Literature DB >> 29795820

Operationalizing Levels of Academic Mastery Based on Vygotsky's Theory: The Study of Mathematical Knowledge.

Peter Nezhnov1, Elena Kardanova2, Marina Vasilyeva3, Larry Ludlow3.   

Abstract

The present study tested the possibility of operationalizing levels of knowledge acquisition based on Vygotsky's theory of cognitive growth. An assessment tool (SAM-Math) was developed to capture a hypothesized hierarchical structure of mathematical knowledge consisting of procedural, conceptual, and functional levels. In Study 1, SAM-Math was administered to 4th-grade students (N = 2,216). The results of Rasch analysis indicated that the test provided an operational definition for the construct of mathematical competence that included the three levels of mastery corresponding to the theoretically based hierarchy of knowledge. In Study 2, SAM-Math was administered to students in 4th, 6th, 8th, and 10th grades (N = 396) to examine developmental changes in the levels of mathematics knowledge. The results showed that the mastery of mathematical concepts presented in elementary school continued to deepen beyond elementary school, as evidenced by a significant growth in conceptual and functional levels of knowledge. The findings are discussed in terms of their implications for psychological theory, test design, and educational practice.

Entities:  

Keywords:  Rasch model; Vygotsky’s theory; mathematics

Year:  2014        PMID: 29795820      PMCID: PMC5965592          DOI: 10.1177/0013164414534068

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


  3 in total

1.  Evidence for the reliability of measures and validity of measure interpretation: a Rasch measurement perspective.

Authors:  E V Smith
Journal:  J Appl Meas       Date:  2001

2.  Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals.

Authors:  Everett V Smith
Journal:  J Appl Meas       Date:  2002

3.  Detecting multidimensionality: which residual data-type works best?

Authors:  J M Linacre
Journal:  J Outcome Meas       Date:  1998
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.