Stories

Tag: digital learning

  • The cost of inaction: Quantifying the impact of climate change on health

    The cost of inaction: Quantifying the impact of climate change on health

    This World Bank report ‘The Cost of Inaction: Quantifying the Impact of Climate Change on Health in Low- and Middle-Income Countries’ presents new analysis of climate change impacts on health systems and outcomes in the regions that are bearing the brunt of these impacts.

    Key analytical insights to quantify climate change impacts on health

    The report makes three contributions to our understanding of climate-health interactions:

    First, it quantifies the massive scale of climate change impacts on health, projecting 4.1-5.2 billion climate-related disease cases and 14.5-15.6 million deaths in LMICs by 2050. This represents a significant advancement over previous estimates, which the report demonstrates were substantial underestimates.

    Second, it illuminates the profound economic consequences, calculating costs of $8.6-20.8 trillion by 2050 (0.7-1.3% of LMIC GDP). The report employs both Value of Statistical Life and Years of Life Lost approaches to provide a range of economic impact estimates.

    Third, it reveals stark geographic inequities in impact distribution, with Sub-Saharan Africa bearing approximately 71% of cases and nearly half of deaths, while South Asia faces about 18% of cases and a quarter of deaths. This spatial analysis helps identify where interventions are most urgently needed.

    Policy implications and systemic perspectives

    The report’s findings point to several critical policy directions:

    • The need for systemic rather than disease-specific interventions emerges as a central theme. The authors explicitly advocate for strengthening entire health systems rather than pursuing vertical disease programs.
    • The economic analysis makes a compelling case for immediate action, demonstrating that the costs of inaction far exceed potential investment requirements for climate-resilient health systems.
    • The geographic distribution of impacts highlights the need for globally coordinated responses while prioritizing support for the most vulnerable regions.

    The findings suggest that transforming systems to address climate change impacts on health requires not just technical solutions but fundamental rethinking of how health systems are organized and financed in vulnerable regions.

    This aligns with recent scholarship on complex adaptive systems and organizational transformation in global health.

    The report’s emphasis on systemic approaches represents a significant shift in thinking about climate-health interventions. This merits unpacking on several levels:

    1. Inadequacy of vertical disease silos: The report challenges the traditional vertical disease management paradigm that has dominated global health programming for decades. While vertical programs have achieved notable successes in areas like HIV/AIDS or malaria control, the report argues that climate change’s multifaceted health impacts require a fundamentally different approach.
    2. Need for systemic intervention: Climate change simultaneously affects multiple disease pathways, nutrition status, and health infrastructure. These interactions cannot be effectively addressed through isolated disease-specific programs. Building core health system capabilities (surveillance, emergency response, primary care) creates multiplicative benefits across various climate-related health challenges. Strong health systems can better identify and respond to emerging threats, whereas vertical programs often lack this flexibility.
    3. Implementation implications: The report suggests this systemic approach requires: integrated planning across health system components, flexible funding mechanisms that support system-wide capabilities, enhanced coordination between different health programmes and investment in cross-cutting infrastructure and capabilities.

    What about the health workforce facing impacts of climate change on health?

    Between this clear-eyed assessment and effective action lies a critical implementation gap.

    Interestingly, the report gives limited explicit attention to the health workforce dimension of climate-health challenges. Yet that is precisely where we need to focus attention, given that:

    • Health workers based in communities are first responders to climate-related health emergencies
    • Workforce capacity significantly determines a health system’s adaptive capabilities
    • Climate change itself affects health worker distribution and effectiveness

    Given the report’s emphasis on systemic approaches, the lack of detailed discussion about human resources for health represents a missed opportunity to explore what effective action might look like.

    The Geneva Learning Foundation’s network, developed through nearly a decade of research and practice, has led us to identify a path for supporting the health workforce to strengthen preparedness and response in response to climate change impacts on health.

    The network already connects over 60,000 health workers. They represent all job roles, rank, and levels of the health system.

    One distinguishing feature of this network is its deep integration with existing government health systems. Over half of network participants are government employees, from community health workers to district officers to national planners.

    62% of participants work in remote rural areas, 47% serve urban poor populations, and 21% operate in conflict zones.

    These are not just statistics: they represent an unprecedented capability to mobilize knowledge and action where it’s most needed.

    Since 2023, network participants have been sharing observations, experiences, and insights of climate change impacts on health. 

