often dominates instead.
    • The “Shortcuts” loop – facing pressure, people cut corners on improvement activities which temporarily frees up more time for work. But this gradually erodes capability.

    The capability trap

    • Short-term “Work Harder” and “Shortcuts” decisions eventually hurt capability and require heroic work efforts to maintain performance, creating a downward spiral.
    • However, because capability erodes slowly, managers fail to connect problems to past decisions and blame poor worker motivation instead, leading to a self-confirming cycle.
    • Even improvement programs just increase pressure and drive more shortcuts, making stereotypes and conflicts worse. This “capability trap” causes programs to fail.

    The “capability trap” refers to the downward spiral organizations can get caught in, where attempting to boost performance by pressuring people to “work harder” actually erodes process capability over time. This trap works through a few key mechanisms:

    1. Facing pressure, people cut corners and reduce time spent on improvement activities in order to free up more time for immediate work. This temporarily boosts throughput.
    2. However, this comes at a cost of gradually declining process capability, as less time is invested in maintenance, training, and problem solving.
    3. Capability erosion then reduces performance, widening the gap versus desired performance levels.
    4. Managers falsely attribute this to poor motivation or effort from the workforce. They lack awareness of the capability trap dynamics, and the delays between pressing people to “work harder” and the capability declines that eventually ensue.
    5. Management increases pressure further, demanding heroic work efforts, which causes workers to cut even more corners. This spirals capability downward while confirming management’s incorrect attribution even more.

    Key takeaway for learning leaders

    Learning leaders must understand the systemic traps identified in the article that underly failed improvement initiatives and facilitate mental model shifts. This help build sustainable, effective learning programs to be realized through productive capability-enhancing cycles.

    Key takeaway for immunization leaders

    It’s reasonable to hypothesize that poor health worker performance is a symptom rather than the cause of poor immunization programme performance. Short-term decisions, often responding to top-down targets and donor requirements, hurt capability and require, as the authors say, “heroic work efforts to maintain performance, creating a downward spiral.” Managers then incorrectly diagnose this as a performance problem due to motivation.

    How to escape the capability trap

    The key to avoiding or escaping this trap is therefore shifting the mental models that reinforce the incorrect attributions about motivation. Some ways to do this include:

    • Educating managers on the systemic structures causing the capability trap through methods like system dynamics modeling
    • Allowing time for capability-enhancing improvements to take effect before judging performance
    • Incentivizing quality and sustainability of throughput rather than just short-term volume alone
    • Seeking input from workers on the barriers to improvement they face

    With awareness of the structural causes and delays, managers can avoid erroneously attributing blame. Patience and a systems perspective are critical for companies to invest their way out of the capability trap.

    • Shift mental models to recognize system structures leading to the capability trap, rather than blaming people. Then improvement tools can work.
    • A useful example could be system dynamics workshops that achieved this shift and enabled successful programs, dramatically enhancing performance.

    Reference: Repenning, N.P., Sterman, J.D., 2001. Nobody ever gets credit for fixing problems that never happened: creating and sustaining process improvement. California management review 43, 64–88.

    Illustration: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/02/23/the-capability-trap-nobody-ever-gets-credit-for-fixing-problems-that-never-happened/

    #capabilityDevelopment #HR #processImprovement #TotalQualityManagement

    #capabilitydevelopment #hr #processimprovement #totalqualitymanagement
  11. Reda Sadki @[email protected] ·

    In the article “Towards reimagined technical assistance: the current policy options and opportunities for change”, Alexandra Nastase and her colleagues argues that technical assistance should be framed as a policy option for governments. It outlines different models of technical assistance:

    1. Capacity substitution: Technical advisers perform government functions due to urgent needs or lack of in-house expertise. This can fill gaps but has “clear limitations in building state capability.”
    2. Capacity supplementation: Technical advisers provide specific expertise to complement government efforts in challenging areas. This can “fill essential gaps at critical moments” but has limitations for building sustainable capacity.  
    3. Capacity development: Technical advisers play a facilitator role focused on enabling change and strengthening government capacity over the long term. This takes time but “there is a higher chance that these [results] will be sustainable.”

    Governments may choose from this spectrum of roles for technical advisers in designing assistance programs based on the objectives, limitations, and tradeoffs involved with each approach: “The most common fallacy is to expect every type of technical assistance to lead to capacity development. We do not believe that is the case. Suppose governments choose to use externals to do the work and replace government functions. In that case, it is not realistic to expect that it will build a capability to do the work independently of consultants.”

    Furthermore, technical assistance should be designed through “meaningful and equal dialogue between governments and funders” to ensure it focuses on core issues and builds sustainable capacity. Considerations that need to be highlighted include balancing short-term needs with long-term capacity building and shifting power to local experts.

    However, this requires reframing technical assistance as a policy option through transparent dialogue between government and funders.

    What key assumptions about technical assistance does this challenge?

