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Researchers routinely infer learning and other unobservable psychological functions based on observable behavior. But what behavioral changes constitute evidence of learning? The standard approach is to infer learning based on a single behavior across individuals, including assumptions about the direction and magnitude of change (e.g., everyone should avoid falling repeatedly on a treacherous obstacle). Here we illustrate the benefits of an alternative "multiexpression, relativist, agnostic, individualized" approach. We assessed infant learning from falling based on multiple behaviors relative to each individual's baseline, agnostic about the direction and magnitude of behavioral change. We tested infants longitudinally (10.5-15 months of age) over the transition from crawling to walking. At each session, infants were repeatedly encouraged to crawl or walk over a fall-inducing foam pit interspersed with no-fall baseline trials on a rigid platform. Our approach revealed two learning profiles. Like adults in previous work, "pit-avoid" infants consistently avoided falling. In contrast, "pit-go" infants fell repeatedly across trials and sessions. However, individualized comparisons to baseline across multiple locomotor, exploratory, and social-emotional behaviors showed that pit-go infants also learned at every session. But they treated falling as an unimpactful "pratfall" rather than an aversive "pitfall." Pit-avoid infants displayed enhanced learning across sessions and partial transfer of learning from crawling to walking, whereas pit-go infants displayed neither. Thus, reliance on a predetermined, "one-size-fits-all" behavioral expression of a psychological function can obscure different behavioral profiles and lead to erroneous inferences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Infants of all species learn to move in the midst of tremendous variability and rapid developmental change. Traditionally, researchers consider variability to be a problem for development and skill acquisition. Here, we argue for a reconsideration of variability in early life, taking a developmental, ecological, systems approach. Using the development of walking in human infants as an example, we argue that the rich, variable experiences of infancy form the foundation for flexible, adaptive behavior in adulthood. From their first steps, infants must cope with changes in their bodies, skills, and environments. Rapid growth spurts and a continually expanding environment of surfaces, elevations, and obstacles alter the biomechanical constraints on balance and locomotion from day to day and moment to moment. Moreover, infants spontaneously generate a variable practice regimen for learning to walk. Self-initiated locomotion during everyday activity consists of immense amounts of variable, time-distributed, error-filled practice. From infants' first steps and continuing unabated over the next year, infants walk in short bursts of activity (not continual steps), follow curved (not straight) paths, and take steps in every direction (not only forward)-all the while, accompanied by frequent falls as infants push their limits (rather than a steady decrease in errors) and explore their environments. Thus, development ensures tremendous variability-some imposed by physical growth, caregivers, and a changing environment outside infants' control, and some self-generated by infants' spontaneous behavior. The end result of such massive variability is a perceptual-motor system adept at change. Thus, infants do not learn fixed facts about their bodies or environments or their level of walking skill. Instead, they learn how to learn-how to gauge possibilities for action, modify ongoing movements, and generate new movements on the fly from step to step. Simply put, variability in early development is a feature, not a bug. It provides a natural training regimen for successfully navigating complex, ever-changing environments throughout the lifespan. Moreover, observations of infants' natural behavior in natural, cluttered environments-rather than eliciting adult-like behaviors under artificial, controlled conditions-yield very different pictures of what infants of any species do and learn. Over-reliance on traditional tasks that artificially constrain variability therefore risks distorting researchers' understanding of the origins of adaptive behavior., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.)

In his target article, Yarkoni prescribes descriptive research as a potential antidote for the generalizability crisis. In our commentary, we offer four guiding principles for conducting descriptive research that is generalizable and enduring: (1) prioritize context over control; (2) let naturalistic observations contextualize structured tasks; (3) operationalize the target phenomena rigorously and transparently; and (4) attend to individual data.