    The model connects different levels of health systems:

    • Community-based health workers share ground-level observations
    • District managers identify emerging patterns
    • National planners gauge system-wide implications
    • Global partners access real-time insights

    When a malaria control officer in Kenya observes changing disease patterns due to altered rainfall, the network enables rapid sharing of this insight with colleagues working on water safety, nutrition, and primary care. These cross-domain connections do not need to be left to chance – they can be enabled through structured peer learning processes that transcend traditional programme, geographic, and hierarchical boundaries

    This creates what organizational theorists call “embedded transformation” – where system change emerges through existing structures rather than requiring new ones.

    Rather than creating new coordination mechanisms, the network enables:

    • Health workers to learn directly from peers in other programs
    • Rapid identification of cross-cutting challenges
    • Spontaneous formation of problem-solving groups
    • Systematic sharing of effective practices

    Rather than replacing existing structures, TGLF’s model demonstrates how digital networks can enable health systems to:

    • Maintain necessary specialization while fostering crucial connections
    • Enable rapid learning and adaptation across programs
    • Optimize resource use through enhanced coordination
    • Build system-wide resilience through structured peer learning

    Such a network enables what complexity theorists call “distributed sensing” that can provide:

    • Early warning of emerging threats
    • Rapid sharing of local solutions
    • System-wide learning from local innovations
    • Continuous adaptation to changing conditions

    This has led us to posit that investment in such emergent digital networks could enable health systems to maintain necessary specialization while fostering crucial connections across domains.

    This is obviously critical to respond to the systems-level complexity of climate change impacts on health.

    World Bank findingTGLF model strategic fit
    Scale of impact (4.1-5.2B cases, 14.5-15.6M deaths by 2050)TGLF’s digital network model demonstrates scalability, already connecting over 60,000 health practitioners across 137 countries. More significantly, the model’s effectiveness increases with scale – as more practitioners join, the network’s ability to identify emerging threats and disseminate effective responses improves. Network analysis shows that larger scale enables more diverse inputs and faster adaptation, suggesting this approach could help health systems respond to the massive scale of projected impacts.
    Economic consequences ($8.6-20.8T by 2050)TGLF’s model offers remarkable cost-effectiveness through its networked learning structure. Rather than requiring massive new investments in parallel systems, it leverages existing health system resources while enabling and accelerating both learning and action. The model demonstrates how digital infrastructure can maximize return on investment – practitioners implement solutions using existing resources, with 82% reporting ability to continue without external support. This suggests potential for significant cost savings while building system resilience.
    Geographic inequities (71% SSA, 18% SA)TGLF’s network already demonstrates strongest presence precisely where the World Bank identifies greatest need – 70% of participants work in Sub-Saharan Africa and South Asia. This concentration is not coincidental; the model’s digital infrastructure and peer learning approach prove particularly effective in resource-constrained settings. The network enables rapid sharing of context-appropriate solutions between regions facing similar challenges, while maintaining sensitivity to local conditions.
    Need for systemic interventionThe network transcends traditional program boundaries through what organizational theorists call “structured emergence” – practitioners naturally form cross-program connections based on shared challenges. When a malaria control officer observes changing disease patterns due to climate shifts, the network enables rapid sharing with colleagues in water safety, nutrition, and primary care. This organic integration emerges through peer learning rather than requiring new coordination mechanisms.
    Urgency of investmentTGLF’s model offers an immediately scalable approach that builds on existing health system capabilities. Rather than waiting years to develop new infrastructure, the network can rapidly expand to connect more practitioners and regions. Evidence shows 7x acceleration in implementation of new approaches compared to conventional means of technical assistance, suggesting potential for rapid, sustainable strengthening of health system resilience.
    Global coordination needWhile enabling global connection, the network maintains strong local grounding through its emphasis on locally-led action and contextual adaptation. Government health workers comprise over 50% of participants, creating what scholars term “embedded transformation” – change emerging through existing structures rather than imposed from outside. This enables coordinated response while respecting local health system authority.
    System transformationThe model demonstrates how digital networks can fundamentally transform how health systems operate without requiring complete restructuring. By enabling rapid knowledge flow across traditional boundaries, supporting emergence of new coordination patterns, and fostering system-wide learning, it shows how transformation can emerge through enhanced connection rather than structural overhaul. Analysis reveals development of new capabilities in surveillance, response, and adaptation through networked learning.