    The article challenges some key assumptions and orthodox views about technical assistance in global health:

    1. It frames technical assistance not as aid provided by donors, but as a policy option and domestic choice that governments make to meet their objectives. This contrasts with the common donor-centric view.
    2. It critiques the assumption that all technical assistance inherently builds sustainable government capacity and questions this expected linear relationship. The article argues different types of technical assistance have fundamentally different aims – gap-filling versus long-term capacity building.
    3. The article challenges the idealistic principles often promoted for technical assistance, like localization, government ownership, and adaptability. It suggests the evidence is lacking on if these principles effectively lead to better development outcomes on the ground.  
    4. The article argues that technical assistance decisions involve real dilemmas, tradeoffs and tensions in practice rather than being clear cut. It challenges the notion of win-win solutions and highlights risks like unintended consequences.
    5. By outlining limitations of different technical assistance approaches, the article pushes back against a one-size-fits-all mindset. The appropriate approach depends on contextual factors and clarity of purpose.
    6. The article questions typical measures of success for technical assistance based on fast results and output delivery. It advocates for greater focus on processes that enable long-term capacity development even if slower.

    How does The Geneva Learning Foundation’s work fit into such a model?

    At The Geneva Learning Foundation (TGLF), we realized that our own model to support locally-led leadership to drive change could be described as a new type of technical assistance that does not fit into any of the existing three categories, because:

    1. TGLF’s model is grounded in principles of localization and decolonization that shift power dynamics by empowering government health workers from all levels of the health system – not only the national authorities – to recognize what change is needed, to lead this change where they work. We have observed that, even in fragile contexts, this accelerates progress toward country goals, and strengthens or can help rebuild civil society fabric.
    2. It focuses on nurturing intrinsic motivation and peer accountability rather than imposing top-down directives or extrinsic incentives. 
    3. It utilizes lateral feedback loops and informal, self-organized networks that cut across hierarchies and geographic boundaries.
    4. It emphasizes flexibility, adaptation to local contexts, and problem-driven iteration rather than pre-defined solutions.
    5. It builds sustainable capacity and self-organized learning cultures that reduce dependency on external support.

    Reference: Nastase, A., Rajan, A., French, B., Bhattacharya, D., 2020. Towards reimagined technical assistance: the current policy options and opportunities for change. Gates Open Res 4, 180. https://doi.org/10.12688/gatesopenres.13204.1

    Illustration: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/02/13/towards-reimagined-technical-assistance-thinking-beyond-the-current-policy-options/

    #capacityBuilding #DAC #decolonization #globalHealth #policy #rethinkingAid #technicalAssistance

    #capacitybuilding #dac #decolonization #globalhealth #policy #rethinkingaid
  12. Reda Sadki @[email protected] ·

    The severe global shortage of health and care workers poses a dangerous threat to health systems, especially in low- and middle-income countries (LMICs). The authors of the article “Prioritising the health and care workforce shortage: protect, invest, together”, including six health ministers and the WHO Director-General, assert that this workforce crisis requires urgent action and propose “protect, invest, together” to tackle it.

    Deep protection of the existing workforce, they assert, is needed through improved working conditions, fair compensation, upholding rights, addressing discrimination and violence, closing gender inequities, and implementing the WHO Global Health and Care Worker Compact to ensure dignified working environments. All countries must prioritize retaining workers to build resilient health systems.

    Significantly increased and strategic long-term investments are imperative in both training new health workers through educational channels and sustaining their employment. Countries should designate workforce development, especially at the primary care level, as crucial human capital investments impacting population health outcomes. Intersectoral financing is key, bringing together domestic funds, grants, concessional sources, and private sector partners into coordinated national plans. Global solidarity is required to resource-constrained LMIC health workforces.

    Intersectoral collaboration between ministries of health, finance, economic development, education and employment can develop integrated health workforce strategies. South-South partnerships offer pathways for health worker training and mobility to address regional shortages. Small island nations confront severe but overlooked workforce obstacles requiring specially tailored policy approaches.

    The severe projected health workforce shortfall urgently necessitates that actors globally protect existing health workers, strategically invest in growing national workforces, and unite intersectorally behind robust health employment systems, especially in lower resourced contexts. As the authors emphasize, “there can be no health, health systems, or emergency response without the health and care workforce.”

    What about the role of education?

    This article does not provide much direct discussion of health education systems related to the global health workforce shortage. However, it makes the following relevant points:

    1. Chronic underinvestment in the health and care workforce, including in education and training, has contributed to long-standing shortages.
    2. There is a need for strategic investments in health and care worker education and lifelong learning, with a focus on primary health care, to help address shortages.
    3. Investments in standalone health infrastructure will have little effect unless matched by investments in developing the health workforce through education and training.
    4. Increasing, smarter and sustained long-term financing is crucial for health and care worker education and employment.
    5. Regional and subregional collaboration should be explored to bring together resources and capacities for health workforce education and training.
    6. Intersectoral collaboration between health, education, finance and other sectors is important for developing policies and making investments in health workforce education.

