J
Jimmie Leppink
Researcher at Hull York Medical School
Publications - 122
Citations - 2892
Jimmie Leppink is an academic researcher from Hull York Medical School. The author has contributed to research in topics: Cognitive load & Cognition. The author has an hindex of 23, co-authored 116 publications receiving 2240 citations. Previous affiliations of Jimmie Leppink include University of Toronto & Maastricht University.
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Journal ArticleDOI
Development of an instrument for measuring different types of cognitive load
Jimmie Leppink,Fred Paas,Fred Paas,Cees P. M. van der Vleuten,Tamara van Gog,Jeroen J. G. van Merriënboer +5 more
TL;DR: A ten-item instrument for the measurement of the three types of cognitive load is presented and a three-component solution is revealed, consistent with the types of load that the different items were intended to measure.
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Effects of pairs of problems and examples on task performance and different types of cognitive load
Jimmie Leppink,Fred Paas,Fred Paas,Tamara van Gog,Cees P. M. van der Vleuten,Jeroen J. G. van Merriënboer +5 more
TL;DR: In this article, the authors investigated whether a psychometric instrument can differentiate intrinsic, extraneous, and germane cognitive load, and found that a slightly modified version of the aforementioned psychometric device could help researchers to differentiate intrinsic and extraneous cognitive load.
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The evolution of cognitive load theory and its application to medical education
TL;DR: This review outlines how CLT has evolved and presents a synthesis of current-day CLT principles in a holistic model for medical education design, with suggestions for future research based on this model.
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The promised land of blended learning: Quizzes as a moderator
Ingrid A. E. Spanjers,Karen D. Könings,Jimmie Leppink,Daniëlle Verstegen,Nynke de Jong,Katarzyna Czabanowska,Katarzyna Czabanowska,Jeroen J. G. van Merriënboer +7 more
TL;DR: In this article, a meta-analysis was conducted to examine whether the expectation of improved education is met by blended learning, defined as a combination of face-to-face and online learning, is expected to lead to improved education.
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Exploring task- and student-related factors in the method of propositional manipulation (MPM)
TL;DR: In this article, the authors explore task and student-related factors influencing students' ability to learn from MPM and find that whether students learn from it depends on their statistics proficiency level, the subject matter, the number of propositions in the learning task, and the instructions.