Abstract
This study explores young children’s abstraction of the rules underlying a robot’s emergent behavior. The study was conducted individually with six kindergarten children, along five sessions that included description and construction tasks, ordered by increasing difficulty. We developed and used a robotic control interface, structured as independent concurrent rules. To capture the children’s changing knowledge representations, we have employed a framework that underscores the differences in generality between episodes, a unique sequence of events, scripts, which include repeating temporal patterns, triggered by an environmental condition and rules, atemporal associations between local environmental conditions and the robot’s actions. Our data unravels the progression through which rules are constructed. From an episode that focuses on the robot’s actions, noticing repeated sequences triggered by occasional environmental conditions emerges into scripts. Once both actions and conditions are attributed with similar importance, noticing the co-variance of environmental conditions with robot actions is made possible, bolstering abstraction of atemporal rules. In addition, we have supported the children’s reasoning by helping them attend to relevant features, and compared their spontaneous and supported descriptions. We elaborate on the role of function and mechanism as invariants, and the support of “concrete-abstractions” in the interaction between cognitive schemas and object-embedded abstract schemas, for the children’s evolving explanations of the robot’s behavior.
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Notes
While in algorithmic programming languages, such as flow-charts, rules can contain scripts and scripts can contain rules, the environment we have constructed is based on a different control paradigm, which does not include scripts (e.g. the finite state machine, and the use of ladder diagrams; see Mioduser et al. 1996).
One may conceive of this process as regression in the zone of proximal development. When the task is too complex, the cognitive load is great and one reverts to earlier ways of thinking. We thank Sidney Strauss, Tel-Aviv University, for helping us in this interpretation.
References
Barton, M. E., & Komatsu, L. K. (1989). Defining features of natural kinds and artifacts. Journal of Psycholinguistic Research, 18(5), 433–447.
Bar-Yam, Y. (1997). Dynamics of complex systems. Reading, Mass.: Addison-Wesley, The Advanced Book Program.
Bers, M. U., & Portsmore, M. (2005). Teaching partnerships: Early childhood and engineering student teaching math and science through robotics. Journal of Science Education and Technology, 14(1), 59–73.
Betzer, N. (2002). The knowledge constructing process and the design process constructing among high achiever pupils through Project-Based Learning (PBL). Dissertation. Tel-Aviv University.
Braitenberg, V. (1984). Vehicles: Experiments in synthetic psychology. Cambridge, Massachusetts: The MIT Press.
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18, 32–42.
Carr, M. (2000). Technological affordance, social practice and learning narratives in early childhood setting. International Journal of Technology and Design Education, 10, 61–79.
Cheng, P. W. (1997). From covariation to causation: A causal power theory. Psychological Review, 104, 367–405.
Chi, M. T. H. (2005). Commonsense conceptions of emergent processes: Why some misconceptions are robust. Journal of the Learning Sciences, 14(2), 161–199.
Flavell, J. H., Miller, P. H., & Miller, S. A. (1993). Cognitive development. 3rd ed. NJ: Prentice Hall.
Fleer, M. (1999). The science of technology: Young children working technologically. International Journal of Technology and Design Education, 9, 269–291.
Fleer, M. (2000). Working technologically: Investigations into how young children design and make during technology education. International Journal of Technology and Design Education, 10, 43–59.
Frye, D., Zelazo, P. D., Brooks, P. J., & Samuels, M. C. (1996). Inference and action in early causal reasoning. Developmental Psychology, 32(1), 120–131.
Fujita, M., Kitano, H., & Doi, T. T. (2000). Robot entertainment. In A. Druin & J. Hendler (Eds.), Robots for kids: Exploring new technologies for learning (pp. 37–72). San-Francisco, California: Morgan Kaufmann Publishers.
Gentner, D., & Medina, J. (1998). Similarity and the development of rules. Cognition, 65, 263–297.
Gentner, D. (1978). A study of early word meaning using artificial objects: What looks like a jiggy but acts like a zimbo? Papers and Reports on Child Language Development, 15, 1–6.
Granott, N. (1991a). Puzzled minds and weird creatures: Phases in the spontaneous process of knowledge construction. In I. Harel & S. Papert (Eds.), Constructionism (pp. 295–310). Norwood, New-Jersey: Ablex Publishing Corporation.
Granott, N. (1991b). From macro to micro and back: On the analysis of microdevelopment. Paper presented at the meeting of the Jean Piaget Society, PA.
Hmelo-Silver, C. E., & Pfeffer, M. G. (2004). Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions. Cognitive Science, 28, 127–138.
Hoyles, C., Noss, R., Adamson, R. & Lowe, S. (2001). Programming rules: What do children understand? In Proceedings of the 25rd. Conference of the International Group for the Psychology of Mathematics Education, Vol. 3, pp. 169–176, Utrecht.
Jacobson, M. J. (2001). Problem solving, cognition, and complex systems: Differences between experts and novices. Complexity, 6(3), 41–49.
Jarvis, T., & Rennie, L. J. (1998). Factors that influence children’s developing perceptions of technology. International Journal of Technology and Design Education, 8, 261–279.
Kahn, K. (1996). ToonTalk™ – An animated programming environment for children. Journal of Visual Languages and Computing, 7, 197–217.
Keil, F. C. (1989). Concepts, kinds, and cognitive development. Cambridge, Massachusetts: The MIT Press.
KemlerNelson, D. G. & 11 Swarthmore College Students (1995). Principle-based inferences in young children’s categorization: Revisiting the impact of function on the naming of artifacts. Cognitive development, 10, 347–380.