    Read more to understand what this means for health education: Protect, invest, together: strengthening health workforce through new learning models

    Reference: Agyeman-Manu et al. Prioritising the health and care workforce shortage: protect, invest, together. The Lancet Global Health (2023). https://doi.org/10.1016/S2214-109X(23)00224-3

    Illustration: The Geneva Learning Foundation Collection © 2024

    https://redasadki.me/2024/02/12/prioritizing-the-health-and-care-workforce-shortage-protect-invest-together/

    #globalShortage #HRH #HumanResourcesForHealth #workforce

    #globalshortage #hrh #humanresourcesforhealth #workforce
  13. Reda Sadki @[email protected] ·

    In their 2014 article, Jacobson, Kapur, and Reimann propose shifting the paradigm of learning theory towards the conceptual framework of complexity science. They argue that the longstanding dichotomy between cognitive and situative theories of learning fails to capture the intricate dynamics at play. Learning arises across a “bio-psycho-social” system involving interactive feedback loops linking neuronal processes, individual cognition, social context, and cultural milieu. As such, what emerges cannot be reduced to any individual component.

    To better understand how macro-scale phenomena like learning manifest from micro-scale interactions, the authors invoke the notion of “emergence” prominent in the study of complex adaptive systems. Discrete agents interacting according to simple rules can self-organize into sophisticated structures through across-scale feedback.

    For instance, the formation of a traffic jam results from the cumulative behavior of individual drivers. The jam then constrains their ensuing decisions.

    Similarly, in learning contexts, the construction of shared knowledge, norms, values and discourses proceeds through local interactions, which then shape future exchanges. Methodologically, properly explicating emergence requires attending to co-existing linear and non-linear dynamics rather than viewing the system exclusively through either lens.

    By adopting a “trees-forest” orientation that observes both proximal neuronal firing and distal cultural evolution, researchers can transcend outmoded dichotomies. Beyond scrutinizing whether learner or environment represents the more suitable locus of analysis, the complex systems paradigm directs focus towards their multifaceted transactional synergy, which gives rise to learning. This avoids ascribing primacy to any single level, as well as positing reductive causal mechanisms, instead elucidating circular self-organizing feedback across hierarchically nested systems.

    The implications are profound. Treating learning as emergence compels educators to appreciate that curricular inputs and pedagogical techniques designed based upon linear extrapolation will likely yield unexpected results. Our commonsense notions that complexity demands intricacy fail to recognize that simple nonlinear interactions generate elaborate outcomes. This epistemic shift suggests practice should emphasize creating conditions conducive for adaptive growth rather than attempting to directly implant mental structures. Specifically, adopting a complexity orientation may entail providing open-ended creative experiences permitting self-guided exploration, establishing a learning culture that values diversity, dissent and ambiguity as catalysts for sensemaking, and implementing distributed network-based peer learning.

    Overall, the article explores how invoking a meta-theory grounded in complex systems science can dissolve dichotomies that have plagued the field. It compels implementing flexible, decentralized and emergent pedagogies far better aligned to the nonlinear complexity of learner development in context.

    Sophisticated learning theories often fail to translate into meaningful practice. Yet what this article describes closely corresponds to how The Geneva Learning Foundation (TGLF) is actually implementing its vision of education as a philosophy for change, in the face of complex threats to our societies. The Foundation conceives of learning as an emergent phenomenon arising from interactions between individuals, their social contexts, and surrounding systems. Our programs aim to catalyze this emergence by connecting practitioners facing shared challenges to foster collaborative sensemaking. For example, our Teach to Reach events connect tens of thousands of health professionals to share experience on their own terms, in relation to their own contextual needs. This emphasis on open-ended exploration and decentralized leadership exemplifies the flexible pedagogy demanded by a complexity paradigm. Overall, the Foundation’s work – deliberately situated outside the constraints of vestigial Academy – embodies the turn towards nonlinear models that can help transcend stale dichotomies. Our practice demonstrates the concrete value of recasting learning as the product of embedded agents interacting to generate systemic wisdom greater than their individual contributions.

    Jacobson, M.J., Kapur, M., Reimann, P., 2014. Towards a complex systems meta-theory of learning as an emergent phenomenon: Beyond the cognitive versus situative debate. Boulder, Colorado: International Society of the Learning Sciences.

    Illustration © The Geneva Learning Foundation Collection (2024)

    https://redasadki.me/2024/01/31/education-as-a-system-of-systems-rethinking-learning-theory-to-tackle-complex-threats-to-our-societies/

    #complexLearning #dichotomies #emergence #MichaelJJacobson #systemsTheory

    #complexlearning #dichotomies #emergence #michaeljjacobson #systemstheory
  14. Reda Sadki @[email protected] ·

    The Geneva Learning Foundation’s Charlotte Mbuh spoke today at the COP28 Health Pavilion in Dubai, United Arab Emirates (UAE). Learn more…

    Good afternoon. I am Charlotte Mbuh. I have worked for the health of children and families in Cameroon for over 15 years.

