Quantity and Variety of Children’s Relational Language During a Semi-Structured Counting Activity

• In Event: 3-227 - Relational Language and Math: Variation Across Types of Language and Math Activities

Integrative Statement

Children’s understanding of language for mathematical relations (e.g., more, before, under) is related to both executive functioning (EF) and math ability (Purpura & Logan, 2015). However, beyond children’s understanding of relational language, children’s production of relational language may shed additional light on children’s understanding of and ability to express mathematical ideas. We observed 34 preschoolers (M=4.7-years-old) engaging in a semi-structured ordinal number activity in pairs over six sessions, led by a trained experimenter (“Magician’s Tricks”, adapted from Building Blocks; Clements & Sarama, 2009; Day-Hess & Clements, 2017). All activity-relevant relational language was identified in order to investigate what factors, such as children’s individual differences and contextual factors (e.g., experimenter use of relational language), may be predictive of children’s relational language use.
During the activity, numbered cards were arranged in order and upside down so that the number was not visible. On each trial, one player pointed to a card and the other guessed the number before flipping it over and explained their thinking. Children were encouraged to use different counting strategies to determine the card’s numerical identity. Additionally, we administered measures of general math knowledge (REMA short-form; Weiland et al., 2012) and EF (MEFS; Carlson & Zelazo, 2014), as well as specific math skills (subtests of the REMA Learning Trajectories; Clements, Sarama, & Liu, 2008): (1) Counting, (2) Comparison and Sequencing, and (3) Shapes (identification and relations).
Overall, most of the relational language used was ordinal (e.g., before; M=5.3 words, 0.08/trial); more so than spatial (e.g., closer; M=1.0 words, 0.02/trial; p<0.001) and magnitude (e.g., bigger; M=0.5 words, 0.009/trial; p<0.001) language.
For children’s individual differences (Table 1), their total number of relational words (i.e., tokens) and unique relational words (i.e., types) were significantly related to their overall math and EF skills. When looking at the specific math skills, children’s production of unique relational words positively correlated with each sub-skill (marginally, p=0.05, for Counting). Similarly, children’s total relational words positively correlated with each subtest, however this was only significant for Shape and marginally for Comparison and Sequencing.
Next, we looked at the relational language children heard during the activity (Table 2), both overall (teacher + other player) and from only the teacher. Children’s relational language was not significantly correlated with child plus teacher or just teachers’ relational language. However, children’s number of unique relational words was significantly related to teachers’ number of unique relational words.
Thus, even in semi-structured activities where the teachers used frequent relational language, children’s math and EF skills predicted the quantity and variety of their own relational language. However, the variety of children’s relational language also significantly related to the variety of teachers’ relational language. Together, these findings suggest that teachers may encourage children’s relational language use (and subsequently, their relational thinking) by using a variety of relational words. Furthermore, although the current analyses focused on children’s math skills measured on standardized assessments, on-going analyses will look at children’s strategies during the actual activity to investigate how relational language may be related to relational strategies, such as counting-on.

Authors

• Michelle A Hurst, University of Chicago
  Presenting Author

• Abrea Greene, University of Chicago
  Non-Presenting Author

• Taylor Praus-Singh, University of Minnesota
  Non-Presenting Author

• Sarah H. Eason, University of Chicago
  Non-Presenting Author

• Michele Mazzocco, University of Minnesota
  Non-Presenting Author

• Amy Claessens, University of Wisconsin
  Non-Presenting Author

• Susan C. Levine, University of Chicago
  Non-Presenting Author