The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
How Do You Learn to Walk? Thousands of Steps and Dozens of Falls per Day
Open accessAbstract
A century of research on the development of walking has examined periodic gait over a straight, uniform path. The current study provides the first corpus of natural infant locomotion derived from spontaneous activity during free play. Locomotor experience was immense: Twelve- to 19-month-olds averaged 2,368 steps and 17 falls per hour. Novice walkers traveled farther faster than expert crawlers, but had comparable fall rates, which suggests that increased efficiency without increased cost motivates expert crawlers to transition to walking. After walking onset, natural locomotion improved dramatically: Infants took more steps, traveled farther distances, and fell less. Walking was distributed in short bouts with variable paths—frequently too short or irregular to qualify as periodic gait. Nonetheless, measures of periodic gait and of natural locomotion were correlated, which indicates that better walkers spontaneously walk more and fall less. Immense amounts of time-distributed, variable practice constitute the natural practice regimen for learning to walk.
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Cites
The origins of intelligence in children.
Piaget, J. (1952) · doi:10.1037/11494-000 · Cited by 10,687
The role of deliberate practice in the acquisition of expert performance
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993) · Psychological Review · doi:10.1037/0033-295x.100.3.363 · Cited by 9,564
Motor Control and Learning: A Behavioral Emphasis
Schmidt, R. A. (1982) · Cited by 4,770
Meaningful Differences in the Everyday Experience of Young American Children
Panagos, R. J. (1998) · Remedial and Special Education · doi:10.1177/074193259801900609 · Cited by 4,173
The CHILDES project: tools for analyzing talk
MacWhinney, B. (1992) · Child Language Teaching and Therapy · doi:10.1177/026565909200800211 · Cited by 3,396
The CHILDES Project: Tools for Analyzing Talk
Pye, C., & MacWhinney, B. (1994) · Language · doi:10.2307/416745 · Cited by 2,301
Advances in Child Development and Behavior
(2008) · Advances in Child Development and Behavior · doi:10.1016/s0065-2407(08)00013-x · Cited by 1,758
Crook, C. (1985) · Ethology and Sociobiology · doi:10.1016/0162-3095(85)90031-7 · Cited by 1,459
Motor control and learning: A behavioral emphasis, 4th ed.
Schmidt, R. A., & Lee, T. D. (2005) · Cited by 930
Handbook of developmental psychology
Wolman, B. B., & Stricker, G. (1982) · Prentice Hall eBooks · Cited by 895
Cited by
Motor Development: Embodied, Embedded, Enculturated, and Enabling
Adolph, K. E., & Hoch, J. E. (2019) · Annual Review of Psychology · doi:10.1146/annurev-psych-010418-102836 · Cited by 580
Self-citationThe development of motor behavior
Adolph, K. E., & Franchak, J. M. (2017) · WIREs Cognitive Science · doi:10.1002/wcs.1430 · Cited by 371
Self-citationThe Developing Infant Creates a Curriculum for Statistical Learning
Smith, L. B., Jayaraman, S., Clerkin, E., & Yu, C. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.02.004 · Cited by 299
Crawling and Walking Infants See the World Differently
Kretch, K. S., Franchak, J. M., & Adolph, K. E. (2014) · Child Development · doi:10.1111/cdev.12206 · Cited by 298
Self-citationAdolph, K. E., & Robinson, S. R. (2015) · Handbook of Child Psychology and Developmental Science · doi:10.1002/9781118963418.childpsy204 · Cited by 135
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Metadata
- Authors
- Adolph, K. E., Cole, W. G., Komati, M., Garciaguirre, J. S., Badaly, D., Lingeman, J. M., Chan, G. L. Y., & Sotsky, R. B.
- Venue
- Psychological Science
- Publisher
- SAGE Publications
- Published
- 2012-10-19
- Volume
- 23
- Issue
- 11
- Pages
- 1387-1394
- ISSN
- 0956-7976 (ISSN-L)
- 1467-9280
- OpenAlex
- W2113885007
- Cited by
- 419
- References
- 49
- FWCI
- 29.00
- Type
- journal article
- Language
- en
- Open access
- green
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- Adolph, K. E., Cole, W. G., Komati, M., Garciaguirre, J. S., Badaly, D., Lingeman, J. M., Chan, G. L. Y., & Sotsky, R. B. (2012). How Do You Learn to Walk? Thousands of Steps and Dozens of Falls per Day. Psychological Science. https://doi.org/10.1177/0956797612446346
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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