| Title: |
Identifying Reciprocities in School Motivation Research: A Review of Issues and Solutions Associated with Cross-Lagged Effects Models |
| Language: |
English |
| Authors: |
Núñez-Regueiro, Fernando (ORCID 0000-0003-4784-2021); Juhel, Jacques (ORCID 0000-0002-3520-6012); Bressoux, Pascal (ORCID 0000-0001-8018-5612); Nurra, Cécile (ORCID 0000-0001-6830-8851) |
| Source: |
Journal of Educational Psychology. Jul 2022 114(5):945-965. |
| Availability: |
American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org |
| Peer Reviewed: |
Y |
| Page Count: |
21 |
| Publication Date: |
2022 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
High Schools; Secondary Education |
| Descriptors: |
High School Students; Student Motivation; Academic Achievement; High Achievement; Low Achievement; Self Concept; Educational Research; Influences; Structural Equation Models |
| DOI: |
10.1037/edu0000700 |
| ISSN: |
0022-0663; 1939-2176 |
| Abstract: |
Part of the evidence used to corroborate school motivation theories relies on modeling methods that estimate cross-lagged effects between constructs, that is, reciprocal effects from one occasion to another. Yet, the reliability of cross-lagged models rests on the assumption that students do not differ in their trajectories of growth over time (e.g., no high- or low-achievers). The present review explains why deviations from this assumption produce unreliable findings by confounding between- and within-person processes of change. To relax this assumption, next-generation cross-lagged models are presented and illustrated using panel data on high school students (N = 944). These issues and solutions are discussed using, as a case study, the pervading theory that motivation develops as a function of reciprocal effects between beliefs about the self (e.g., academic self-concept) and school achievement. Implications regarding the use of cross-lagged models and knowledge building in school motivation research are discussed. Online supplementary materials containing technical notes on cross-lagged models, as well as open-source data and scripts for R and Mplus, are provided to aid educational researchers use and compare these alternative models. |
| Abstractor: |
As Provided |
| Notes: |
https://osf.io/mrfw4 |
| Entry Date: |
2023 |
| Accession Number: |
EJ1372732 |
| Database: |
ERIC |