Spatial Training in Preschool: Identifying the Malleable Factors
Description:Co-Principal Investigator: Kathy Hirsh-Pasek (Temple University)
Purpose: A growing body of literature reveals the importance of early spatial abilities to later success in science, technology, engineering, and math (STEM) fields. Yet by the time American children have entered school, they are already lagging behind their peers in other countries. Preschool children can learn important spatial and mathematical concepts but our current instructional approaches do not foster or support their understanding of STEM concepts. The purpose of this project is to understand how three malleable factors (modeling and feedback; gesture; and spatial language) tested across two platforms (concrete and digital delivery) affects children’s spatial skills. The results of this project are expected to add to the literature on children’s spatial reasoning and how that reasoning relates to early mathematics skill.
Project Activities: Research activities will identify the malleable factors associated with improvements in three year olds’ spatial skills; describe the relationship between spatial learning and mathematics skills; and compare the delivery of the malleable factors (i.e., modeling and feedback; gesture; language) in spatial assembly using concrete and digital formats. First, researchers will conduct three sets of exploratory experiments in order to examine three malleable factors: 1) providing nonverbal feedback and modeling; 2) teaching children to gesture with their hands as a way to anticipate piece placement; and 3) the provision of spatial-relational language and shape names. Second, the researchers will collect data and conduct analyses to examine possible associations between children’s spatial skills and mathematics skills. Finally, the researchers will compare different formats for presenting the malleable factors. That is, to explore how children learn best about spatial assembly, they will examine the differences between performance when working with concrete (i.e., using magnetized geometric pieces that children can handle to recreate the model) versus digital (i.e., use of an electronic delivery device such as a tablet computer to present the stimuli) materials.
Products: The products of this project will be a better understanding of factors related to young children’s spatial skills, knowledge of how spatial reasoning is related to early mathematics skills, and information about potentially promising instructional practices. Peer reviewed publications will also be produced.
Setting: The project will be carried out in a university preschool, private preschools and Head Start programs in Delaware and Pennsylvania.
Sample: The researchers will recruit approximately 480 three-year-old children from Head Starts (low-SES), a university preschool (mid-SES) and private preschools (mid- to high-SES) to participate in these exploratory studies.
Intervention: Due to the nature of the study, there is no formal intervention. Researchers will examine the use of three malleable factors (i.e., providing nonverbal feedback and modeling; use of gestures; and use of spatial language and labels) that may be incorporated into a future intervention.
Research Design and Methods: Over the course of four years, the researchers will conduct three multi-part studies to investigate potentially malleable factors in children’s spatial assembly skills. They will evaluate improvements in children’s spatial skills in response to three malleable factors (modeling and feedback; gesture; and spatial language) tested across two platforms (concrete versus digital) and three conditions (concrete versus digital versus control). Each study will include a pre-test, five instructional sessions for children in the experimental groups, and a post-test. In Year 1, the researchers will complete development of the software application that will be used to deliver the digital version of each malleable factor, and will examine whether children can learn new spatial skills without explicit instruction. In Year 2, the researchers will examine whether children learn better when asked to use gestures to demonstrate their answer prior to responding. In Year 3, the researchers will examine whether language helps children to focus on, encode and reproduce spatial relationships. In Year 4, the researchers will summarize and interpret the results from all study conditions and comparisons of malleable factors.
Control Condition: The children in the control condition will receive pre- and post-tests but no instruction.
Key Measures: Parents will complete a pretest questionnaire to provide information about family demographic characteristics (e.g., socioeconomic status) and children’s exposure to spatial language, spatial play, and media use. The dependent measures will be three tests of spatial skill, two tests of mathematics skill, and a vocabulary test. Two researcher-developed measures, the 2-Dimensional Test of Spatial Assembly (2-D TOSA) and the 3-Dimensional Test of Spatial Assembly (3-D TOSA) will be administered to each child. The Beery Visual Motor Integration Test & Motor Subtest-6th Edition VMI will be used to assess children’s visual and motor abilities by coding the accuracy with which children copy drawings of simple designs made of lines and geometric forms. The Woodcock-Johnson III Applied Problems subtest and the Early Math Assessment System will be used to assess children’s early math skills. The Woodcock-Johnson III Picture Vocabulary test will also be administered to participating children.
Data Analytic Strategy: Researchers will conduct regression analyses to examine the associations between the malleable factors, the two delivery platforms, and children’s spatial and math skills. Predictors for the multiple regression analyses will be the nine experimental conditions: Modeling and Feedback-Concrete, Digital, and Control; Gesture-Concrete, Digital, and Control; and Spatial Language and Shape Names-Concrete, Digital, and Control. Analyses will also be conducted to explore possible gender by condition and SES by condition interactions.