    I am one of more than 5,500 health workers from 68 countries who have connected to share our observations of how climate is affecting the health of those we serve. 

    “Going back home to the community where I grew up as a child, I was shocked to see that most of the rivers we used to swim and fish in have all dried up, and those that are still there have become very shallow so that you can easily walk through a river you required a boat to cross in years past.”

    These are the words of Samuel Chukwuemeka Obasi, a health worker from Nigeria.

    Dr Kumbha Gopi, a health worker from India said: “The use of motor vehicles has led to an increase in air pollution and we see respiratory problems and skin diseases”.

    Climate change is hurting the health of those we serve. And it is getting worse.

    Few here would deny that health workers are an essential voice to listen to in order to understand climate impacts on health.

    Yet, a man named Jacob on social media snapped: “Since when are health workers the authority on air pollution?”

    Here are the words of Bie Lilian Mbando, a health worker from my country: “Where I live in Buea, the flood from Mount Cameroon took away all belongings of people in my neighborhood and killed a secondary school student who was playing football with his friends.”

    Climate change is killing communities.

    Cecilia Nabwirwa, a nurse in Nairobi, Kenya: “I remember my grand-son getting sick after eating vegetables grown along areas flooded by sewage. Since then I resolved to growing my own vegetables to ensure healthy eating.”

    And yet, another man on social media, Robert, found this “ridiculous. As if my friend who sells fish at his fish stall comes as an expert on water quality.”

    I wondered: why such brutal responses?

    Well, unlike scientists or global agencies, we cannot be dismissed as “experts from on-high”.

    What we know, we know because we are here every day.

    We are part of the community.

    And we know that climate change is a threat to the health of the communities we serve.

    We are already having to manage the impacts of climate change on health.

    We are doing the best that we can.

    But we need your support.

    The global community is investing in building a new scientific field around climate and health.

    Massive investments are also being made in policy.

    Are we making a commensurate investment in people and communities?

    That should mean investing in health workers.

    What will happen if this investment is neglected?

    What if big global donors say: “it’s important, but it’s not part of our strategy?”

    Well, in 5, 10, or 15 years, we will certainly have much improved science and, hopefully, policy.

    Yet, some communities might reject better science and policy.

    Will the global community then wonder: “Why don’t they know what’s good for them?” 

    I am an immunization worker. For over 15 years, I have worked for my country’s ministry of health.

    Like my colleagues from all over the world, I know more than a little about what it takes to establish and maintain trust.

    Trust in vaccination, trust in public health.

    Trust that by standing together in the face of critical threats to our societies, we all stand to do better.

    Local communities in the poorest countries are already bearing the brunt of climate change effects on health.

    Local solutions are needed.

    Health workers are trusted advisors to the communities we serve.

    With every challenge, there is an opportunity.

    On 28 July 2023, 4,700 health workers began learning from each other through the Geneva Learning Foundation’s platform, community, and network.

    Thousands more are connecting with each other, because they choose to.

    And because they want to take action.

    It is our duty to support them.

    In March 2024, we will hold the tenth Teach to Reach conference.

    The last edition reached over 17,000 health workers from more than 80 countries.

    This time, our focus will be on climate and health.

    We invite global partners to join, to listen and to learn.

    We invite you to consider how you, your organization, your government might support action by health workers on the frontline.

    Because we will rise.

    As health workers, with or without your support, we will continue to stand up with courage, compassion and commitment, working to lift up our communities.

    Our perseverance calls us all to press forward towards climate justice and health equity.

    I wish to challenge us, as a global community, to rise together, so that  the voices of those on the frontline of climate change will be at the next Conference of Parties.

    By standing together, we all stand to do better.

    Thank you.

    https://redasadki.me/2023/12/11/climate-and-health-health-workers-trust/

    #CharlotteMbuh #climate #climateCrisis #COP28 #Dubai #health #healthWorkforce #HRH

    #charlottembuh #climate #climatecrisis #cop28 #dubai #health
  15. Reda Sadki @[email protected] ·

    Samuel Chukwuemeka Obasi, a health professional from Nigeria:

    “Going back home to the community where I grew up as a child, I was shocked to see that most of the rivers we used to swim and fish in have all dried up, and those that are still there have become very shallow so that you can easily walk through a river you required a boat to cross in years past.”

    In July 2023, more than 1200 health workers from 68 countries shared their experiences of changes in climate and health, at a unique event designed to shed light on the realities of climate impacts on the health of the communities they serve.

    Before, during and after COP28, we are sharing health workers’ observations and insights.

