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Originalartikel/Original Articles

Are There Gender Differences in Computer Performance? If So, Can Motivation Explain Them?

Published Online:January 14, 2008https://doi.org/10.1024/1010-0652.21.3.251

Abstract

Abstract. Building on previous research which suggests that females are at a disadvantage when working with computers, the current paper investigates possible explanations. We used the cognitive-motivational process model (Vollmeyer & Rheinberg, 1999, 2000) to explore if motivation can account for the performance differences between male and female students. The model assumes that initial motivation affects strategies and motivation during learning which then influence performance. Male and female students from an introductory statistics class (N = 40), had to solve four statistics tasks with SPSS in 30 minutes. Measurements included initial motivation, functional state (i.e., flow) during task performance, navigation style, and task performance. Results show that males outperform females in terms of time needed for task completion and performance level. Male students displayed more solution-oriented navigation traces than female students. In a tentative exploratory path model, flow-experience and navigation style could be identified as mediating variables. The findings are interpreted in terms of a more effective use of trial-and-error strategies and a preference for tinkering behavior by males.


Gibt es Geschlechtsunterschiede beim Lernen am Computer? Wenn ja, kann Motivation sie erklären?

Zusammenfassung. Bisherige Forschung ergab, dass Frauen bei der Arbeit am Computer benachteiligt sind. Die vorliegende Studie untersucht mögliche Erklärungen. Wir nutzten das kognitiv-motivationale Prozessmodell (Vollmeyer & Rheinberg, 1999, 2000) um zu testen, ob Motivation den Geschlechtsunterschied erklären kann. Das Modell nimmt an, dass die Eingangsmotivation die Strategien und die Motivation während des Lernens beeinflusst, die dann wiederum auf die Leistung wirken. Studenten und Studentinnen einer Einführungsvorlesung in Statistik (N = 40) mussten in 30 Minuten vier Statistikaufgaben mit dem SPSS-Programm bearbeiten. Gemessen wurden die Eingangsmotivation, der funktionale Zustand (i.e., Flow) während der Aufgabenbearbeitung, der Navigationsstil und die Leistung. Die Ergebnisse zeigen, dass die Studenten schneller und besser die Aufgaben bearbeiteten als die Studentinnen. Studenten zeigten einen stärker lösungsorientierten Navigationsstil als Studentinnen. In einer explorativen Pfadanalyse erwiesen sich Flow und der Navigationsstil als Mediatoren. Die Ergebnisse werden so interpretiert, dass Studenten effektivere Versuch-und-Irrtum-Strategien benutzen.

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