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The quality of self-determined learning motivation in two educational settings – a person-centered approach / Florian H. Müller ; Irina Andreitz ; Almut E. Thomas ; Barbara Hanfstingl ; Marko Palekčić.

By: Müller, Florian H.
Contributor(s): Palekčić, Marko [aut].
Material type: ArticleArticleDescription: 99-100 str.Other title: The quality of self-determined learning motivation in two educational settings - a person-centered approach [Naslov na engleskom:].Subject(s): 5.06 | self-determination theory, learning motivation, two educational settings, learning environment and outcomes, achievement. hrv | self-determination theory, learning motivation, two educational settings, learning environment and outcomes, achievement eng In: International Conference on Motivation. Motivation in all Spheres of Live (Frankfurt: August, 28– 30.8. 2012 ; Frankfurt) Thomas Martens, Regina Vollmeyer, Kathrin Rakoczy (Eds.) International Conference on Motivation. Motivation in all Spheres of Live Program & Abstracts Pabst Science Publisheres: Lengerich, Berlin, Bremen, Miami, Riga, Viernheim, Wien, Zagreb, p. 99-100 str. 99-100Thomas Martens, Regina Vollmeyer, Kathrin RakoczySummary: Self-determination theory (SDT)( Deci & Ryan, 2002) allows a differentiated analysis of the qualities of motivation distinguishing autonomous and controlled forms of regulation. Previous studies in education mostly investigated the relation between autonomous vs. controlled motivation, need satisfaction and learning outcomes applying a variable - centered approach. In contrary to this approach the both present studies identify personal profiles of motivational regulation styles and examine how these clusters are associated with the perceived learning environment and learning outcomes. The participants in study 1were 4, 417 students from all types of compulsory secondary schools. In study II the questionnaires were administered to 1, 625 university students. Results of both studies revealed the presence of a four-cluster solution, reflecting different levels of autonomous and controlled learning motivations. Across validation of the clusters revealed high Cohen’s kappa coefficients. The results indicate slight differences in the type structure of school and university students. Findings generally favored the both high quality motivation clusters displayed the most optimal learning pattern and scored highest on perceived need-supportive learning environment, relevance, teachers’ enthusiasm as well as on achievement. Overall, these findings point out (1) that cluster analysis is useful in the understanding of the complex relationship between learning motivation, learning environment and outcomes and (2) that the quality of motivational clusters can thoroughly differ according to settings.
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URL internet adrese: http://www.icm2012.de/program/ICM2012_Printprogram.pdf PAP-06: 4

Self-determination theory (SDT)( Deci & Ryan, 2002) allows a differentiated analysis of the qualities of motivation distinguishing autonomous and controlled forms of regulation. Previous studies in education mostly investigated the relation between autonomous vs. controlled motivation, need satisfaction and learning outcomes applying a variable - centered approach. In contrary to this approach the both present studies identify personal profiles of motivational regulation styles and examine how these clusters are associated with the perceived learning environment and learning outcomes. The participants in study 1were 4, 417 students from all types of compulsory secondary schools. In study II the questionnaires were administered to 1, 625 university students. Results of both studies revealed the presence of a four-cluster solution, reflecting different levels of autonomous and controlled learning motivations. Across validation of the clusters revealed high Cohen’s kappa coefficients. The results indicate slight differences in the type structure of school and university students. Findings generally favored the both high quality motivation clusters displayed the most optimal learning pattern and scored highest on perceived need-supportive learning environment, relevance, teachers’ enthusiasm as well as on achievement. Overall, these findings point out (1) that cluster analysis is useful in the understanding of the complex relationship between learning motivation, learning environment and outcomes and (2) that the quality of motivational clusters can thoroughly differ according to settings.

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