    Follow The Geneva Learning Foundation to learn how climate change is affecting health in multiple ways:

    • How extreme weather events can lead to tragic loss of life.
    • How changing weather patterns are leading to crop failures and malnutrition, and forcing people to abandon their homes.
    • How infectious diseases are surging as mosquitoes proliferate and water sources are contaminated.
    • How climate stresses are particularly problematic for those with existing health conditions, like cardiovascular disease and diabetes.
    • How climate impacts are having a devastating effect on mental health as people’s ways of life are destroyed.
    • How climate change is changing the very fabric of society, driving displacement and social hardship that undermines health and wellbeing.
    • How a volatile climate is disrupting the delivery of essential health services and people’s ability to access them.
    • We will finish the series with  inspiring stories of how health workers are already responding to such challenges, working with communities to counter the effects of a changing climate.

    On 1 December 2023, TGLF will be publishing a compendium and analysis of these 1200 contributions – On the frontline of climate change and health: A health worker eyewitness report. Get the report…

    This landmark report – a global first – kickstarts our campaign to ensure that health workers in the Global South are recognized as:

    • The people already having to manage the impacts of climate change on health.
    • An essential voice to listen to in order to understand climate impacts on health.
    • A potentially critical group to work with to protect the health of communities in the face of a changing climate.

    Before, during, and after COP28, we are advocating for the recognition and support of health workers as trusted advisers to communities bearing the brunt of climate change effects on health.

    https://redasadki.me/2023/11/29/before-during-and-after-cop28-climate-crisis-and-health-through-the-eyes-of-health-workers-from-africa-asia-and-latin-america/

    #climate #climateChange #communities #COP28 #health #healthWorkers #HRH #leadership

    #climate #climatechange #communities #cop28 #health #healthworkers
  16. Reda Sadki @[email protected] ·

    The following is excerpted from Watkins, K.E. and Marsick, V.J., 2023. Chapter 4. Learning informally at work: Reframing learning and development. In Rethinking Workplace Learning and Development. Edward Elgar Publishing.

    This chapter’s final example illustrates the way in which organically arising IIL (informal and incidental learning) is paired with opportunities to build knowledge through a combination of structured education and informal learning by peers working in frequently complex circumstances.

    Reda Sadki, president of The Geneva Learning Foundation (TGLF), rethought L&D for immunization workers in many roles in low- and middle-income countries (LMICs).

    Adapting to technology available to participants from the countries that joined this effort, Sadki designed a mix of experiences that broke out of the limits of “training” as it was often designed.

    He addressed, the inability to scale up to reach large audiences; difficulty to transfer what is learned; inability to accommodate different learners’ starting places; the need to teach learners to solve complex problems; and the inability to develop sufficient expertise in a timely way. (Marsick et al., 2021, p. 15)

    TGLF invited learners to create and share new learning to the social and behavioral challenges faced by front-line staff from all levels of immunization systems in low- and middle-income countries (LMICs).

    Sadki designed L&D for “in-depth engagement on priority topics,” insights into “the raw, unfiltered perspectives of frontline staff,” and peer dialogue that “gives a voice to front-line workers” (The Geneva Learning Foundation, 2022).

    Reda started with an e-learning course, which he supplemented by interactive, community building, and knowledge creation features offered by Scholar, a learning platform developed by Bill Cope and Mary Kalantzis (Marsick et al., 2021, pp. 185-186).

    Scholar’s data analytics enabled him to tailor learning to learner preferences and to continually check outcomes and adjust next steps.

    See Figure 4.3, which lays out the full learning cycle Reda implemented to support peer learning-based work—“work that privileges learning in order to build individual and organizational capacity to better address emergent challenges or opportunities” (Marsick et al., 2021, p.177).

    In his initiative, over a period of 12-18 months, participants develop and implement projects related to local immunization initiatives.

    To date, participants have come from 120 countries.

    In this vignette, Reda Sadki reflects on how the approach evolved over time, and how L&D has changed in a connected, networked learning environment.

    My reframe of L&D started when I wrote to Bill Cope and Mary Kalantzis, respectively professor and dean of the University of Illinois College of Education, after I was appointed Senior Officer for Learning Systems at the International Federation of Red Cross and Red Crescent Societies (IFRC). I shared my strategy for the organization of facilitation, learning, and sharing of knowledge. I thought my strategy was brilliant.

    They replied that these were interesting ideas, but I was missing the point because this is not learning. What I shared focused on publishing knowledge in different ways, but not on creation of knowledge as key to the learning process.

    That was a shock to me.

    So, the first realization about the limits of current thinking about L&D came from Bill and Mary challenging me by saying: “What are people actually getting to do? You know, that’s where the learning is likely to happen.”

    I could see they had a point, but I didn’t know what it meant.

    I reflected on recent work I had done for the IFRC, where I was responsible for a pipeline of 80 or so e-learning modules.

    These information transmission modules were extremely limited, had very little impact.

    But there is a paradox, which is that people across the Red Cross who we were trying to reach were really excited and enthusiastic about them.

    The learning platform had become the fastest-growing digital system in the entire Red Cross Red Crescent movement.

    I had not designed these modules.

    It was 500 screens of information with quizzes at the end.

    It violated every principle of learning design.

    And yet people loved it and were really proud to have completed it.

