Book chapter 2022

PLS-Based Structural Equation Modelling: An Alternative Approach to Estimating Complex Relationships Between Unobserved Constructs

BE
Business Education, Universität Kassel
 HF
Hilkenmeier, Frederic
Professional and Practice-based Learning
Journal · Vol. 33 · pp. 269-292
Abstract

A traditional approach to test complex relationships between different unobserved constructs included in theoretical models is to apply covariance-based structural equation modelling (CB-SEM). This chapter aims at introducing an alternative approach to estimating structural equation models that has not yet widely been used in research on professional learning and development or in research on learning in general: Partial-least squares structural equation modelling (PLS-SEM). PLS-SEM is based on ordinary least square regression analysis and uses an iterative algorithm to find parameter estimates. This estimation approach has several advantages including fewer statistical assumptions. In addition, PLS-SEM allows for the incorporation of both lower order and higher order formative constructs as well as for estimating rather complex models, which is not always possible with CB-SEM. The conceptual explanation of this particular SEM technique will be illustrated using a replication study of a published research study, focussing on the influence of learner factors and learning context on different professional learning activities. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Author Keywords

workplace learning Professional Development informal learning SEM Learning culture Partial Least Square PLS

Index Keywords

Author Affiliations
Institute of Educational Science, Paderborn University, Paderborn, Nordrhein-Westfalen, Germany
Hochschule Fresenius, Idstein, Hessen, Germany
Funding & Acknowledgements
No funding information
References 10 References
1 Ajzen, Icek, The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 2, pp. 179-211, (1991)
2 Bauer, Johannes, A Primer to Latent Profile and Latent Class Analysis, Professional and Practice-based Learning, 33, pp. 243-268, (2022)
3 Technology Studies, (1995)
4 Bollen, Kenneth Alan, Latent variables in psychology and the social sciences, Annual Review of Psychology, 53, pp. 605-634, (2002)
5 Bollen, Kenneth Alan, A tetrad test for causal indicators, Psychological Methods, 5, 1, pp. 3-22, (2000)
6 Butler, Jim E., The learning context within technical and further education colleges as perceived by apprentices and their workplace supervisors, Journal of Vocational Education and Training, 50, 1, pp. 79-96, (1998)
7 Cangialosi, Nicola, Learning Climate and Innovative Work Behavior, the Mediating Role of the Learning Potential of the Workplace, Vocations and Learning, 13, 2, pp. 263-280, (2020)
8 Cerasoli, Christopher P., Antecedents and Outcomes of Informal Learning Behaviors: a Meta-Analysis, Journal of Business and Psychology, 33, 2, pp. 203-230, (2018)
9 Cheng, Eddie W.L., The influence of job and career attitudes on learning motivation and transfer, Career Development International, 6, 1, pp. 20-28, (2001)
10 Technology Studies, (1995)
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