From the article: "Abstract, technology-enhanced learning can be used to replicate existing teaching practices, supplement existing teaching or transform teaching and/or learning process and outcomes. Enhancing workplace learning, which is integrated into higher professional education, with technology, calls for designing such transformations. Although research is carried out into different kinds of technological solutions to enhance workplace learning, we do not know which principles should guide such designs. Therefore, we carried out an explorative, qualitative study and found two such design principles for the design of technology-enhanced workplace learning in higher professional education. In this research, we focused on the students' perspective, since they are the main users of such technology when they are learning at the workplace, as part of their study in becoming lifelong learning, competent professionals."
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From the article: "The goal of higher professional education is to enable students to develop into reflective practitioners, having both a firm theoretical knowledge base as well as appropriate, professional attitudes and skills. Learning at the workplace is crucial in professional education, because it allows students to learn to act competently in complex contexts and unpredictable situations. Reflection on learning during an internship is hard to interweave with the working process, which may easily result in students having little control over their own learning process while at work. In this study, we aim to discover in what way we can effectively use technology to enhance workplace learning, by synthesizing design propositions for Technology- Enhanced Workplace Learning (TEWL). We conducted design-based research which is cyclic in nature. Based on preliminary research, we constructed initial design propositions and developed a web-based app (software program for mobile devices) providing interventions based on these propositions. In a pilot study, students from different educational domains used this app to support their workplace learning. We evaluated the initial design propositions by carrying out both a theoretical and a practical evaluation. With the insights obtained from these evaluations, we developed a next version of the design propositions and improved the app accordingly. The research result is a set of design propositions for TEWL. For daily practice, the developed web-based app is available for re-use and further research and development."
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https://www.researchgate.net/publication/323361454_Design_Implementation_of_Technology-Enhanced_Workplace_Learning/references DOI: 10.13140/RG.2.2.26079.56489
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To cope with changing demands from society, higher education institutes are developing adaptive curricula in which a suitable integration of workplace learning is an important factor. Automated feedback can be used as part of formative assessment strategies to enhance student learning in the workplace. However due to the complex and diverse nature of workplace learning processes, it is difficult to align automated feedback to the needs of the individual student. The main research question we aim to answer in this design-based study is: ‘How can we support higher education students’ reflective learning in the workplace by providing automated feedback while learning in the workplace?’. Iterative development yielded 1) a framework for automated feedback in workplace learning, 2) design principles and guidelines and 3) an application prototype implemented according to this framework and design knowledge. In the near future, we plan to evaluate and improve these tentative products in pilot studies. https://link.springer.com/chapter/10.1007/978-3-030-25264-9_6
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Fysieke onderwijsruimtes worden niet alleen anders ingericht in het kader van de gewenste flexibiliteit in de onderwijsvormgeving, ook de beschikbare technologie wordt in die ruimtes belangrijker. Daarmee ontstaan nieuwe learning spaces in instituten voor hoger onderwijs die ook nieuwe mogelijkheden bieden voor het vormgeven van een grote variatie aan onderwijsleerpraktijken. Het verkennend onderzoek had als doel het in kaart brengen van de ontwikkelingen in Nederlandse hoger onderwijs met betrekking tot technologierijke learning spaces, en inzicht krijgen in het gebruik van deze technologierijke learning spaces in een aantal instituten die er gebruik van maken. Een van de inzichten uit het onderzoek is de indeling in vier verschillende typen op basis van het gebruik van de ruimte.
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From the article: "The educational domain is momentarily witnessing the emergence of learning analytics – a form of data analytics within educational institutes. Implementation of learning analytics tools, however, is not a trivial process. This research-in-progress focuses on the experimental implementation of a learning analytics tool in the virtual learning environment and educational processes of a case organization – a major Dutch university of applied sciences. The experiment is performed in two phases: the first phase led to insights in the dynamics associated with implementing such tool in a practical setting. The second – yet to be conducted – phase will provide insights in the use of pedagogical interventions based on learning analytics. In the first phase, several technical issues emerged, as well as the need to include more data (sources) in order to get a more complete picture of actual learning behavior. Moreover, self-selection bias is identified as a potential threat to future learning analytics endeavors when data collection and analysis requires learners to opt in."
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De implementatie van blended learning – waarbij fysiek leren wordt gecombineerd met online leren – staat bij veel onderwijsinstellingen hoog op de agenda, om activeren, intensiveren, flexibiliseren, differentiëren en/of personaliseren mogelijk te maken (Bos, 2022). Als gevolg hiervan krijgt de online leeromgeving binnen onderwijsinstellingen een steeds nadrukkelijkere rol. Om te komen tot betekenisvol leren in deze online leeromgeving (vaak in de vorm van een leermanagementsysteem, ook wel LMS genoemd), is het belangrijk dat studenten hierin actief aan de slag gaan met de aangeboden onderwijsinhoud en geïnteresseerd en gemotiveerd zijn om dit te (gaan) doen (Michael, 2006; Alhazmi & Rahman, 2012; Derboven et al., 2017; Grant-Smith et al., 2019). Echter, in de praktijk blijkt dat lang niet altijd sprake is van deze gewenste student engagement. Bijlage 1: Dit artikel geeft de resultaten weer van een onderzoek naar mogelijkheden om student engagement in het LMS te vergroten. Deze resultaten zijn tevens samengevat in twee overzichtelijke infographics. Bijlage 2: Infographic 1 omvat het gehele overzicht van de (mogelijk) te implementeren ontwerpprincipes. Bijlage 3: Infographic 2 bevat een stappenplan voor docenten om hun LMS te analyseren en te optimaliseren (laaghangend fruit).
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Game-based learning (GBL) is an interactive form of training in which instructional elements are combined with motivational elements within one GBL-environment. Under the right circumstances, GBL can contribute to both learning and motivation. It is, however, unclear which elements in the design of GBL-environments can encourage effective and efficient learning. Metacognition is cognition about cognition: knowing about one’s own knowledge and applying that knowledge in practice. While research has found that learners can benefit from metacognitive support within learning environments, it is unclear how to encourage metacognition in GBL-environments to improve learning effectively and efficiently. In this paper, we present a qualitative review of metacognition within GBL. We discuss the objectives, interventions, and effects reported in studies that address metacognition in GBL-environments. The aim of this review is to inform educational designers, researchers, and other professionals who want to address metacognition in GBL, and the review concludes with concrete implications for design and research. (PsycINFO Database Record (c) 2020 APA, all rights reserved)
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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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