Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 428702
Title Nutrient analysis explained for non-chemists by using interactive e-learning material
Author(s) Busstra, M.C.; Hulshof, P.J.M.; Houwen, J.; Elburg, L.; Hollman, P.C.H.
Source Journal of Food Composition and Analysis 25 (2012)1. - ISSN 0889-1575 - p. 88 - 95.
DOI https://doi.org/10.1016/j.jfca.2011.07.003
Department(s) Chair Nutrition and Disease
Chair Nutrition and Health over the Lifecourse
Human Nutrition (HNE)
Rikilt B&T Toxicologie en Effectanalyse
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) instructional-design - quality
Abstract The diverse educational and professional background of individuals involved in food composition data work presents challenges in their training. In particular, it is difficult to explain chemical analysis of nutrients to individuals lacking a background in chemistry. Therefore an interactive e-learning module entitled “Nutrient Analysis for Non-chemists” was developed. Interactive e-learning provides a powerful set of tools to stimulate a learning process tailored to the needs and background of course members. In its design, specific aims derived from theories on learning and instruction were first formulated: motivate the student; provide an authentic learning context; visualize important concepts; promote active learning; and avoid unnecessary cognitive load. The e-learning module developed contains a large variety of interactive exercises, animations, and background information. The following four topics or cases were elaborated: Fats and Fatty Acids, Proteins and Amino Acids, Carbohydrates and Fiber, and Elements. In diverse educational settings, the module was evaluated by course members of postgraduate courses who highly appreciated it with an overall score of 4.5 on a 5-point scale. The e-learning module that was developed can be nicely integrated into a blended learning course on food composition data. However, it is also very well suited for individual distance learning
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