    The second realization was that what made people excited using the most boring format and medium was that this was the first time in their life that they were connecting in a digital space with something that spoke to their IFRC experience.

    So, the driver was learning. People come to the Red Cross and Red Crescent because they want to learn first aid skills.

    They want to learn how to prepare for a disaster or recover from one.

    Previously, that was an entirely brick-and-mortar experience.

    You have Red Cross branches pretty much everywhere in the world.

    It’s a very powerful social peer learning experience.

    The trainer teaching you first aid is likely to be someone like you from your community.

    You meet people with like-minded values.

    It’s a really powerful model.

    And so, however inadequate, the digital parallel to that existed, and ti helped people connect with their Red Cross culture, but in the digital space.

    The third insight was reading what George Siemens was writing in 2006.

    That was the connection to complexity in networks.

    I read Marsick and Watkins in the ’80s and ’90s, and then Siemens in the 2000s, on digital networks.

    The Internet leads to a different kind of thinking, and his theory of learning, connectivism, grew out of that difference.

    January of 201, Ivy League universities began to publish massive open online courses (MOOCs).

    Stanford professors had 150,000 people in their artificial intelligence MOOC, versus 400 people who take the same course on the Stanford campus.

    Sasha Poquet is developing a paper (still being written as of November 2023) based on a social networking analysis of what we did during the COVID-19 Scholar Peer Hub.

    The COVID-19 Scholar Peer Hub was a digital network hosted by The Geneva Learning Foundation (TGLF) and developed with health worker alumni from all over the world.

    The Peer Hub launched in July 2020 and connected over 6,000 health professionals from 86 countries to contribute to strengthening skills and supporting implementation of country COVID-19 plans of action.

    Using social network analysis (SNA), Poquet explored the value of a learning environment that builds a community of learning professionals, and that has ongoing activities to maintain the community both short- and long term, where you educate through various initiatives rather than create individual communities for each independent offering.

    That’s where we have moved in rethinking Learning & Development.

    You help people learn by connecting to each other, and by understanding the informal, incidental nature of learning.

    A colleague commented that in today’s world, you’re better of talking about digital networks than you are about communities of practice.

    Yet these are two competing frameworks that collide, contradict, and are superimposed on top of each other.

    Both are helpful at specific times.

    In general, you can recognize the tensions and say: “Well, let’s put each one in front of the problem. Let’s see what we gain by applying each. Let’s reconcile in situ what the contradictory things are that we learn through these different lenses and then make decisions and figure out what the design elements look like.”

    What does it give to hold these notions of community and network in creative tension with one another?

    It depends on the context.

    It’s kind of like a fruit salad where you mix all these fruits together and the juice you get at the bottom of the bowl tends to be really delicious. That’s the best case.

    The flip side can be confusion.

    Some categories of learners just feel completely overwhelmed by being presented with multiple ways of doing something, having to make their own decisions in ways they’re simply not used to, being given too many choices or being put in contexts that are too ambiguous for there to be an easy resolution.

    But if you think about the skills we need in a digital age—for navigating the unknown, accepting uncertainty, making decisions, that ability to look around the corner—we try to convey the message to people who are uncomfortable that if they don’t figure out how to overcome their discomfort, they’re probably going to struggle and not be ready to function in the age in which we live.

    Evolution of the Model

    Looking back to early 2020, Reda described the roots of this approach in an early pre-course symposium offering lived experiences shared by course applicants combined with video archives drawn from prior conferences sponsored by the Bill & Melinda Gates Foundation.

    Reda packaged selected talks in a daily sequence, and interspersed it with networking discussions and sharing of experiences of immunization training by field-based practitioners.

    For many, it was the first time they could go online and discover the experience of a peer, who could be from anywhere in the world.

    It was a process of discovery – realizing you can literally and figuratively connect across distance with people who are like yourself.

    We were able to create a conference-like experience, a metaphor that’s familiar to many—the combination of presentation and conversation and shared experience – by basically Scotch-taping together some older videos and editing a few stories from the real world.

    Now, it was part of an overall process over several years that got us to that point—where we had formed a community, a digital community that was mature enough, that was sophisticated enough, to overcome the barriers they were facing and participate.

    But still, it showed it could be done.

    We began to try out our new ideas.

    In a Teach to Reach Conference we designed with an organizing committee composed of over 500 alumni, we set up opportunities for people to pair of and talk to one another about their field experiences with vaccination.

    The conference offered some 56 workshops and formal sessions, but we discovered that the most meaningful learning was through some 14,000 networking meetings, where you pressed a button and you were randomly matched with someone else at the conference.

    That gave birth to a quarterly event dedicated entirely to such networking, which has continued to grow.

    People now joing a group session where you discuss, you hear people sharing their insights and experiences of vaccine hesitancy, and then you go off and network in one-to-one, private meetings and share your experience, nourished by what happened in that group session; and also continue your learning in that very intimate way that you get through individual conversation that you don’t get in the anonymization of the Zoom rectangles.

