Integrating internationalisation in learning outcomes and assessment has long been known to be a key issue in higher education. However, getting buy-in from academics and incorporating learning outcomes into a programme’s larger internationalisation goals can present a challenge. LinkedIn: https://www.linkedin.com/in/josbeelen/
MULTIFILE
Peer reviewed paper op SEFI Engineering Education congress 2009 In engineering programs an important part of the learning process takes place in practical assignments like capstone projects, internships and co-op assignments in industry. The assignments are very divers. Students have different roles, work in different environments and the learning outcomes are not uniform. So how can the individual learning outcomes or growth competencies of the assignments be determined? To cope with this question the authors developed and implemented a method to monitor and assess the individual learning outcomes of the assignments. The method can be used to match a student to his next assignment in such a way that he can build his individual learning track. The method defines three aspects of an assignment: the role of the engineer (i.e. project leader, designer, researcher), the domain(s) of the assignment (i.e. user interface, software engineering) and a general results matrix that describes results and the level required to produce them. To manage the process learning outcomes are defined as products so project management methods can be used to plan, monitor and assess learning outcomes. Key aspects of the method are: 1. A general results matrix for engineering assignments 2. Learning outcomes that are defined as results in the matrix and these results can be assessed. 3. The results have levels so the learning outcomes can grow during the programme. 4. The method can be used to match, monitor and assess students on one assignment. 5. The method can be used to match, monitor and assess students for the entire programme. 6. The tools that are developed are based on an industry standard for project management.
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Dit paper is het eindproduct van leerarrangement 1 (Zin in Leren) van de HBO masteropleiding Leren en Innoveren. Het is een literatuurstudie naar blended learning en hoe blended learning kan bijdragen aan een beter leerresultaat van de student.
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As the Dutch population is aging, the field of music-in-healthcare keeps expanding. Healthcare, institutionally and at home, is multiprofessional and demands interprofessional collaboration. Musicians are sought-after collaborators in social and healthcare fields, yet lesser-known agents of this multiprofessional group. Although live music supports social-emotional wellbeing and vitality, and nurtures compassionate care delivery, interprofessional collaboration between musicians, social work, and healthcare professionals remains marginal. This limits optimising and integrating music-making in the care. A significant part of this problem is a lack of collaborative transdisciplinary education for music, social, and healthcare students that deep-dives into the development of interprofessional skills. To meet the growing demand for musical collaborations by particularly elderly care organisations, and to innovate musical contributions to the quality of social and healthcare in Northern Netherlands, a transdisciplinary education for music, physiotherapy, and social work studies is needed. This project aims to equip multiprofessional student groups of Hanze with interprofessional skills through co-creative transdisciplinary learning aimed at innovating and improving musical collaborative approaches for working with vulnerable, often older people. The education builds upon experiential learning in Learning LABs, and collaborative project work in real-life care settings, supported by transdisciplinary community forming.The expected outcomes include a new concept of a transdisciplinary education for HBO-curricula, concrete building blocks for a transdisciplinary arts-in-health minor study, innovative student-led approaches for supporting the care and wellbeing of (older) vulnerable people, enhanced integration of musicians in interprofessional care teams, and new interprofessional structures for educational collaboration between music, social work and healthcare faculties.
The results will be consensus between departments of physiotherapy universities of allied health care about learning outcomes CommunicationThere is no consensus between Dutch Physiotherapy departments on learning outcome of bachelors
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
