D
Dirk T. Tempelaar
Researcher at Maastricht University
Publications - 120
Citations - 3076
Dirk T. Tempelaar is an academic researcher from Maastricht University. The author has contributed to research in topics: Blended learning & Learning analytics. The author has an hindex of 24, co-authored 114 publications receiving 2579 citations.
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How achievement emotions impact students' decisions for online learning, and what precedes those emotions
TL;DR: It is concluded that while goal setting behavior only marginally impacts achievement emotions, effort views—a crucial component of the social-cognitive model of implicit theories of intelligence—have a substantial impact on achievement emotions.
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The role of cultural dimensions of international and Dutch students on academic and social integration and academic performance in the Netherlands
Bart Rienties,Dirk T. Tempelaar +1 more
TL;DR: In this article, a cross-institutional comparison among 1275 international students at nine higher educational institutes in the Netherlands, differences in academic performance between Dutch and international students were identified by focussing on their levels of academic and social integration.
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A structural equation model analyzing the relationship of student achievement motivations and personality factors in a range of academic subject-matter areas
TL;DR: In this paper, the authors investigated subject-specificity of achievement motivations in the context of the expectancy-value model, and used structural equation methods to decompose achievement motivations into generic and subject specific components.
Educational innovation in economics and business administration : the case of problem-based learning
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Student profiling in a dispositional learning analytics application using formative assessment
TL;DR: It is conjecture that establishing a chain of antecedent-consequence relationships starting from learning disposition, through student activity in e-tutorials and formative assessment performance, to course performance, adds a crucial dimension to current learning analytics studies: that of profiling students with descriptors that easily lend themselves to the design of educational interventions.