    The next step was the addition of a project around a real problem that participants face, and use of learning resources to support work on that project.

    An evaluation showed that people were already implementing projects and doing things with what they had learned.

    The course includes the development of an action plan, but in order to catalyze action on project plans, we added the Ideas Engine, where people share ideas and practices, and give and receive feedback on them.

    That’s followed by situation analysis really getting to the root cause of the problem they’re facing. We just ask learners to ask “why” fives times. Half of learners found a root cause different from the one they had initially diagnosed.

    And third, then, is action planning to clarify: What’s your goal? What are three corrective actions you’re going to take? Do you have specific, measurable goals?

    It has taken years to bring together the right components, in the right sequence, to encourage reflective practice, develop analytical competencies, higher-order learning… but in ways that link every step of thinking to doing, and where the end game is about improved health outcomes, not just learning outcomes.

    That led us ultimately to the Impact Accelerator—that doesn’t have an end point.

    It’s four weeks of goal setting, focused on continuous quality improvement.

    People initially set broad goals like, “By the end of the month I will have improved immunization coverage.” This is too broad to be useful, and seldom can be achieved within a month.

    We help them set specific goals. For example: “By the end of the month, I will have presented the project to my boss and secured some funding”— and even that may be very ambitious.

    We help people figure out for themselves what they can actually do within the constraints they have.

    Unlike “Grand Challenges” or other innovation tournaments, you don’t have a competitive element, you don’t have a financial incentive, and it still works.

    The heart and soul of it is intrinsic motivation.

    After these steps there’s ongoing longitudinal reporting.

    Peer learning provides a new kind of accountability, as colleagues challenge each other to do better – and also to present credible results.

    Basically, we’ll call you back and ask, what happened to that project you were doing? Did you finish it? Did you get stuck? if so, why? What evidence do you have that it’s made a difference? You share that with us and if you have good news to share, we’ll probably invite you to an inspirational event for the next cycle.

    Supports and Challenges

    If you look at this from the point of view of the learner, the first point of contact is social.

    It’s somebody they know who’s going to share with them on WhatsApp the invitation to join the program.

    Second are steps that test motivation and commitment because they could be seen as barriers to entry, for example, a long questionnaire for the current full learning cycle.

    Close to 7,000 people have completed that.

    About 40% of people who start the questionnaire finish it, and then start receiving instructions in a flow of emails, to prepare for the next steps.

    We start with didactic steps, combined with some inspirational messages, e.g., asking them to reflect on why they are committed to the program, or how they are going to organize their time.

    We don’t know what the program design will look like until we’ve collected the applications and analyzed what people share about their biggest challenges because it’s all challenge-based.

    We think it’s vaccine hesitancy, and vaccine hesitancy is right up there, but there may be some things that surprise us.

    And so, we adapt every part of the design, and we keep doing that every day throughout the program, so there’s no disconnect between the design and the implementation.

    In the course, the first thing is an inspirational event to connect with their intrinsic motivation, which we mobilize throughout the cycle.

    Yesterday, for example, we had an event for the network that completed the first part of the full learning cycle.

    We challenged people to share photos, showing them in the field, doing their daily work during World Immunization Week.

    We got over 1,000 photos in about two weeks.

    We shared this with the community in a live event that was just sharing the photos with music and reading the names of the people, inviting them to comment each other’s photos.

    A big chunk of what we do addresses the affective domain of learning that is critical to complex problem-solving and usually incredibly hard to get to.

    And what we saw were people in the room having those moments of coming to consciousness, realizing their problems are shared, and feeling stronger because of it.

    People love peer learning in principle but still are wary.

    They might wonder how they can trust what their peer says: What’s the proof I can rely on them? What happens if they let me down? How do I feel if I don’t own up to the expectations? What if I’m peer-reviewing the work of somebody who’s far more experienced than I am, or conversely, if I read somebody’s work and judge they didn’t have the time or make the effort to do something good?

    We use didactic constraints to create spaces of possibility: If your project is due by Friday, we announce that there will be no extension. By contrast, the choice of project is yours.

    We’re not going to tell you from Geneva, Switzerland, what your challenge is in your remote village, so you define it. We will challenge you to put yourself to the test, to demonstrate that this is actually your toughest challenge.

    Or to demonstrate that what you think is the cause is the actual root cause.

    And then we’ll have a support system that has about 20 different ways in which people can not only receive support, but also give it to others.

    For the technical support session, we’ll say there are two reasons for joining. Either you have a technical issue you want to solve; or you’re doing so well, you have a little bit of time to give to help your colleagues. 

    This is an example of how we encourage connections between peers. It took us years to find the right way to formulate the dialectic between those who are doing well, and those who are not. Are they really peers?

    Over time, we gained confidence in peer learning after we adopted it. We had a particularly challenging course that led to a breakthrough.

    We had prior experiences with learners who wanted an expert to tell them if their assignment was good or not.

    Getting people to trust peer learning forced us to think through how we articulate the value of peer learning.