    Reference

    Uribe, J.P., Rabie, T., 2024. The Cost of Inaction: Quantifying the Impact of Climate Change on Health in Low- and Middle-Income Countries. The World Bank, Washington, D.C. https://doi.org/10.1596/42419

    Image: The Geneva Learning Foundation Collection © 2024

  • Taking the pulse: why and how we change everything in response to learner signals

    Taking the pulse: why and how we change everything in response to learner signals

    The ability to analyze and respond to learner behavior as it happens is crucial for educators.

    In complex learning that takes place in digital spaces, task separation between the design of instruction and its delivery does not make sense.

    Here is the practical approach we use in The Geneva Learning Foundation’s learning-to-action model to implement responsive learning environments by listening to learner signals and adapting design, activities, and feedback accordingly.

    Listening for and interpreting learner signals

    Educators must pay close attention to various signals that learners emit throughout their learning journey. These signals appear in several key ways:

    1. Engagement levels: This includes participation rates, the quality of contributions in discussions, how learners interact with each other, and knowledge artefacts they produce.
    2. Emotional responses: The tone and content of learner feedback can indicate enthusiasm, frustration, or confusion.
    3. Performance patterns: Trends in speed and volume of responses tend to strongly correlate with more significant learning outcome indicators.
    4. Interaction dynamics: Learners can feel a facilitator’s conviction (or lack thereof) in the learning process. Observing the interaction should focus first on the facilitator’s own behavior: what are they modeling for learners?
    5. Technical interactions: The way learners navigate the learning platform, which resources they access most, and any technical challenges they face are important indicators.

    Making sense of learner signals

    Once these signals are identified, a nuanced approach to analysis is necessary:

    1. Contextual consideration: Understanding the broader context of learners’ experiences is vital. For example, differences between language cohorts might reflect varying levels of real-world experience and cultural contexts.
    2. Holistic view: Look beyond immediate learning objectives to understand all aspects of learners’ experiences, including factors outside the course that may affect their engagement.
    3. Temporal analysis: Track changes in learner behavior over time to reveal important trends and patterns as the course progresses.
    4. Comparative assessment: Compare behavior across different cohorts, language groups, or demographic segments to identify unique needs and preferences.
    5. Feedback loop analysis: Examine how learners respond to different types of feedback and instructional interventions to provide valuable insights.

    Adapting learning design in situ

    What can we change in response to learner behavior, signals, and patterns?

    1. Customized content: Tailor case studies, examples, and scenarios to match the real-world experiences and cultural contexts of different learner groups.
    2. Flexible pacing: Adjust the rhythm of content delivery and activities based on observed engagement patterns and feedback.
    3. Varied support mechanisms: Implement a range of support options, from technical assistance to emotional support, based on identified learner needs.
    4. Dynamic group formations: Adapt group activities and peer learning opportunities based on observed interaction dynamics and skill levels.
    5. Multimodal delivery: Offer content and activities in various formats to cater to different learning preferences and technical capabilities.

    Responding to learner signals

    Feedback plays a crucial role in the learning process:

    1. Comprehensive acknowledgment: Feedback mechanisms should demonstrate to learners that their input is valued and considered. This might involve creating, at least once, detailed summaries of learner feedback to show that every voice has been heard.
    2. Timely interventions: Using real-time feedback to address emerging issues or confusion quickly can prevent small challenges from becoming major obstacles.
    3. Personalized guidance: Tailor feedback to individual learners based on their unique progress, challenges, and goals.
    4. Peer feedback facilitation: Create opportunities for learners to provide feedback to each other to foster a collaborative learning environment.
    5. Metacognitive prompts: Incorporate feedback that encourages learners to reflect on their learning process to promote self-awareness and self-directed learning.

    Balancing act

    When combined, these analyses provide clues to inform decisions.

    Nothing should be set in stone.

    Decisions need to be pragmatic and rapid.

    In order to respond to the pattern formed by signals, what are the trade-offs?

    The digital economy of effort makes rapid changes possible.

    Nevertheless, we consider the cost of each change versus its benefit.

    This adaptive approach involves careful balancing of various factors:

    1. Depth versus speed: Navigate the tension between providing comprehensive feedback and maintaining a timely pace of instruction.
    2. Structure versus flexibility: Maintain a coherent course structure while allowing for adaptations based on learner needs.
    3. Individual versus group needs: Balance addressing individual learner challenges with maintaining the momentum of the entire cohort.
    4. Emotional support versus learning structure: Provide necessary emotional support, especially in challenging contexts, while maintaining focus on learning objectives.

