When do children acquire the ability to understand recursion, i.e., repeated loops of actions, as in cookery recipes or computer programs? Hitherto studies have focused either on unconscious recursions in language and vision or on the difficulty of conscious recursions – even for adults – in learning to program. In contrast, we examined 10 to 11 year-old fifth-grader’s ability to deduce the consequences of loops of actions in informal algorithms and to create such algorithms for themselves. In our experiments, the children tackled problems requiring the rearrangements of cars on a toy railway with a single track and a siding – an environment that in principle allows for the execution of any algorithm, i.e., it has the power of a universal Turing machine. The children were not allowed to move the cars, and so each problem’s solution called for them to envisage the movements of cars on the track. We describe a theory of recursive thinking, which is based on kinematic simulations, and which we have implemented in a computer program embodying mental models of the cars and track. Experiment 1 tested children’s ability to deduce rearrangements of the cars in a train from descriptions of algorithms containing a single loop of actions. Experiment 2 assessed children’s spontaneous creation of similar sorts of algorithm. The results showed that fifth-grade children with no training in computer programming have systematic abilities to deduce from, and to create informal recursive algorithms.

Simulation in children’s conscious recursive reasoning

Monica Bucciarelli;
2018-01-01

Abstract

When do children acquire the ability to understand recursion, i.e., repeated loops of actions, as in cookery recipes or computer programs? Hitherto studies have focused either on unconscious recursions in language and vision or on the difficulty of conscious recursions – even for adults – in learning to program. In contrast, we examined 10 to 11 year-old fifth-grader’s ability to deduce the consequences of loops of actions in informal algorithms and to create such algorithms for themselves. In our experiments, the children tackled problems requiring the rearrangements of cars on a toy railway with a single track and a siding – an environment that in principle allows for the execution of any algorithm, i.e., it has the power of a universal Turing machine. The children were not allowed to move the cars, and so each problem’s solution called for them to envisage the movements of cars on the track. We describe a theory of recursive thinking, which is based on kinematic simulations, and which we have implemented in a computer program embodying mental models of the cars and track. Experiment 1 tested children’s ability to deduce rearrangements of the cars in a train from descriptions of algorithms containing a single loop of actions. Experiment 2 assessed children’s spontaneous creation of similar sorts of algorithm. The results showed that fifth-grade children with no training in computer programming have systematic abilities to deduce from, and to create informal recursive algorithms.
2018
1
15
Recursion, Informal algorithms, Deduction, Abduction, Kinematic simulations
Monica Bucciarelli, Robert Mackiewicz, Sangeet S. Khemlani, P. N. Johnson-Laird
File in questo prodotto:
File Dimensione Formato  
Simulation in children's conscious recursive reasoning.pdf

Open Access dal 17/07/2020

Tipo di file: POSTPRINT (VERSIONE FINALE DELL’AUTORE)
Dimensione 1.78 MB
Formato Adobe PDF
1.78 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1670858
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 4
social impact