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In our cognitive motivational process model (Vollmeyer & Rheinberg, Zeitschrift für Pädagogische Psychologie, 12:11–23, 1998) we assume that initial motivation affects performance via motivation during learning and learning strategies. These variables are also central for self-regulation theories (e.g., M. Boekaerts, European Psychologist, 1:100–122, 1996). In this article we discuss methods with which the model can be tested. Initial motivation with its four factors challenge, probability of success, interest, and anxiety was measured with the Questionnaire on Current Motivation (QCM; Rheinberg, Vollmeyer, & Burns, Diagnostica, 47:57–66, 2001). As an indicator for the functional state we assessed flow with the FKS (Rheinberg, Vollmeyer, & Engeser, Diagnostik von Motivation und Selbstkonzept [Diagnosis of Motivation and Self-Concept], Hogrefe, Göttingen, Germany, 261–279, 2003). We also used different tasks, including a linear system, a hypermedia program, and university-level classes. In general, our methods are valid and with them we found support for our model.
As meta-analyses demonstrate feedback effects on performance, our study examined possible mediators. Based on our cognitive-motivational model [Vollmeyer, R., & Rhemberg, F. (1998). Motivationale Einflusse auf Erwerb und Anwendung von Wissen in einem computersimulierten System [Motivational influences on the acquisition and application of knowledge in a simulated system]. Zeitschrift fur Padagogische Psychologie, 12, 11-23] we examined how feedback changed (1) strategies, and (2) motivation during learning, and by doing so improved (3) final performance. Students (N = 211) learned how a dynamic system works and how to reach given goal states for the system. One group received feedback (i.e., knowledge of performance) the other one did not. We expected learners to improve after they received the first feedback. However, we found that learners expecting feedback used better strategies right from the start. Thus, they acquired more knowledge over fewer trials. Although we had also expected effects of feedback on motivation during learning, we could not support this hypothesis. (c) 2005 Elsevier Ltd. All rights reserved
Motivationale Einflüsse auf Erwerb und Anwendung von Wissen in einem computersimulierten System
(1998)
What makes computer users spend their free time working with the computer? Are there different types of users and, if so, in what ways do they differ? N = 271 subjects took part in an online survey concerning the incentives for computer use in free time. Selected mailing lists were used to identify highly committed users (A4 3.9 hours of free time a day spent working with computers). The following incentive factors were found for these users: community/ affiliation; sense of competence; flexibility/utility; avoidance of boredom; rebellious tendency to illegality. Depending on their favorite use of the computer, three types of users were found: Purposeful users (58%), hackers (entering other networks without intention to cause damage) (22%), and crackers (entering other networks with intention to cause damage) (20%). There are significant differences in the incentive profiles of these types of users. Hacking and cracking, but not purposeful use, are correlated with flow experience and positive activation. These findings are not representative for all leisure time computer users. They refer to a sample of highly committed users who can be reached in special associations (e.g., relevant student networks, the Chaos Computer Club)
What makes computer users spend their free time working with the computer? Are there different types of users and, if so, in what ways do they differ? N = 271 subjects took part in an online survey concerning the incentives for computer use in free time. Selected mailing lists were used to identify highly committed users (A4 3.9 hours of free time a day spent working with computers). The following incentive factors were found for these users: community/ affiliation; sense of competence; flexibility/utility; avoidance of boredom; rebellious tendency to illegality. Depending on their favorite use of the computer, three types of users were found: Purposeful users (58%), hackers (entering other networks without intention to cause damage) (22%), and crackers (entering other networks with intention to cause damage) (20%). There are significant differences in the incentive profiles of these types of users. Hacking and cracking, but not purposeful use, are correlated with flow experience and positive activation. These findings are not representative for all leisure time computer users. They refer to a sample of highly committed users who can be reached in special associations (e.g., relevant student networks, the Chaos Computer Club)
Ovlivnovani ucebni motivace
(2001)
Motivationstraining
(2000)
Lehrende in Schulen
(2001)
Dem Text liegt ein Vortrag zugrunde, der auf dem 31. Motivationspsychologischen Kolloquium (MPK) in Heidelberg 2015 gehalten wurde. Im ersten Teil bietet er einen Überblick über die Motivationsforschung am Bochumer Heckhausen-Lehrstuhl in den 70er-Jahren („Bochumer Schule“). Dabei werden neben Heinz Heckhausen einzelne Mitarbeiter und ihre Schwerpunkte vorgestellt sowie das stimulierende Arbeitsklima an diesem Lehrstuhl beschrieben. Entsprechend der Vortragseinladung wird im Anschluss die Entwicklung der eigenen Forschungsschwerpunkte skizziert. Noch unter Heckhausens Leitung waren dies zunächst die Forschung zur Bezugsnormorientierung und die Einzelfallanalysen zur Lernmotivation mit dem Erweiterten Kognitiven Motivationsmodell. Danach geht der Vortrag auf Forschungsthemen ein, die dann in Heidelberg und Potsdam dazukamen. Hier geht es um die Erforschung von Tätigkeitsanreizen und um das Flow-Erleben. Abschließend wird der Potsdamer Versuch skizziert, herauszufinden, auf welche Weise unterschiedliche Motivationsqualitäten den Lernprozess und seine Resultate beeinflussen.
Motivationsdiagnostik
(2006)
Bezugsnorm-Orientierung
(2006)
Bezugsnormorientierung
(2006)