    Learning is research

    Each learning experience should be treated as a research opportunity:

    1. Data collection: Systematically collect data on learner behavior, feedback, and outcomes.
    2. Team reflection: Conduct regular debriefs with the instructional team to share insights and adjust strategies.
    3. Iterative design: Use insights gained from each cohort to refine the learning design for future iterations.
    4. Cross-cohort learning: Apply lessons learned from one language or cultural group to enhance the experience of others, while respecting unique contextual differences.

    Image: The Geneva Learning Foundation Collection © 2024

  • Making sense of sensemaking

    Making sense of sensemaking

    In her article “A Shared Lens for Sensemaking in Learning Analytics”, Sasha Poquet argues that the field of learning analytics lacks a shared conceptual language to describe the process of sensemaking around educational data. She reviews prominent theories of sensemaking, delineating tensions between assumptions in dominant paradigms. Poquet then demonstrates the eclectic use of sensemaking frameworks across empirical learning analytics research. For instance, studies frequently conflate noticing dashboard information with interpreting its significance. To advance systematic inquiry, she calls for revisiting epistemic assumptions to reconcile tensions between cognitive and sociocultural traditions. Adopting a transactional perspective, Poquet suggests activity theory, conceptualizations of perceived situational definitions, and ecological affordance perception can jointly illuminate subjective and objective facets of sensemaking. This preliminary framework spotlights the interplay of internal worldviews, external systemic contexts, and emergent perceptual processes in appropriating analytics.

    The implications span research and practice. The proposed constructs enable precise characterization of variability in stakeholder sensemaking to inform dashboard design. They also facilitate aggregating insights across implementations. Moreover, explicitly mapping situational landscapes and tracking affording relations between users and tools reveals rapid shifts in adoption phenomena frequently obscured in learning analytics. Capturing sensemaking dynamics through this multidimensional lens promises more agile, context-sensitive interventions. It compels a human-centered orientation to analytics aligned with longstanding calls to catalyze latent systemic wisdom rather than control complex educational processes.

    The Geneva Learning Foundation’s mission centers on fostering embedded peer learning networks scaling across boundaries. This vision resonates deeply with calls to transition from fragmented insights towards fostering collective coherence. The Foundation already employs a complexity meta-theory treating learning as an emergent phenomenon arising from cross-level interactions between minds and cultures. Adopting Poquet’s shared vocabulary for examining sensemaking processes driving appropriation of insights can help, as we continue to explore how to describe, explain, and understand our own work, large parts of which remain emergent. For instance, analysis could trace how contextual definitions interact with perceived affordances and activity systems to propagate innovative practices during Teach to Reach events spanning thousands worldwide. More broadly, the lens proposed mobilizes analytics to illuminate rather than dictate stakeholder wayfinding through complex challenges.

    Poquet, O. (2024). A shared lens around sensemaking in learning analytics: What activity theory, definition of a situation and affordances can offer. British Journal of Educational Technology, 00, 1–21.

    Illustration: The Geneva Learning Foundation Collection © 2024

  • What learning science underpins peer learning for Global Health?

    What learning science underpins peer learning for Global Health?

    Watch Reda Sadki’s presentation about peer learning for global health at the Annual Meeting of the American Society for Tropical Medicine and Hygiene (ASTMH) Symposium on 19 October 2023

    Most significant learning that contributes to improved performance takes place outside of formal training.

    It occurs through informal and incidental forms of learning between peers.

    This is called peer learning or peer-to-peer learning.

    Effective use of peer learning requires realizing how much we can learn from each other (peer learning), experiencing the power of defying distance to solve problems together (remote learning), and feeling a growing sense of belonging to a community (social learning), emergent across country borders and health system levels (networked learning).

    At the ASTMH annual meeting Symposium organized by Julie Jacobson, two TGLF Alumnae, María Monzón from Argentina and Ruth Allotey from Ghana, will be sharing their analyses and reflections of how they turned peer learning into action, results, and impact.

    In his presentation, Reda Sadki, president of The Geneva Learning Foundation (TGLF), will explore:

    1. What do we need to understand about digital learning?
    2. Networked learning: rethinking learning architecture in the Digital Age
    3. Social learning: peer learning is about making human connections
    4. Practical examples of TGLF peer learning systems for WHO, Wellcome, UNICEF, and Bridges to Development that connect learning to change, results, and impact.
    5. Emergent peer learning systems driven by local practitioner and community needs and priorities.

