Tag: e-learning

  • Learn health, but beware of the behaviorist trap

    Learn health, but beware of the behaviorist trap

    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

  • Mobile learning: the “anywhere” in the affordance of ubiquity

    Mobile learning: the “anywhere” in the affordance of ubiquity

    When I look at my Facebook friends online, I can see that most of them are connected, almost 24/7, via their phones. Those connected from a laptop or desktop computer (shown by a green dot instead of a little phone icon) are an ever-dwindling minority.

    As Scholar is meant to be a social application for learning, I thought it might be useful to reflect on what mobile means for learning. Recently, I invited mobile design expert Josh Clark to explain to a Red Cross audience why we should design our applications (including those for learning) using a mobile-first strategy. He’s not a learning guy, but I haven’t been able to find a learning expert with useful insights on these issues (as I explain in my conclusion). You can read about Josh’s work on the web here, for example:

    Josh’s first point is that we have a “condescending” view of mobile, seeing it as a “lite” version of the “full” desktop experience. This view is wrong, and to demonstrate this he debunks several mobile myths: “We have some really stubborn myths about mobile users, really screwing up the way we provide mobile services.”

    Myth #1 is that “mobile users are rushed and distracted”, with a short attention span. With mobile learning, this has translated into little info tidbits or short exercises. MIT’s Open CourseWare (OCW) iPhone app, for example, starts up with a message warning that it’s “a subset” of the OCW catalog.

    Yes, sometimes you use your mobile device for information on the go. But that’s far from the only use case. Mobile is also on the couch, in the kitchen, on the bed, or during a 3-hour layover… and, last but not least, sitting on the throne (according to Josh, 40% admit to using phones in bathroom).

    Those mobile contexts allow us to concentrate and focus on content. They are non-traditional (for now) contexts of engagement which can make learning more pleasurable (because of the level of comfort, by saving us from boredom during that layover, etc.).

    So what do users expect from a mobile application? 85% expect mobile to be *at least as good* as desktop. Why would this be any different for students or other learners? We do everything on our phones that it seems obvious we are now at a point where the concept of a distinct, discrete *mLearning* makes no sense.

    OK, so if mobile doesn’t necessarily mean rushed users, what about small screen sizes? Doesn’t that physical limitation place limits on learning?

    The screen size raises the issue of visual presentation of learning content. Yes, we have built a lot of user interaction and interface conventions on the assumption of a 4:3 or 16:9 screen ratio. This goes back a while for machine learning, starting with Macromedia Director interfaces in the 1990s that imposed 640 x 480 pixels as a “standard” screen size for interactive, animated content. So we have at least 20 years of thinking reliant on the model of eLearning that some are now trying to painstakingly reduce by changing the “e” in learning to the “m”.

    I agree with Josh that the real answer is not in this alphabet soup. Don’t confuse context with intent. We make too many assumptions from screen size. Screen size should not be an excuse to limit functionality. Using small screen does not equal wanting to do less. It would be like saying that because paperbacks have smaller pages, you have to remove entire chapters. The trick is to make complexity uncomplicated. There’s a difference.

    Mobile websites/apps should have full content/tools. Yes, they may be displayed differently and hierarchy may change. Some devices may be better suited to some tasks than others — so EMPHASIZE different content on different devices. But don’t arbitrarily give me LESS. That goes not only for individual sites but for families of sites.

    A lot of people ONLY use their phone. And of course perhaps the more expected numbers from developing world: In Egypt, 70% of net users rely solely on their phones. In India, it’s 59%. Ghana: 55%. Kenya: 54%. Nigeria: 50%. OK, you say, but these are developing countries where desktop computers and broadband access are expensive. But wait, what’s this… 25% in the US and 22% in the UK use *only* their phone. Another 28% of US mobile web users *mostly* use mobile web.

    And, if we are talking about teaching young people, I’m sure these stats are much higher.

    This group of mobile-only or mostly-mobile users definitely expect to do everything on mobile. If we care about reaching them or teaching them, we have to care about hitting them on mobile.

    For individual-learner click-through online learning modules, I’ve recently sent out two requests for proposals to over 20 companies that specialize in building such modules to support adult learning. Not a single one actually can currently deliver a mobile-first strategy. Yet, the tools and techniques to build a single code base (using HTML5 to replace Flash for animation and a technique called responsive design) already exist and are in wide use in other areas — just not in learning. Yes, they all know it’s a long-term trend, but in many of the responses I received they proposed to build a separate, “lite” version of the “real” learning modules. Exactly the opposite of what I think is needed. And the stats cited above (as well as more insightful analysis from Josh and other designers) make a strong case that this needs to happen today, not in some distant future.