Klahr, D., Fay, A. L., & Dunbar, K. (1993). Heuristics for scientific experimentation: A developmental study. Cognitive Psychology, 25, 111–146.
Kuhn, D., & Dean, D. Jr. (2004). Connecting scientific reasoning and causal inference. Journal of Cognition and Development, 5(2), 261–288.
Kuhn, D. (1989). Children and adults as intuitive scientists. Psychological Review, 96, 674–689.
Lave, J. (1988). Cognition in practice. Cambridge, UK: Cambridge University Press.
Levy S. T., & Mioduser, D. (2007). Does it “want” or “was it programmed to...”? Kindergarten children’s explanations of an autonomous robot’s adaptive functioning. Accepted for publication in the International Journal of Technology and Design Education.
Maddocks, R. (2000). Bolts from the blue: How large dreams can become real products. In A. Druin & J. Hendler (Eds.) Robots for kids: Exploring new technologies for learning (pp. 111–156). San-Francisco, California: Morgan Kaufmann Publishers.
Markovits, H. (2002). The development of conditional reasoning: A mental model account. Developmental Review, 22, 5–36.
Mioduser, D., Venezky, R. L., & Gong, B. (1996). Student’s perception and design of simple control systems. Computers in Human Behavior, 12(3), 363–388.
Montemayor, J., Druin, A, & Hendler, J. (2000). PETS: A personal electronic teller of stories. In A. Druin & J. Hendler (Eds.), Robots for kids: Exploring new technologies for learning (pp. 73–110). San-Francisco, California: Morgan Kaufmann Publishers.
Morgado, L., Cruz, M. G. B., & Kahn, K. (2001). Working in ToonTalk with 4- and 5-year olds. Paper presented at the Playground International Seminar, April 2001, Porto, Portugal.
Muller, U., Overton, W. F., & Reene, K. (2001). Development of conditional reasoning: A longitudinal study. Journal of Cognition and Development, 2(1), 27–49.
Niazzi, T., & Gopnik, A. (2003). Sorting and acting with objects in early childhood: An exploration of the use of causal cues. Cognitive Development, 18, 299–317.
Overton, W., Byrnes, J. P., & O’Brien, D. P. (1985). Developmental and individual differences in conditional reasoning: The role of contradiction training and cognitive style. Developmental Psychology, 21(4), 692–701.
Papert, S. (1980, 1993). Mindstorms: children, computers, and powerful ideas. 1st and 2nd eds. Cambridge, MA: Basic Books.
Piaget, J., & Inhelder, B. (1948/1956). The child’s conception of space. New-York: Norton.
Piaget, J., & Inhelder, B. (1972). Explanations of machines. In The child’s conception of physical causality (pp. 195–236). New-Jersey: Littlefield Adams & Co.
Resnick, M. (1998). Technologies for lifelong kindergarten. Educational Technology Research & Development. 46(4), 43–55.
Resnick, M., Martin, F., Sargent, R., & Silverman, B. (1996). Programmable bricks: Toys to think with. IBM Systems Journal, 35(3–4), 443–452.
Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Hillsdale, New-Jersey: Lawrence Erlbaum.
Schauble, L. (1990). Belief revision in children: The role of prior knowledge and strategies for generating evidence. Journal of Experimental Child Psychology, 49, 31–57.
Schwartz, D. L., & Black, J. B. (1996). Shuttling between depictive models and abstract rules: Induction and fallback. Cognitive Science, 20, 457–497.
Shanks, D. R. (1995). Is human learning rational? The Quarterly Journal of Experimental Psychology, 48A(2), 257–279.
Siegler, R. S. (1986). Children’s thinking. Englewood-Cliffs, NJ: Prentice-Hall International.
Siegler, R. S., & Chen, Z. (1998). Developmental differences in rule learning: A microgenetic analysis. Cognitive Psychology, 36, 273–310.
Simons, D., & Keil, F. (1995). An abstract to concrete shift in the development of biological thought: The insides story. Cognition, 56, 129–163.
Sobel, D. M., Tenenbaum, J. B., & Gopnik, A. (2004). Children’s causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers. Cognitive Science, 28, 303–333.
Talis, V., Levy, S. T., & Mioduser, D. (1998). RoboGAN: Interface for programming a robot with rules for young children. Tel-Aviv: Tel-Aviv University.
van Duuren, M., Dossett, B., & Robinson, D. (1998). Gauging children’s understanding of artificially intelligent objects: A presentation of “counterfactuals. International Journal of Behavioral Development, 22(4), 871–889.
Vygotsky, L. (1986). Thought and language. Cambridge, Massachusetts: MIT Press.
Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems perspective to making sense of the world. Journal of Science Education and Technology, 8(1), 3–19.
Wyeth, P., & Purchase, H. C. (2000). Programming without a computer: A new interface for children under eight. Paper presented at the User Interface Conference, AUIC, January–February, 2000. First Australasian.
Zimmerman, C. (2000). The development of scientific reasoning skills. Developmental Review, 20, 99–149.
Zuga, K. F. (2004). Improving technology education research on cognition. International Journal of Technology and Design Education, 14, 79–87.
Acknowledgements
We thank Ms. Diana Levy, a graduate student in the Knowledge Technology Lab at Tel-Aviv University, for her assistance in coding the data and performing the initial analysis.
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Mioduser, D., Levy, S.T. & Talis, V. Episodes to scripts to rules: concrete-abstractions in kindergarten children’s explanations of a robot’s behavior. Int J Technol Des Educ 19, 15–36 (2009). https://doi.org/10.1007/s10798-007-9040-6
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DOI: https://doi.org/10.1007/s10798-007-9040-6