    Join this #TropMed23 Peer Learning symposium on Day 2 of the Annual Meeting of the American Society for Tropical Medicine and Hygiene (ASTMH).

  • The COVID-19 Peer Hub as an example of Collective Intelligence (CI) in practice

    The COVID-19 Peer Hub as an example of Collective Intelligence (CI) in practice

    A new article by colleagues at the Cambridge Digital Education Futures Initiative (DEFI) illustrates academic understanding of Collective Intelligence (CI) through the COVID-19 Peer Hub, a peer learning initiative organized by over 6,000 frontline health workers in Africa, Asia, and Latin America, with support from The Geneva Learning Foundation (TGLF), in response to the initial shock of the pandemic on immunization services that placed 80 million children at risk of missing lifesaving vaccines. Learn more about the COVID-19 Peer Hub…

    From the abstract:

    Collective Intelligence (CI) is important for groups that seek to address shared problems.

    CI in human groups can be mediated by educational technologies.

    The current paper presents a framework to support design thinking in relation to CI educational technologies.

    Our Collective Intelligence framework is grounded in an organismic-contextualist developmental perspective that orients enquiry to the design of increasingly complex and integrated CI systems that support coordinated group problem solving behaviour.

    We focus on pedagogies and infrastructure and we argue that project-based learning provides a sound basis for CI education, allowing for different forms of CI behaviour to be integrated, including swarm behaviour, stigmergy, and collaborative behaviour.

    We highlight CI technologies already being used in educational environments while also pointing to opportunities and needs for further creative designs to support the development of CI capabilities across the lifespan.

    We argue that Collective Intelligence education grounded in dialogue and the application of CI methods across a range of project-based learning challenges can provide a common bridge for diverse transitions into public and private sector jobs and a shared learning experience that supports cooperative public-private partnerships, which can further reinforce advanced human capabilities in system design.

    Article excerpt:

    As an example of Collective Intelligence in practice, in 2020–2021, more than 6000 health workers joined The Geneva Learning Foundation (TGLF) COVID-19 Peer Hub.

    Participants shared more than 1200 ideas or practices for managing the pandemic in their contexts within 10 days. Relevant peer ideas and practices were then referenced as participants produced individual, context-specific action plans that were then reviewed by peers before finalisation and implementation.

    Mapping of action plan citations (C3L 2022) demonstrate patterns of peer learning, between countries, organisations and system levels.

    In parallel, TGLF synthesises data generated by peer learners in formats legitimised by the global health knowledge system (e.g. Moore et al. 2022).

    The biggest challenge to CI in this context remains one of legitimacy: how can collective intelligence compete with the perceived gold standard of academic publication within this expert-led culture?

    We argue that as CI education is further developed and extends across the lifespan from school learning environment to work and organisational environments, CI technologies and practices will be further developed, evaluated, and refined and will gain legitimacy as part of broader societal capabilities in CI that are cultivated and reinforced on an ongoing basis.

    References

    • Kovanovic, V. et al. (2022) The power of learning networks for global health: The Geneva Learning Foundation COVID-19 Peer Hub Project Evaluation Report. Centre for Change and Complexity in Learning.
    • Moore, Katie, Barbara Muzzulini, Tamara Roldán, Juliet Bedford, and Heidi Larson. 2022. Overcoming barriers to vaccine acceptance in the community: Key learning from the experiences of 734 frontline health workers (1.0). The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.6965355
    • Hogan, M.J., Barton, A., Twiner, A., James, C., Ahmed, F., Casebourne, I., Steed, I., Hamilton, P., Shi, S., Zhao, Y., Harney, O.M., Wegerif, R., 2023. Education for collective intelligence. Irish Educational Studies 1–30. https://doi.org/10.1080/03323315.2023.2250309
  • Mission accomplished

    Mission accomplished

    We won.

