The relevance of an internationalised home curriculum for all students is generally acknowledged. Other than study abroad, the home curriculum gives programs of study full control over the way students learn international, intercultural, and interdisciplinary perspectives. However, misconceptions, lack of strategies, lack of skills of academics, and lack of connection between stakeholders present major obstacles to internationalising teaching and learning “at home”. The practical trajectory outlined in this chapter presents programs of study with the opportunity to focus on employability skills instead of on a semantic discussion on internationalisation. By linking this orientation on employability skills with the articulation of intended learning outcomes (ILOs), a pathway for developing employability skills in all students will be created. Within this pathway, international, intercultural, interdisciplinary, and future-focused dimensions serve to enhance students’ acquiring employability skills. The trajectory presented here evolved out of action research on internationalisation with academics. During the action research, taking employability skills as a starting point emerged as an enabler for the internationalisation process. It helped to overcome lengthy and semantic discussions on the meaning of internationalisation. After that, international and intercultural dimensions are included in these employability skills. These skills are then translated into ILOs. This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in Internationalization and employability in higher education on 19/25/06, available online: https://www.taylorfrancis.com/books/e/9781351254885.
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Process Mining can roughly be defined as a data-driven approach to process management. The basic idea of process mining is to automatically distill and to visualize business processes using event logs from company IT-systems (e.g. ERP, WMS, CRM etc.) to identify specific areas for improvement at an operational level. An event log can be described as a database entry that signifies a specific action in a software application at a specific time. Simple examples of these actions are customer order entries, scanning an item in a warehouse, and registration of a patient for a hospital check-up.Process mining has gained popularity in the logistics domain in recent years because of three main reasons. Firstly, the logistics IT-systems' large and exponentially growing amounts of event data are being stored and provide detailed information on the history of logistics processes. Secondly, to outperform competitors, most organizations are searching for (new) ways to improve their logistics processes such as reducing costs and lead time. Thirdly, since the 1970s, the power of computers has grown at an astonishing rate. As such, the use of advance algorithms for business purposes, which requires a certain amount of computational power, have become more accessible.Before diving into Process Mining, this course will first discuss some basic concepts, theories, and methods regarding the visualization and improvement of business processes.
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