How lecturers in higher education handle, or curate, educational resources during course design, has become increasingly important with the growing amount of digitally available educational materials. Despite the recognition of curation in educational literature and the development of two conceptual models, there is a lack of empirical knowledge of lecturers' actual curational practices. Through 23 semi-structured interviews at a Dutch University of Applied Sciences, this study identified six categories of distinguishable but interconnected activities that constitute lecturers' curational behaviour, taking place within the context of course design. These activities are: searching for resources, assessing and selecting resources, creating and editing resources, structuring resources, sharing resources, and soliciting feedback. The findings suggest that lecturers underemphasize the construction of a narrative that relates the resources and are providing students with little didactical support when sharing the resources. This paper offers an empirical a foundation for educational curation and suggests directions for future research to inform lecturers’ course design practices and enhance support for lecturers in this critical task.
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After decades in which a great deal of effort was spent on the creation of resources, there are currently several initiatives worldwide that aim to create an interoperable, sustainable research infrastructure. An integral part of such an infrastructure constitutes the resources (data and tools) which researchers in the various disciplines employ. Whether the infrastructure will be successful in supporting the needs of the research communities it intends to cater for depends on a number of factors. One factor is that resources that are or could be relevant to the wider research community are made visible through this infrastructure and, to the greatest extent possible, accessible and usable. In practice, the durable availability of resources is often not properly regulated within research projects. CLARIN-NL is directed at creating an interoperable language resources infrastructure for the humanities in the Netherlands. The Data Curation Service was established in order to salvage language resources in this field that are threatened to be lost. In the CLARIN context, a great deal of attention is given to standards, formats and intellectual property rights. Consequently, the Data Curation Service (DCS) has a role as mediator in bringing researchers in the field of humanities and existing data centres closer together. This article consists of two parts: the first part provides the background to the work of the DCS while the second part illustrates the work of the DCS by describing the actual curation of a collection of language learner data.
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Social networks and news outlets entrust content curation to specialised algorithms from the broad family of recommender systems. Companies attempt to increase engagement by connecting users with ideas they are more likely to agree with. Eli Pariser, the author of the term filter bubble, suggested that it might come as a price of narrowing users' outlook. Although empirical studies on algorithmic recommendation showed no reduction in diversity, these algorithms are still a source of concern due to the increased societal polarisation of opinions. Diversity has been widely discussed in the literature, but little attention has been paid to the dynamics of user opinions when influenced by algorithmic curation and social network interaction.This paper describes our empirical research using an Agent-based modelling (ABM) approach to simulate users' emergent behaviour and track their opinions when getting news from news outlets and social networks. We address under which circumstances algorithmic filtering and social network dynamics affect users' innate opinions and which interventions can mitigate the effect.The simulation confirmed that an environment curated by a recommender system did not reduce diversity. The same outcome was observed in a simple social network with items shared among users. However, opinions were less susceptible to change: The difference between users' current and innate opinions was lower than in an environment with users randomly selecting items. Finally, we propose a modification to the collaborative filtering algorithm by selecting items in the boundary of users' latitude of acceptance, increasing the chances to challenge users' opinions.
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