    • The former school teacher and humanitarian trainer who argued vociferously that nothing would ever supplant face-to-face training is now running a MOOC.
    • The training manager who refused to consider e-learning is now running a distance learning, scenario-based simulation. People he trains are now working remotely – and a simulation, dirt-cheap and run by e-mail, is closer to modelling the real world than is the artificially and unrealistically “safe space” of the high-cost, low-volume training room. Work went through digital transformation before “training” did.
    • The old-school learning and development manager is getting certified to run webinars. Through practice, she has surprised herself by how much she feels when running a session.
    • A digital course run ahead of a face-to-face workshop mobilized ten times as many (people), for ten times less (money). Course participants produced tangible artefacts, directly applicable to work, through collaboration and peer review. And they did not need to take time off in order to do so. The outcome of the physical-world, residential experience is less tangible. Or, with a double entendre, one could say: more virtual.

    These are not stories of the superiority of one medium over another. They are stories of the accelerating pace of change.

    These are not stories of victory. They are stories of experiencing our humanity in and through new, rapidly-changing spaces where we work, live, and grow.

    This is how we learn.

    Image: A metaphor for irony. Bush delivers a speech to crew onboard the USS Abraham Lincoln to declare combat operations over in Iraq, as the carrier steamed toward San Diego, California on May 1, 2003 (Larry Downing/file/Reuters).

  • Tower of Babel

    Tower of Babel

    What happens when a fledgling, start-up foundation convenes learning leaders from all over the world to explore digital learning? Over 800 participants from 103 countries have joined the Geneva Learning Foundation’s #DigitalScholar course developed in conjunction with the University of Illinois College of Education and Learning Strategies International.

    The course officially launches on Monday. Yet participants  joining the online community have begun introducing themselves and, in the process, are already tackling challenging questions on the pedagogy, content, and economics of education and its digital transformation.

    “Look at all the people here!” exclaimed one Digital Scholar. And, yes, we are from everywhere. You could start from “cloudy England”, a hop-and-a-skip away from “rainy Amsterdam” and then keep travelling, stopping in any of the 103 countries where participants live. You might end up in the “paradise island” of Mauritius, “sunny but chilly” Sidney, or “hot and humid” Puerto Rico.

    Think about it. When Bill Cope and Mary Kalantzis describe the affordance of “ubiquity”, the anywhere-anytime in digital learning, that describes the ability of learners to connect to a course. But ubiquity also enables our connections to each other, across time and space. A banal weather report becomes a way of relating here to there, a way to refer the diversity of contexts and paths that have led us here.

    “Thrilled” and “excited” and “delighted” come up more than once. But why are we here? In the words of one Digital Scholar: “I hope to learn and obtain skills to rock!” It is the “opportunity to learn new skills” about the “nuts and bolts” of digital learning. It is also for “professional and educational growth”.  Yes, technology is the “new shiny” but our task as learning leaders is to be “always thinking about how it can best be used in learning”.

    So we are here to begin building our own digital course. Not everyone is sure what to expect – and I was surprised by the number who do not know what course they want to develop. That will be the first order of business on Monday and throughout the first week of the course. What we express is of course situated in our context of work and life. The diversity of contexts is staggering – and harder to wrap my head around than the weather. I get that the choice, for example, to focus on “citizen-centered community action”, education, peace, or social justice issues is of course no accident.

    The Geneva Learning Foundation’s initial call for applications focused on its own network, in the humanitarian, development, and global health space. So there are public health specialists, evaluators, crisis mappers, knowledge managers, leadership developers, school principals and teachers.

    But our bet was that the call would then escape the boundaries of our known circles and reach other industries. And we have. Hence we find decision-making and risk management, writing, faculty development, and the occasional topic that intersect specialties, such as the course on “Twitter for health professionals”.

    The common thread is the yearning to share, translate, grow, develop, fusing experience and practice and networks.

    So you want to build a course. How do you know that there is a demand for it? Yes, that is the crass language of Economics 101 supply-and-demand intruding in a world of learning that we would like to imagine pure and removed from material considerations. But one of the key lessons we hope to convey in this course will be the realization that there is a political economy to knowledge and learning. “There seems to be an interest to learn more” about Twitter for health professionals, explained one participant, after giving presentations “at various local medical organizations”. Is that sufficient to demonstrate demand for a course that will require investment of time and resources and possibly carry a price tag? There is, in fact, only one business model for education that can happen fast and be sustainable: institutions, individuals or both must be prepared to pay enough to cover the costs of the operation.

    Traditional institutions of higher education already have channels for marketing, recruitment, sales, and so on. But what about those of us who do not work within one of these institutions – or who wish to develop learning that does not fit into their sometimes-narrow constraints, especially as we push to innovate the practice of education?

