engleski

Untangling sources of inter- and intra-individual variability in learning motivation within Latent State-Trait (LST) framework

Socio-cognitive models of learning motivation have emphasized situational specificity of this process for more than two decades and the need to shift from trait- based to more dynamic conceptualizations and measurement of motivation was highlighted at the beginning of the century. However, when it comes to the assessment of this construct, it seems that studies with a single data point prevail. If learning motivation is measured in two or more time points, then developmental trends are usually considered (i.e. in both cases it is treated as trait-like entity). The paper In this presentation we try towill demonstrate how psychometric theory and repeated measurement design of learning motivation can be usedful to in analyzeing dispositional and situational variability in of learning motivation this processes and its potential correlatessources. Results of two studies will be presented, both anchored in psychometric LST framework (Steyer, Ferring, & Schmitt, 1992). Different latent variables models developed within this framework were used to test hypotheses about situational specificity of learning motivation and sources of its inter- and intra-individual variability. The first study, (conducted on the sample of 153 university students attending one course, ) suggested that self-report measures of learning motivation, contextualized on the course level, can capture variability in learning motivation across different occasions (7 weeks time lag between occasions). However, intrinsic and extrinsic motivation seemed to be different regarding their proneness to situational influences as indicated by consistency and situational specificity coefficients. These results were replicated in the second study (conducted on the sample of 297 university students, ) where hypotheses about personality traits as potential sources of inter- and intra-individual variability inof learning motivation were also formulated and tested via extended SEM models.

learning motivation ; socio-cognitive models ; inter- and intra-individual variability ; Latent State-Trait theory

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