Heuristic techniques for the analysis of variability as a dynamic aspect of change

Abstract

Spanish

Due to the influence of dynamic systems and microgenetic perspectives, variability is nowadays often seen as an important phenomenon that helps us understand the underlying mechanisms of development. This paper aims at demonstrating several simple techniques that can be used to analyse variability in data of developing (or learning) individuals. These techniques will be illustrated by applying them to a time serial dataset of early child language (to be specific, the emergence of grammatical preposition use). First, we show some descriptive techniques that are essential first steps for generating hypotheses. Also, we propose a measure that expresses qualitative variability. Furthermore, we demonstrate how resampling techniques can be used to test the presence of performance peaks, which may be important because they indicate the emergence of new abilities. Finally, we show the use of a technique that is especially useful for exploring interactions between ordinal variables (the State Space Grid, or SSG). With this illustration, we hope to encourage researchers to take a more exploratory approach to variability in their data and to develop methods directed at analysing dynamic aspects of change.

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References

Alibali

Goldin-Meadow

(1993). Gesture-speech mismatch and mechanisms of learning: What the hands reveal about the child's state of mind. Cognitive Psychology, 25, 468–523.

Bertenthal

(1999). Variation and selection in the development of perception and action. Savelsbergh

In G.

van Der Maas

van Geert

(Eds.), Non-linear developmental processes (Vol. 175, pp. 105–121). Amsterdam: Koninklijke Nederlandse Academie van Wetenschappen.

Brown

(1973). A first language: The early stages. London, UK: Allen & Unwin.

Clark

E. V.

(1978). Strategies for communicating. Child Development, 49, 943–959.

Fischer

K.W.

Granott

(1995). Beyond one-dimensional change: Parallel, concurrent socially distributed processes in learning and development. Human Development, 38, 302–314.

Good

P. I.

(1999). Resampling methods: a practical guide to data analysis. Boston: Birkhauser.

Graham

Perry

(1993). Indexing transitional knowledge. Developmental Psychology, 29 (4), 779–788.

Granott

(1998). Unit of analysis in transit: From the individual's knowledge to the ensemble process. Mind, Culture, and Activity, 5 (1), 42–66.

Lamey

Hollenstein

Lewis

M. D.

Granic

(2004). Grid Ware (Version 1.1). [Computer software]. http://statespacegrids.org

10.

Hood

(2008). Poptools [Computer software]. Canberra: Pest Animal Control Co-operative research Center (CSIRO).

11.

Hollenstein

Lewis

M. D.

(2006). A state space analysis of emotion and flexibility in parent-child interactions. Emotion, 6, 656–662.

12.

Hosenfeld

Van

DER

Maas

H. L. J.

Van

DEN

Boom

D. C.

(1997). Indicators of discontinuous change in the development of analogical reasoning. Journal of Experimental Child Psychology, 64, 367–395.

13.

Howe

C. J.

(1981). Interpretive analysis and role semantics: a ten-year misalliance? Journal of Child Language, 8, 439–456.

14.

Lewis

M. D.

Lamey

Douglas

(1999). A new dynamic systems method for the analysis of early socioemotional development. Developmental science, 2 (4), 457–475.

15.

Mandler

J. M.

(2006). Actions organize the infant's world. Hirsh-Pasek

In K.

Golinkoff

R. M.

(Eds.), Action meets word: How children learn verbs (pp. 111–133). New York, NY: Oxford University Press.

16.

Miller

P. H.

(2002). Order in Variability, Variability in Order. Human Development, 45, 161–166.

17.

Siegler

R. S.

(1995). How does change occur: A microgenetic study of number conservation. Cognitive Psychology, 28, 225–273.

18.

Slegler

(1996). Emerging minds: The process of change in children's thinking. New York, NY: Oxford University Press.

19.

Slegler

(2007). Learning about learning. Ladd

In G. W.

(Ed.), Appraising the human developmental sciences: Essays in honor of Merrill-Palmer Quarterly (pp. 67–82). Detroit, MI: Wayne State University Press.

20.

Slmonoff

J. S.

(1996). Smoothing methods in statistics. New York: Springer Verlag.

21.

Steenbeek

Van Geert

(2007). The Empirical Validation Of A Dynamic Systems Model Of Interaction; Do Children Of Different Sociometric Statuses Differ In Their Dyadic Play Interactions? Developmental Science, 11, 253–281

22.

Thelen

Smith

L. B.

(1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA: MIT-Press.

23.

Thordardottir

E. T.

Weismer

S. E.

(1998). Mean length of utterance and other language sample measures in early Icelandic. First Language, 18 (52), 1–32.

24.

Todman

J. B.

Dugard

(2001). Single-case and small-n experimental designs: A practical guide to randomization tests. Mahwah, NJ: Erlbaum.

25.

Tomasello

(1987). Learning to use prepositions: a case study. Journal of Child Language, 14, 79–98.

26.

Valian

(1986). Syntactic categories in the speech of young children. Developmental Psychology, 22, 562–579.

27.

Van Dijk

Van Geert

(2005). Disentangling behavior in early child development: Interpretability of early child language and its effect on utterance length measures. Infant Behavior and Development, 28, 99–117.

28.

Van Dijk

Van Geert

(2007). Wobbles, humps and sudden jumps: A case study of continuity, discontinuity and variability in early language development. Infant and Child Development, 16, 7–33.

29.

Van Geert

Van Dijk

(2002). Focus on variability: New tools to study intra-individual variability in developmental data. Infant Behavior & Development, 25, 340–374.

30.

Van Geert

P. L. C.

Van Dijk

(2003). The problem of inter-observer reliability in ambiguous observation data. First Language, 23, 259–284.

31.

Verspoor

Lowie

Van Dijk

(2008). Variability in L2 development from a dynamic systems perspective. Modern Language Journal, 92, 214–232.