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The Mechanisms of Peer-Effects in Education: A Frame Factor Analysis
Jönköping University, School of Education and Communication, HLK, Praktiknära utbildningsforskning (PUF), Epistemic Cultures & Teaching Practices.ORCID iD: 0000-0002-3516-9346
2021 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

An extensive body of literature in the economic sciences has focused upon peer effects in education, showing that peer effects exist (Yeung & Nguyen-Hoang, 2016; Ewijk & Sleegers, 2010). In this literature, attention has been brought to the fact that the mechanisms creating the peer effects are still to a large extent hidden in obscurity (Lazear, 2001; Rutter & Maughan, 2002). In this research, distinctions are made between employing exogenous or endogenous independent variables for explaining peer effects (Epple & Romano, 2011). Research using endogenous variables (i.e. measures of students’ aptitude, prior knowledge or behaviour) shed some light on the issue of mechanisms creating peer effects, for instance reporting on the importance of counteracting disruptive classroom behaviour as a means to decrease influence of negative peer effects on student outcomes (Lavy, Paserman, & Schlosser, 2011; Bäckström, 2020).

The issue of peer effects is also addressed in educational sciences, but not as explicitly as in the economic sciences. In educational research it has been labelled as “contextual” or “compositional” effects (Dreeben & Barr, 1988). This literature investigates the peer effects in a wider scope, including issues such as why smaller classes would be better than large classes (Bourke, 1986; Blatchford et al, 2007) or how instruction is affected by class composition (Dumay & Dupriez, 2007; Hansson, 2011).

In educational sciences, there has been a theoretical debate concerning whether teachers’ instruction is dependent or independent of class composition. Benjamin Blooms’ model of Mastery Learning argues that teachers’ instruction is (or should be) independent of class composition, whilst Urban Dahllöfs’ emerging frame factor theory suggest that it is dependent of class composition (Barr & Dreeben, 1977). If the latter is true, I argue that this must be interpreted as a peer effect on instruction, probably also causing peer effects on student results.

The overall aim of the study presented in this paper is to test this argument, that the frame factor theory [ramfaktorteorin] (as later put forward by Ulf P. Lundgren, 1972) can be applied to the issue of peer effects.

At heart of the theory is the concept of “time needed” for students to learn a certain curricula unit, as it was suggested by John Carroll (1963). The relations between class-aggregated time needed and the actual time available, steers and hinders the actions possible for the teacher according to the theory. The theory predicts that the timing and pacing of the teachers’ instruction is governed by a “criterion steering group” (CSG), namely the pupils in the 10th-25th percentile of the aptitude distribution in class. Previous studies of Dahllöf (1967; 1971), Lundgren (1972) and Beckerman and Good (1981) report evidence of this hypothesis. The class composition hereby set the possibilities and limitations for instruction, creating peer effects on individual outcomes.

To test if the theory can be applied to the issue of peer effects, I employ multilevel structural equation modelling (M-SEM) on Swedish TIMSS 2015-data (Trends in International Mathematics and Science Study). Using confirmatory factor analysis (CFA) in the SEM-framework in MPLUS, I first specify latent variables according to the theory, such as “limitations of instruction” from TIMSS survey items. The results indicate a good model fit to data of the measurement model.

The preliminary results from this ongoing study verify a relation between the mean level of the CSG and the latent variable of limitations on instruction, a variable which have a great impact on individual students’ test results. The analysis hereby confirms the predictions derived from the theory and reveals that one important mechanism creating peer effects in student outcomes is the effect class composition has upon the teachers’ instruction.

Place, publisher, year, edition, pages
2021.
National Category
Didactics
Identifiers
URN: urn:nbn:se:hj:diva-54281OAI: oai:DiVA.org:hj-54281DiVA, id: diva2:1586109
Conference
ECER 2021, Geneva (online), 6-10 September 2021
Available from: 2021-08-19 Created: 2021-08-19 Last updated: 2021-08-19Bibliographically approved

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