    For one participant, the logic is one of austerity, of how to do more with less: “Due to the sharp decrease in training funding from the government, we are looking seriously at the fully-online mode” rather than blended learning that had been used in the past. The caveat is that the mere fact that technology does enable you to make “services more widely accessible” does not mean they will be more affordable – and nor does accessibility mean that people will come (much less pay for) an educational programme.

    My premise is that content and pedagogy are the easy parts (tongue in cheek) to figure out. The real challenge is in taking it to market (even if the learners won’t be the ones paying for it). In developing their course announcement, #DigitalScholar course participants may well find that this is the most challenging part of the endeavor. How do you test and verify your assumptions about who would actually want to take your course? What if you are wrong?

    My last question to incoming participants is about the Digital Transformation. Yes, that’s with capital letters, originally used in management theory to describe how conventional industries are transformed by “e-business”. I believe that this is one useful lens to reframe our role as learning leaders, to help us adapt and perhaps even stay a step ahead of the accelerated pace of technological change.

    Some Digital Scholars are not sure about what it means. For others, it referred to the impact of technology on learning, “how we interact with content” or “with each other in a Digital Age”, “how content is made available, and how it is utilized” in a “mix of dynamic possibilities”. Others ascribed the concept with inspirational or aspirational aims, leading to “a transformed learning experience” “potentially offering innovative and dynamic courses”, in the name of “deeper, more meaningful learning” and “rich interactions with peers and the instructor”.

    Many of us keep coming back to scale (““improving access of education to more learners”) as the starting point for thinking about what we can afford to do through effective use of technology. What we will explore in the course is that there are, in fact, many more affordances of digital learning’s amazing economy of effort.

    You can still join to become a #DigitalScholar until Sunday, 3 July 2016. The course will launch on the 4th of July. Read the full course announcement and apply here. We also have Facebook, Twitter, and Slack.

    Image: The Tower of Babel by Pieter Bruegel the Elder (1563).

  • Beyond MOOCs: the democratization of digital learning

    Beyond MOOCs: the democratization of digital learning

    It is with some trepidation that I announce the Geneva Learning Foundation’s first open access digital course in partnership with the University of Illinois College of Education and Learning Strategies International.

    The mission of the brand-new Geneva Learning Foundation is to connect learning leaders to research, invent, and trial breakthrough approaches for new learning, talent and leadership as a way of shaping humanity and society for the better.

    This open access, four-week (16 hours total) online course will start on 4 July 2016 and end on the 29th. It will be taught by Bill Cope, Catherine Russ, and myself, three of the eleven charter members of the Foundation.

    We’ll be using Scholar to teach the latest digital learning pedagogies. Everyone will develop, peer review, and revise an outline for a course relevant to their own context of work. This outline is intended to be the practical basis for developing and offering an actual course – so this is no academic exercise.

    The course is tightly aligned by this mission, both theoretically and practically:

    • Theoretically, learning – like almost everything else – is being remade by digital. Learning in a knowledge society is a key process to change, hence the urgency and centrality of thinking through what digital transformation means with respect to knowledge and learning.
    • Practically, it will convene learning professionals who will collaborate to develop new ways of teaching and learning

    You will notice that there is no reference specifically to the humanitarian context in the course announcement. I hope that participants will come from many different industries, and that all stand to benefit by new learning approaches we have developed on the edge of chaos.

    Please do share the course announcement with trusted colleagues and networks. And, if you are free in July, don’t miss it. I am betting that this first run will gather an eclectic group of learning mavericks and at least a few of those whom Cath calls edge-walkers, not just fellow humanitarians but folks from other industries operating in the same, increasingly-complex world.

    So why claim that this is “beyond MOOCs”? I do not mean to imply that this course is somehow a successor to massive open online courses (MOOCs). Rather, I have written elsewhere about how MOOCs remain mostly about the transmission of knowledge. This course is about learners as active knowledge producers. I believe this is an important distinction. (Seb Schmoller argues that strong learning design can organize a beautiful, effective learning journey in just about any architecture. This, to me, is akin to saying that even a car can be made to fly – you just need to strap on some wings…)

    There is an equally important distinction when defining what we mean by the democratization of learning: is this about scale (more learners with access to education)? Or is it about a paradigm change in what learners get to do: learning anywhere and any time by actively designing meanings and making knowledge they can use, thinking about thinking (metacognition), giving each other recursive feedback as they collaborate to solve problems… in other words, being teachers in a Digital Age?

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