Social interaction and conceptual change pave the way away from children's misconceptions about the Earth

Abstract

Throughout development, children undergo moments of abrupt conceptual transitions, often replacing intuitive knowledge with grounded scientific theories. This typically also creates a situation of social conflict, as different children may hold at the same time substantially different theories and explanations about the same phenomenon. The main objective of this work is to understand whether social interaction and exchange of arguments and reasoning may be a catalyzer for conceptual development. Dyads of 7-year-old children with different conceptual understanding of the Earth were asked to reach a consensus about its astronomic and geometric properties. Our results show that mere minutes of deliberation can result in substantial changes in children's conceptual representations, and moreover, that this transition was consistently in the direction of reasoned and scientific opinions. These results provide empirical evidence and suggest specific ways in which peer interaction can be used effectively to promote conceptual change in school settings, in a knowledge domain at the center of this era's post truth and science denial crisis.

Keywords: Cognitive neuroscience; Human behaviour.

Fig. 1

Knowledge level changes after interaction. a Knowledge level was scored in 11 dimensions per session. Differences between interviews of one child (shift, Δ₁₂) and between members of a dyad (gap, Δ_ML) were calculated on a per dimension basis and then averaged. ${\Delta }_{\mathrm{12}}$: knowledge level shift between Interviews 1 and 2, for Children M (${\Delta }_{\mathrm{12}}^M$), L (${\Delta }_{\mathrm{12}}^L$) and control (${\Delta }_{\mathrm{12}}^C$); ${\Delta }_{ML}$: knowledge level gap between Children M and L, in Interviews 1 (${\Delta }_{ML}^{\mathrm{1}}$) and 2 (${\Delta }_{ML}^{\mathrm{2}}$). M1/M2, L1/L2, C1/C2: more knowledgeable (M), less knowledgeable (L), and control (C) children in Interview 1 or 2. b Average knowledge level gap between children in each dyad was significantly smaller after interaction than before. c Shift in knowledge levels. Children L significantly increased their knowledge levels. In contrast, no significant gains or losses were found for either controls or Children M, between whom no significant differences were found either. (*p < 0.05, **p < 0.1, ***p < 0.001, ns: non-significant. Error bars represent SEM, and circles are individual data points)

Fig. 2

Knowledge similarity. a Responses of Children L and M are coded in Interviews 1 (L1 and M1) and 2 (L2 and M2). To assess knowledge similarity, coding of each trait in each channel is compared. In the example, Child L’s and Child M’s Interviews 1 (L1M1) are compared. A trait is said to match if it was given the exact same code in both cases (both children or both interviews) in at least one channel. b Matching of traits within dyads. Children L and their peers matched in significantly more traits after (L2M2) than before (L1M1) interaction. Particularly, Response Adoption (i.e., modification of children’s responses to resemble those of their partners) was significant for Children L (L2M1–L1M1), whereas not for Children M (L1M2–L1M1). LxMy: number of traits matching between Child L in Interview x and Child M in Interview y, with x/y: 1 or 2. c Knowledge shifts led by Response Adoption. Adopted responses are defined as traits matching between a child’s Interview 2 and her partner’s Interview 1, whereas not between them before interaction in Interview 1. Here, adopted responses were divided into groups of positive, negative, or no knowledge level shift. Responses adopted from their partners led to significantly more knowledge gains than either losses or no changes in Children L. (*p < 0.05, **p < 0.01, ***p < 0.001, ns: non-significant. Error bars represent SEM, and circles are individual data points)

Fig. 3

Coding scheme 1: coarse-grained scheme. Participants were first scored with Coding scheme 1 to pair them in dyads for peer interaction. This scheme consisted of three axes, each one scored in a 7-point Likert-type scale: hollow/not-hollow, disc/sphere and dual/not-dual. Representative drawings of extremes responses for each axis are shown. This scheme was based on previously described children’s mental models: (1) the rectangular (flat) earth: with people living on flat ground which extends all the way down below the earth; (2) the disc earth: where flat ground is shaped as a disc; (3) the dual earth: with a flat earth on which people live and another earth suspended in space; (4) the hollow sphere earth: where the earth is suspended in space and people live on flat ground deep inside it; and (5) the flattened sphere earth: with gravity holding people on flattened areas at the earth’s top and bottom^,–

Fig. 4

Coding scheme 2: fine-grained scheme. a Coding scheme. Responses to questionnaire questions are used to code 44 knowledge traits in three channels each. Some of these traits (boxed in gray), with predefined codes at two or more levels of knowledge, are scored from 0 to 1. Finally, to prevent some aspects of knowledge from being over- or underrepresented later in score differences, scored traits belonging to similar topics are combined into 11 dimensions and their scores averaged. b Comparison with Coding scheme 1. We compared Coding scheme 1 used to form dyads and Coding scheme 2 used for data analysis. Each point represents one participant’s interview, with its Coding 2 or mean dimension score and its Coding 1 or mean axis score. A strong correlation between scores from both coding schemes was found. Histograms next to each axis represent score frequencies, with kernel density smoothing function fit in dashed lines