Abstract
A dynamical model of approach and avoidance motivation in achievement contexts was recently proposed by Gernigon et al. (2015) as a parsimonious alternative to contemporary models of achievement goals (e.g., Elliot, 2005). The purpose of this doctoral dissertation was to provide the first empirical evidences of the relevance of this model. A first series of studies consisted in developing and validating a questionnaire measuring states of achievement goal involvement according to Elliot et al.'s (2011) 6-goal model: the QIBA-6 (Study 1), as well as a questionnaire measuring the three key social-cognitive variables of the model to be tested (competence expectancies, benefit to the self, and threat to the self that are conveyed by a goal), the interactions of which determine the value of the control parameter k of approach and avoidance motivational attractors: the QSAE (Study 2). A second series of studies was then carried out to test the model and its bases. The first of them (Study 3) led to support some conceptual bases of the model by showing that self- and norm-referenced goals impact self-esteem differently. The last two studies (studies 4 and 5) aimed to validate the dynamic properties of the model. Thus, Study 4 led to support the properties of non-linearity and resistance to change in motivational states, under the influence of gradual variations in the parameter k and in the resulting approach and avoidance attractor landscape. Finally, based on longitudinal data collected in natural achievement contexts (academic and sports), Study 5 enabled the detection of the prevalence of two clusters corresponding to the motivational attractors of approach and avoidance, as well as the characterization of the dynamics of motivational states as mainly modelable in terms of moving average processes, which reflects their environmental sensitivity. The results of this doctoral work provide the first empirical validations of the dynamical model of approach and avoidance in achievement contexts. By showing the utility of the dynamical systems approach, they also invite to continue—via agent-based modeling—the investigation of the emergence of approach and avoidance motivational states as they result from self-organization processes. The model, as currently validated, already offers opportunities for practical applications for anyone (coach, teacher, educator, coach) in charge of the development and maintenance of individuals' motivation in achievement contexts.