Taking Research out of the Lab: Embodied and Situated Language Development
Bibliographic record
Abstract
Language acquisition is influenced by the child, in terms of their genetic and biological make-up, but also acquired within the context of their family, social systems, schools, and community. Development is influenced by the culture, language, and social context surrounding the child. Embodied cognition is the view that thinking is grounded in perceptual, action, and emotion systems. An embodied theory of language acquisition predicts that early concepts develop from sensorimotor experience. Evidence regarding the role of the body in language acquisition can influence teaching, community programs, and families. Researchers also can learn from the experiences of the child and their communities when supporting young language learners. In Chapter 2, I describe embodied cognition for educators. I describe the shift in cognitive psychology from describing thinking as the manipulation of arbitrary symbols to the view that an integrated system houses sensory and motor systems but also language information. I provide evidence for the role of sensorimotor experience in learning. I also discuss some critical areas that need to be explained by embodied cognition, where more research is required and take-home messages for teachers. In Chapter 3, I delineate embodied from situated cognition in language acquisition. Language is embodied in that our internal cognitive mechanisms are grounded in our sensorimotor and affective systems but also situated because language is learned within a broader context. In Chapter 4, I describe a community-based research project testing a program designed to increase adult talk and conversation between caregivers and children. Community-based research allows for an exploration of language learning in the context of the families and communities in which children live. With training, caregivers can increase the quantity of speech they share with their children, and feedback could be one way to help facilitate this process. I consider how these findings could influence a broader discussion around the role of parental input in language development. Across these diverse studies, I explore language outside the traditional laboratory setting for language research. I bring knowledge of language acquisition theory and principles to teachers for direct application in their classrooms. I delineate the need for lab-based research and research in naturalistic environments and examine one such endeavour.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".