    How do we help people understand that the limitations are there, but that they do not limit the learning? An assumption in global health is that, in order to teach, you need technical expertise. So if you are a technical expert, it is assumed that you can teach what you know.

    We consider subject matter expertise, but if you are an expert and come to our event, you’re actually asked to listen.

    You do not get to make a presentation, at least not until learners have experienced the power of peer leraning.

    You listen to what people are sharing about their experiences, and then you have a really important role, that is, to respond to what you’ve heard and demonstrate that your expertise is relevant and helpful to people who are facing these challenges.

    That has sometimes led to opposition when people understand to what extent we flipped the prevailing model around.

    Some people really embrace it.

    Others get really scared.

    One of the most recent shifts we have made is that we stopped talking about courses.

    Courses are a very useful metaphor, but we are now talking about a movement for immunization.

    In the past, we observed that people who dropped out felt shame and stopped participating.

    Even if you are not actively participating, you’re still a member of the immunization movement.

    People have participated as health professionals, as government workers, as members of civil society, in various kinds of movements since decolonization.

    So the “movement” metaphor has a different resonance than that of “courses”.

    We used to call the Monday weekly meeting a discussion group.

    We’re now calling it a weekly assembly.

    It is a term that speaks to the religiosity of many learners, as well as to those with social commitments in their local communities.

    About ten years ago, I began to think of my goal for these discussion groups like the musician, the artist that you most appreciate, who really moves your soul, moves you, your every fiber and your body and your soul and your mind.

    I remember in 1989 I went to a Pink Floyd concert.

    When we left the concert, we were drenched in sweat; we were exhausted and just had an exhilarating experience.

    That’s what I would like people who participate in our events to feel.

    I believe that’s key to fostering the dynamics that will lead to effective teaching and learning and change as an outcome.

    We’re still light years away from that.

    Recently, a global health researcher shared that when she joins our events, she feels like she is in church in her home country of Nigeria.

    So, light years away, but making some progress.

    https://redasadki.me/2023/11/04/how-we-reframed-learning-and-development-learning-based-complex-work/

    #complexity #immunization #incidentalLearning #informalLearning #KarenEWatkins #PerformanceManagement #RethinkingWorkplaceLearningAndDevelopment #TheGenevaLearningFoundation #VictoriaJMarsick #workforceDevelopment

    #complexity #immunization #incidentallearning #informallearning #karenewatkins #performancemanagement
  17. N-gated Hacker News @[email protected] ·

    🎭 Oh no, #AI is making fake #poverty #porn now? 🖼️ Quick, someone grab a digital extinguisher! 🚒 Because nothing says "solving global issues" like a committee of moral hand-wringing and LinkedIn posts. 🙄
    redasadki.me/2025/10/23/how-do #DigitalEthics #MoralResponsibility #SocialMediaCritique #HackerNews #ngated

    #ai #poverty #porn #digitalethics #moralresponsibility #socialmediacritique
  18. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: 📅 Today on #WorldNTDDay, join #TeachToReach to
    listen to health workers share their direct experiences in the fight ag…

    #worldntdday #teachtoreach
  19. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: 📢 Practitioner insights! Psychological first aid in support of #children affected by the humanitarian crisis in #Ukra…

    #children #ukra
  20. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: 💉🦟 Tackling #malaria, #NTDs, or #immunization challenges? Learn how #TeachToReach’s peer learning model accelerates lo…

    #malaria #ntds #immunization #teachtoreach
  21. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: 🌍 Teach to Reach: À l’attention des professionnels de la vaccination et des soins de santé primaires 🚨 #PEV #VaccinesW…

    #pev #vaccinesw
  22. Reda Sadki @[email protected] ·

    I’m in awe of the photos being shared via @DigitalScholarX… We’re just a few hours from our 3rd annual World Immunization Week visual storytelling event #Humanly Possible #VaccinesWork t.co/Bge1bG3Dxv t.co/HiScvjInKa

    #humanly #vaccineswork
  23. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Adaptive change propagates learning. #ComplexLearning

    #complexlearning
  24. Reda Sadki @[email protected] ·

    RT @Gendarmerie_074: Fin de l’alerte !

    Merci aux démineurs de la @SecCivileFrance de #Lyon et à nos gendarmes #EOR (explosive ordnance rec…

    #lyon #eor
  25. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Creating order from chaos is the art of learning. #ComplexLearning

    #complexlearning
  26. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Noise is the curriculum. #ComplexLearning

    #complexlearning
  27. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Beyond cognitive/situative - learning emerges from bio-psycho-social systems. #ComplexLearning

    #complexlearning
  28. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: The edge of chaos is where knowledge thrives. #ComplexLearning

    #complexlearning
  29. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Context is the missing variable. #ComplexLearning

    #complexlearning
  30. Reda Sadki @[email protected] ·

    RT @DigitalScholarX: Learn the whole, not just the parts. #ComplexLearning

    #complexlearning
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