Scientific reasoning in early and middle childhood: The development of domain‐general evidence evaluation, experimentation, and hypothesis generation skills

Abstract

According to Klahr's (2000, 2005; Klahr & Dunbar, 1988) Scientific Discovery as Dual Search model, inquiry processes require three cognitive components: hypothesis generation, experimentation, and evidence evaluation. The aim of the present study was to investigate (a) when the ability to evaluate perfect covariation, imperfect covariation, and non-covariation evidence emerges, (b) when experimentation emerges, (c) when hypothesis generation skills emerge, and (d), whether these abilities develop synchronously during childhood. We administered three scientific reasoning tasks referring to the three components to 223 children of five age groups (from age 4.0 to 13.5 years). Our results show that the three cognitive components of domain-general scientific reasoning emerge asynchronously. The development of domain-general scientific reasoning begins with the ability to handle unambiguous data, progresses to the interpretation of ambiguous data, and leads to a flexible adaptation of hypotheses according to the sufficiency of evidence. When children understand the relation between the level of ambiguity of evidence and the level of confidence in hypotheses, the ability to differentiate conclusive from inconclusive experiments accompanies this development. Implications of these results for designing science education concepts for young children are briefly discussed.

Development of Science Process Skills in the Early Childhood Years

“…In situations where there are no strong prior beliefs and the outcomes are equally plausible, preschoolers were able to correctly interpret perfect and partial covariation evidence, but they showed considerable diffi cultly dealing with non-covariation evidence. Piekny and Maehler ( 2013 ) found a similar pattern of results with respect to preschoolers' abilities to interpret perfect, partial, and noncovariation evidence. Even older children (aged 10-14) have diffi culty with the concept of non-covariation (Kanari & Millar, 2004 ).…”

Diagrams support revision of prior belief in primary-school children

“…In their study, Koerber and colleagues presented children with a hypothesis held by a story character and a set of covariation data (perfect and imperfect covariations, noncovariation) that contradicted the protagonist's hypothesis. Most five-year-olds successfully attributed a belief revision to the protagonist when the relation presented in the data was straightforward (perfect covariation), showing that they are able to successfully interpret simple patterns of data without any distortions and to incorporate this new evidence into their theories (see also Piekny & Maehler, 2013;van der Graaf, Segers, & Verhoeven, 2016, for a replication of these findings). These confirmatory findings of early data interpretation skills are in line with a growing literature on early preschool and primary school scientific thinking, which shows that already young children possess a basic understanding of the distinction between hypothesis and evidence (Mayer, Koerber, Sodian & Schwippert, 2014;Sandoval, Sodian, Koerber, & Wong, 2014).…”

Scientific Concepts: Development in Children

“…In a simple study of a single cause, for example, children as young as 5 years can evaluate how evidence relates to a cause (Ruffman et al, 1993), and children as young as 4 years can predict how another person will change a prior belief with new covarying evidence (Koerberg et al, 2005). Preschool children were relatively good at drawing conclusions from perfect and partial covariation data (Piekny and Maehler, 2012), but even older children -10-14 year olds -had difficulty interpreting noncovarying data (Kanari and Millar, 2004). Another source of difficulty for children is interpreting data that is inconsistent with their own beliefs, even with perfect covariation but especially with partial covariation (Koerber et al, 2005), though this finding is consistent with the performance seen in older children and even adults (Zimmerman and Croker, 2013).…”

“…For example, young children choose the better of two simple experiments in providing useful information, but are not very good at designing unconfounded experiments themselves until around third grade (Sodian et al, 1991;Piekny and Maehler, 2012) or even later (Bullock and Ziegler, 1999). Similar to their ability to reason about causal relationships in the studies discussed above, children can begin to use statistical information about covariance to reason and make conclusions from evidence, though this ability is limited by the complexity of the information children are given.…”