In Nederland wordt jaarlijks voor drie miljard euro aan bedrijfsopleidingen aangeboden. De meeste van deze opleidingen pretenderen de deelnemer werkelijk iets blijvends te leren. Transfer, beklijving van opleidingsresultaten, is hierin een cruciaal begrip. Onderzoek wijst uit dat de mate van transfer laag is: korte tijd na de opleiding ligt dit nog op zestig procent, echter de mate van transfer neemt met de tijd sterk af, na langere tijd blijkt deze waarde op tien procent te liggen. Schrikbarend laag! Hier is dus veel winst te behalen. In dit artikel bespreken we welke factoren een rol spelen bij het optimaliseren van de transfer. Tevens beschrijven we een pilotstudie naar transfer bij trainingen op het gebied van interpersoonlijke vaardigheden.
An important goal of educational designers is to achieve long-term transfer of learning that is the learner's application of newly acquired competencies. Extensive research during more than a century shows that especially in formal educational settings this fundamental aspect of education often occurs poorly or not at all, leading to what is called a Transfer Problem. To address this transfer problem, the present study examines intentions to transfer learning to multiple contexts; this focus on multiple transfer contexts extends previous research focusing on a single transfer context, typically the workplace. The present study aimed to estimate the influence of five organizational variables (peer support, supervisor support, opportunity to use, openness to change, and feedback) on pre-training intention to transfer prospective learning in two different transfer contexts: study and work. Participants were 303 students at an open university starting a digital course in information literacy. The model was tested using structural equation modelling. The results indicated that before starting the course supervisor support and feedback were considered the strongest predictors of intention to transfer new learning in both the study and the work contexts. This research is amongst the first in the training literature to address multicontextuality and examines intentions to transfer generic competences to the two transfer contexts study and work within one single study.
MULTIFILE
The past decades have shown an accelerated development of technology-enhanced or digital education. Although an important and recognized precondition for study success, still little attention has been paid to examining how an affective learning climate can be fostered in online training programs. Besides gaining insight into the dynamics of affective learning itself it is of vital importance to know what predicts trainees’ intention to transfer new knowledge and skills to other contexts. The present study investigated the influence of five affective learner characteristics from the transfer literature (learner readiness, motivation to learn, expected positive outcomes, expected negative outcomes, personal capacity) on trainees’ pre-training transfer intention. Participants were 366 adult students enrolled in an online course in information literacy in a distance learning environment. As information literacy is a generic competence, applicable in various contexts, we developed a novel multicontextual transfer perspective and investigated within one single study the influence of the abovementioned variables on pre-training transfer intention for both the students’ Study and Work contexts. The hypothesized model has been tested using structural equation modeling. The results showed that motivation to learn, expected positive personal outcomes, and learner readiness were the strongest predictors. Results also indicated the benefits of gaining pre-training insight into the specific characteristics of multiple transfer contexts, especially when education in generic competences is involved. Instructional designers might enhance study success by taking affective transfer elements and multicontextuality into account when designing digital education.
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Teachers have a crucial role in bringing about the extensive social changes that are needed in the building of a sustainable future. In the EduSTA project, we focus on sustainability competences of teachers. We strengthen the European dimension of teacher education via Digital Open Badges as means of performing, acknowledging, documenting, and transferring the competencies as micro-credentials. EduSTA starts by mapping the contextual possibilities and restrictions for transformative learning on sustainability and by operationalising skills. The development of competence-based learning modules and open digital badge-driven pathways will proceed hand in hand and will be realised as learning modules in the partnering Higher Education Institutes and badge applications open for all teachers in Europe.Societal Issue: Teachers’ capabilities to act as active facilitators of change in the ecological transition and to educate citizens and workforce to meet the future challenges is key to a profound transformation in the green transition.Teachers’ sustainability competences have been researched widely, but a gap remains between research and the teachers’ practise. There is a need to operationalise sustainability competences: to describe direct links with everyday tasks, such as curriculum development, pedagogical design, and assessment. This need calls for an urgent operationalisation of educators’ sustainability competences – to support the goals with sustainability actions and to transfer this understanding to their students.Benefit to society: EduSTA builds a community, “Academy of Educators for Sustainable Future”, and creates open digital badge-driven learning pathways for teachers’ sustainability competences supported by multimodal learning modules. The aim is to achieve close cooperation with training schools to actively engage in-service teachers.Our consortium is a catalyst for leading and empowering profound change in the present and for the future to educate teachers ready to meet the challenges and act as active change agents for sustainable future. Emphasizing teachers’ essential role as a part of the green transition also adds to the attractiveness of teachers’ work.
The pressure on the European health care system is increasing considerably: more elderly people and patients with chronic diseases in need of (rehabilitation) care, a diminishing work force and health care costs continuing to rise. Several measures to counteract this are proposed, such as reduction of the length of stay in hospitals or rehabilitation centres by improving interprofessional and person-centred collaboration between health and social care professionals. Although there is a lot of attention for interprofessional education and collaborative practice (IPECP), the consortium senses a gap between competence levels of future professionals and the levels needed in rehabilitation practice. Therefore, the transfer from tertiary education to practice concerning IPECP in rehabilitation is the central theme of the project. Regional bonds between higher education institutions and rehabilitation centres will be strengthened in order to align IPECP. On the one hand we deliver a set of basic and advanced modules on functioning according to the WHO’s International Classification of Functioning, Disability and Health and a set of (assessment) tools on interprofessional skills training. Also, applications of this theory in promising approaches, both in education and in rehabilitation practice, are regionally being piloted and adapted for use in other regions. Field visits by professionals from practice to exchange experiences is included in this work package. We aim to deliver a range of learning materials, from modules on theory to guidelines on how to set up and run a student-run interprofessional learning ward in a rehabilitation centre. All tested outputs will be published on the INPRO-website and made available to be implemented in the core curricula in tertiary education and for lifelong learning in health care practice. This will ultimately contribute to improve functioning and health outcomes and quality of life of patients in rehabilitation centres and beyond.
Multiple sclerosis (MS) is a severe inflammatory condition of the central nervous system (CNS) affecting about 2.5 million people globally. It is more common in females, usually diagnosed in their 30s and 40s, and can shorten life expectancy by 5 to 10 years. While MS is rarely fatal; its effects on a person's life can be profound, which signifies comprehensive management and support. Most studies regarding MS focus on how lymphocytes and other immune cells are involved in the disease. However, little attention has been given to red blood cells (erythrocytes), which might also be important in developing MS. Artificial intelligence (AI) has shown significant potential in medical imaging for analyzing blood cells, enabling accurate and efficient diagnosis of various conditions through automated image analysis. The project aims to implement an AI pipeline based on Deep Learning (DL) algorithms (e.g., Transfer Learning approach) to classify MS and Healthy Blood cells.
