Despite the promises of learning analytics and the existence of several learning analytics implementation frameworks, the large-scale adoption of learning analytics within higher educational institutions remains low. Extant frameworks either focus on a specific element of learning analytics implementation, for example, policy or privacy, or lack operationalization of the organizational capabilities necessary for successful deployment. Therefore, this literature review addresses the research question “What capabilities for the successful adoption of learning analytics can be identified in existing literature on big data analytics, business analytics, and learning analytics?” Our research is grounded in resource-based view theory and we extend the scope beyond the field of learning analytics and include capability frameworks for the more mature research fields of big data analytics and business analytics. This paper’s contribution is twofold: 1) it provides a literature review on known capabilities for big data analytics, business analytics, and learning analytics and 2) it introduces a capability model to support the implementation and uptake of learning analytics. During our study, we identified and analyzed 15 key studies. By synthesizing the results, we found 34 organizational capabilities important to the adoption of analytical activities within an institution and provide 461 ways to operationalize these capabilities. Five categories of capabilities can be distinguished – Data, Management, People, Technology, and Privacy & Ethics. Capabilities presently absent from existing learning analytics frameworks concern sourcing and integration, market, knowledge, training, automation, and connectivity. Based on the results of the review, we present the Learning Analytics Capability Model: a model that provides senior management and policymakers with concrete operationalizations to build the necessary capabilities for successful learning analytics adoption.
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After 15 years of digital openness in education with as its most visible elements OER and MOOCs, the open community is challenged to widen adoption of openness in teaching practices to (as Rogers puts it) the early and late majority of teachers. For them to adopt, the gain should be clear and directly visible to have them adopt openness. Arguments like it saves students money, it is efficient because you will not reinvent the wheel or publishing quality OER and MOOCs adds to the reputation of our institution are, how true they might be, not appealing to teachers who are in most cases crowded with their day-to-day teaching tasks. One approach to overcome this hurdle is to connect to the core of a teacher’s job: pedagogy. We assume each teacher has a vision on when his/her course can be called a success and what this means for activities s/he and the students have to perform. Many teachers experience challenges in realizing their optimal lectures. For some of these challenges forms of open online education can be of use, especially in enhancing pedagogical opportunities. The latter is called Open pedagogy. To create awareness of the world of open and the opportunities it may have, we have developed a workshop for teachers and teacher support. This workshop has been delivered several times in Fall 2016. In the presentation we elaborate on the content of this workshop, the experiences we had, the feedback of the participants and the impact it had after taking the workshop. The materials used in this workshop and a script is published under a CC BY license and is available in both Dutch and English. This creates the opportunity to conduct the workshop locally for everyone interested, stimulating/increasing chances for widespread adoption of open education in (formal) education.
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In de landelijk projecten Boegbeeldproject hbo Verpleegkunde (fase 1) en haar opvolger SAMEN hbo Verpleegkunde (fase 2) hebben 15 hbo-instellingen met een Bachelor Verpleegkunde programma samengewerkt om in een vakcommunity digitale leermaterialen te maken en open te delen. Beide projecten beslaan de periode januari 2017 – oktober 2020. Na afloop van deze projecten is een onderzoek uitgevoerd om antwoorden te krijgen op de volgende vragen: 1. Hoe zijn de projecten in fase 1 en 2 georganiseerd en welke activiteiten zijn er uitgevoerd? 2. Welke activiteiten hebben een positieve bijdrage geleverd aan het projectresultaat, welke niet en waarom? 3. Hoe is het proces van adoptie van delen en hergebruiken van open leermaterialen door docenten verlopen? 4. Welke lessen kunnen worden geleerd uit dit project? 5. Welke adviezen kunnen worden gegeven aan Samen Delen Verpleegkunde en aan andere partijen die een soortgelijk project willen starten?
The scientific publishing industry is rapidly transitioning towards information analytics. This shift is disproportionately benefiting large companies. These can afford to deploy digital technologies like knowledge graphs that can index their contents and create advanced search engines. Small and medium publishing enterprises, instead, often lack the resources to fully embrace such digital transformations. This divide is acutely felt in the arts, humanities and social sciences. Scholars from these disciplines are largely unable to benefit from modern scientific search engines, because their publishing ecosystem is made of many specialized businesses which cannot, individually, develop comparable services. We propose to start bridging this gap by democratizing access to knowledge graphs – the technology underpinning modern scientific search engines – for small and medium publishers in the arts, humanities and social sciences. Their contents, largely made of books, already contain rich, structured information – such as references and indexes – which can be automatically mined and interlinked. We plan to develop a framework for extracting structured information and create knowledge graphs from it. We will as much as possible consolidate existing proven technologies into a single codebase, instead of reinventing the wheel. Our consortium is a collaboration of researchers in scientific information mining, Odoma, an AI consulting company, and the publisher Brill, sharing its data and expertise. Brill will be able to immediately put to use the project results to improve its internal processes and services. Furthermore, our results will be published in open source with a commercial-friendly license, in order to foster the adoption and future development of the framework by other publishers. Ultimately, our proposal is an example of industry innovation where, instead of scaling-up, we scale wide by creating a common resource which many small players can then use and expand upon.
