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Goal orientation profiles and task performance growth trajectories

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Abstract

Goal orientation theories were used to generate predictions regarding the moderating effect of goal orientation profiles on task performance growth trajectories. Participants were given multiple trials of practice on an air traffic control task. Analyses were conducted using growth curve modeling. As expected, individuals with high performance-approach orientation improved their task performance scores faster than their counterparts. The interaction between mastery and performance-avoid orientations moderated the performance growth curve such that individuals with high mastery and low performance-avoid orientation improved their performance at the fastest rate. The interaction between performance-approach and performance-avoid orientations also moderated the performance growth curve. Individuals with low performance-approach and high performance-avoid orientation improved their performance at the slowest rate. These findings contribute to theory and practice by elucidating how various combinations of goal orientations influence the rate of skill acquisition.

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Notes

  1. Note that researchers have conceptualized additional dimensions of goal orientation such as mastery-avoidance orientation (Elliot and McGregor 2001) and normative ability goals (similar to performance-approach orientation except that the focus is on intelligence rather than performance outcomes) (Grant and Dweck 2003).

  2. Results presented are based on a model with a homogenous error structure. A model with an autoregressive error structure was significantly different from the unrestricted model, χ2(427) = 675.99, p < .001, however it was not significantly different from the model with a homogenous error structure, χ2(1) = 2.27, p < .001. Therefore, we report results from the more parsimonious homogenous model. The substantive interpretation of results did not differ between the homogenous and autoregressive models.

  3. A follow-up model indicated that the three-way interaction among the goal orientation dimensions significantly predicted the quadratic trajectory (but not the linear trajectory). However, this parameter increased rather than decreased the explained variance in the model, which casts doubt on the validity of this result.

  4. We thank our Associate Editor, Ruth Butler, for this suggestion.

  5. Please note that a follow-up analysis of these data (as reported in Harackiewicz et al. 2002a) indicated that the interaction between mastery and performance-approach orientations did not predict performance on the follow-up test. However, this analysis involved only one measurement of performance. The point here is that if the effects of mastery orientation on performance take time to emerge, then any effects of mastery orientation on performance growth trajectories may only emerge over extended periods of observation.

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  1. School of Psychology, University of Queensland, Brisbane, 4072, Australia

    Gillian B. Yeo, Tamma Sorbello & Annette Koy

  2. Goldsmiths, University of London, London, UK

    Luke D. Smillie

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Yeo, G.B., Sorbello, T., Koy, A. et al. Goal orientation profiles and task performance growth trajectories. Motiv Emot 32, 296–309 (2008). https://doi.org/10.1007/s11031-008-9099-8

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