Within NHL Stenden University of Applied Science, a choice for a new virtual learning environment was made in mid-2021, primarily on policy and management grounds. Early in the migration process, it became clear that this approach could perturb the further rollout of the Design-Based Education (DBE, https://edu.nl/mwp8j) educational concept. Four templates were developed to intertwine technological and educational processes that structure different ways of "blended" learning and teaching within DBE. Initial user experiences show that the templates’ structures help teachers reconsider online learning activities to shape and facilitate blended DBE learning processes.
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In tourism management, traditional input-output models are often applied to calculate economic impacts, including employment impacts. These models imply that increases in output are translated into proportional increases in labour, indicating constant labour productivity. In non-linear input- output (NLIO) models, final demand changes lead to substitution. This causes changes in labour productivity, even though one unit of labour ceteris paribus still produces the same output. Final demand changes can, however, also lead to employees working longer, harder and/or more efficiently. The goal of this article is to include this type of 'real' labour productivity change into an NLIO model. To do this, the authors introduce factor augmenting technical change (FATC) and a differentiation between core and peripheral labour. An NLIO model with and without FATC is used to calculate the regional economic impacts of a 10% final demand increase in tourism in the province of Zeeland in the Netherlands. Accounting for real productivity changes leads to smaller increase in the use of labour, as productivity increases allow output to be produced using fewer inputs.
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Habitual behavior is often hard to change because of a lack of self-monitoring skills. Digital technologies offer an unprecedented chance to facilitate self-monitoring by delivering feedback on undesired habitual behavior. This review analyzed the results of 72 studies in which feedback from digital technology attempted to disrupt and change undesired habits. A vast majority of these studies found that feedback through digital technology is an effective way to disrupt habits, regardless of target behavior or feedback technology used.
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