Influence de la motivation sur l’apprentissage d’un système linéaire

Cette étude examine le rôle médiateur de la démarche cognitive, le niveau de motivation à la tâche et l’apprentissage qui en résulte. Quatre dimensions ont été considérées pour définir la motivation initiale : les attentes de réussite, l’anxiété, le défi et l’intérêt. L’analyse de ces dimensions a permis d’identifier trois profils motivationnels. Dans le premier profil qualifié de très motivé, les participants s’attendent à réussir. Intéressés, ils vivent leur défi avec peu d’anxiété. Dans le deuxième, les participants sont dits peu motivés ; leur niveau d’intérêt et d’attentes de réussite s’avère peu élevé. Quant au troisième profil, il est composé de participants qui présentent un faible sentiment de défi et un niveau d’anxiété élevé.This study focuses on the mediating role of the cognitive process, the level of on-task motivation and the learning resulting from it. Four dimensions were considered to define initial motivation : success expectations, anxiety, challenge, and interest. The analysis of these dimensions helped to identify three motivational profiles. In the first profile described as very motivated, the participants expect to succeed. They are interested and face challenges with little anxiety. In the second profile, the participants are known for having a low level of motivation ; their level of interest and success expectations proves to be relatively low. As for the third profile, it is composed of participants who do not feel very challenged and have a high level of anxiety.Este estudio analiza el papel mediador del enfoque cognitivo, el nivel de motivación a la tarea y el aprendizaje que de ello se deduce. Cuatro dimensiones han sido consideradas para definir la motivación inicial : las expectativas de logro, la ansiedad, el desafío y el interés. El análisis de esas dimensiones ha permitido identificar tres perfiles motivacionales. En el primer perfil, designado como motivación alta, los participantes tienen la expectativa de tener éxito.Interesados, viven su reto con poca ansiedad. En el secundo perfil, los participantes son considerados como poco motivados; su nivel de interés y de expectativas de logro es bajo. En cuanto al tercer perfil, está compuesto de participantes que presentan un bajo sentimiento de desafío y un nivel elevado de ansiedad.Diese Studie untersucht die Vermittlerrolle des Erkenntnisvorgangs, den Motivationsgrad bei der Ausführung einer Aufgabe und die Lehre, die sich daraus ergibt. Vier Dimensionen wurden berücksichtigt, um die Anfangsmotivation zu definieren : die Erfolgserwartungen, die Angst, die Herausforderung und das Interesse. Die Analyse dieser Dimensionen hat ermöglicht, drei Motivationsprofile zu identifizieren. Im ersten Profil, das als sehr motiviert qualifiziert ist, erwarten die Teilnehmer erfolgreich zu sein. Da sie interessiert sind, erleben sie eine Herausforderung mit wenig Angst. Im zweiten Profil, betrachtet man die Teilnehmer als wenig motiviert ; ihr Interessenniveau und ihre Erfolgserwartungen erweisen sich als niedrig. Das dritte Profil hingegen, besteht aus Teilnehmern die ein schwaches Herausforderungsgefühl und ein hohes Angstniveau darstellen

Does Hypothesis-Instruction Improve Learning?

Dual space models of problem solving (e.g., Simon & Lea, 1974; Klahr & Dunbar, 1988) assume that the problem space for a task consists of two spaces: an hypothesis space and an experiment space. In hypothesis space, hypotheses about rules governing the task are generated, which can then be tested in experiment space. However, experiment space can be searched by applying the operators even without knowledge about the task. W e predicted that people searching hypothesis space would learn more about the task. To test this claim, two experiments were performed in which subjects had to learn to control a system consisting of three input variables that had unknown links to three output variables. Subjects first explored the task, then they had to reach goal states for the output variables. In both experiments subjects were presented with an hypothesis about one of the links, which should foster search of hypothesis space. In Experiment 1, hypothesis instruction improved performance and we showed that it had a similar effect to a manipulation of goal specificity, suggesting that both factors improve learning by encouraging search in hypothesis space. In Experiment 2 subjects were given a correct hypothesis or an incorrect hypothesis. Both groups performed better than an appropriate control. Thus instructions that encourage hypothesis testing appear to improve learning in problem solving

Goals, Strategies, and Motivation

Goal-specificity has been found to affect performance: In difficult tasks, specific goals may be detrimental for learning. Locke and Latham (1990) claimed that goal-specificity has an impact on performance via motivation. Vollmeyer and Rheinberg's (1998) cognitive-motivational process model proposed that cognitive and motivational processes interact. Therefore, we investigated if goal-specificity may change the nature of this interaction, by trying to fit different structural equations models for groups given a specific goal (SG) or a nonspecific goal (NSG). Before beginning a complex dynamic task, the SG group was given a specific goal to reach, but the NSG group only received a goal when they had to transfer their knowledge. We found that the SG group learnt less and had lower motivation during learning. Contrary to earlier claims, there was no direct effect of goal-specificity on initial motivation, but it did alter the interaction between strategies and motivation during learning. The empirical model for the SG group showed a strong effect of initial motivation on the learning process and goal-directed strategies were effective. For the NSG group motivation during the task and systematic strategies were important

Goal Speciflcity in Hypothesis Testing and Problem Solving

Theories of skill acquisition have made radically different predictions about the role of means-ends analysis in acquiring general rules that promote effective transfer to new problems. Under one view, means-ends analysis is assumed to provide the basis for efficient knowledge compilation (Anderson, 1987), whereas under the alternative view means-ends analysis is believed to disrupt rule induction (Sweller, 1988). We suggest that in the absence of a specific goal people are more likely to use a rule-induction learning strategy, whereas providing a speciflc goal fosters use of means ends analysis, which is a non-rule-induction strategy. We performed an experiment to investigate the impact of goal specificity and systematicity of rule-induction strategies in learning and transfer within a complex dynamic system. Subjects who were provided with a specific goal were able to solve the initial problem, but were impaired on a transfer test using a similar problem with a different goal, relative to subjects who were encouraged to use a systematic rule-induction strategy to freely explore the problem space. Our results support Sweller's proposal that means-ends analysis leads to specific knowledge of an isolated solution path, but docs not provide an effective method for learning the overall structure of a problem space

Gender stereotypes: implicit threat to performance or boost for motivational aspects in primary school?

Based on stereotype threat and stereotype lift theory, this study explores implicit stereotype threat effects of gender stereotypes on the performance of primary school children in mathematics. Moreover, effects of implicit gender stereotypical cues (gender-specific task material) on motivational aspects were explored, which have revealed mixed results in stereotype threat research in the past. N = 151 German primary school children (47.7% female; mean age: M = 9.81, SD = 0.60) calculated either stereotypical or neutral mathematical text problems before motivational aspects were assessed. Contradicting our expectations, results neither revealed a stereotype threat effect on girls’ performance nor a lift effect on the boys. Instead, girls calculating stereotypical tasks outperformed girls in the control group, whereas boys’ performance did not significantly differ compared to the control group. Regarding motivational aspects, only traditional gender differences emerged as girls reported significantly more pressure and tension calculating the mathematical tasks. The discussion focuses on the way in which stereotypes can affect children’s cognitive performance and in turn, their mathematical performance