181 research outputs found

    Using Open Data as a Material for Introductory Programming Assignments

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    This case study explores why and how open data can be used as a material with which to produce engaging challenges for students as they are introduced to programming. Through describing the process of producing the assignments, and learner responses to them, we suggest that open data is a powerful material for designing learning activities because of its qualities of ease of access and authenticity. We conclude by outlining steps to take in devising and implementing open data-based assignments

    Strength of Protection for Geographical Indications: Promotion Incentives and Welfare Effects

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    We address the question of how the strength of protection for geographical indications (GIs) affects the GI industry\u27s promotion incentives, equilibrium market outcomes, and the distribution of welfare. Geographical indication producers engage in informative advertising by associating their true quality premium (relative to a substitute product) with a specific label emphasizing the GI\u27s geographic origin. The extent to which the names/words of the GI label can be used and/or imitated by competing products—which depends on the strength of GI protection—determines how informative the GI promotion messages can be. Consumers’ heterogeneous preferences (vis-à-vis the GI quality premium) are modeled in a vertically differentiated framework. Both the GI industry and the substitute product industry are assumed to be competitive (with free entry). The model is calibrated and solved for alternative parameter values. Results show that producers of the GI and of the lower-quality substitute good have divergent interests: GI producers are better off with full protection, whereas the substitute good\u27s producers prefer intermediate levels of protection (but they never prefer zero protection because they benefit indirectly if the GI producers’ incentives to promote are preserved). For consumers and aggregate welfare, the preferred level of protection depends on the model\u27s parameters, with an intermediate level of protection being optimal in many circumstances
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