Desarrollo de un currículum educativo IA basado en microcredenciales

Referencia : RDRDK2023-curriculum

Caduca : 2024-02-15 00:00:00


University College of Northern Denmark, a centre for vocational education, is looking for partners for their project on developing a set of micro-credentials on artificial intelligence for radiography students, lecturers, and graduates to be offered across Higher Education Institution in European countries – this entails developing an AI educational curriculum for radiography students.

Información adicional

It is anticipated that the implementation of artificial intelligence (AI) in radiology over the next decade significantly will influence the work of radiographers and radiological technologists (hereafter named radiographers), and with the development of AI, radiographers have an opportunity to redefine/develop their roles and lead the development of best practices for working alongside semi-automated AI systems. The foundation of the radiographer profession is person-centred and compassionate care, and radiographers are professionally accountable for patients’ physical and psychological wellbeing, immediately prior to, during and following imaging investigations or therapy procedures. Radiographers take an active role in the justification and optimisation of medical imaging and radiotherapeutic procedures and have a vital role in the radiation safety of patients, carers, and relatives in accordance with the “As Low as Reasonably Practicable (ALARP)” principle and relevant legislation. Radiographers are also responsible for themselves and colleagues, ensuring that appropriate outcome measures are used and throughput efficiency is not at the detriment of staff or patient wellbeing and quality of care. Artificial intelligence Artificial intelligence is a broad umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. It is a data-reliant paradigm that fits well with the technology driven practice of modern radiology, medical imaging, and computer vision tasks. In the future radiographer profession, AI is expected to have a major impact on clinical decisions, risk-communication with patients, dose reduction/optimisation in all modalities, interpretation of reading of imaging examinations, patient positioning and the possibility of providing fast/immediate results to patients. In addition, AI has the potential to optimize patient and professional’ workload and workflow. Furthermore, the capability of AI to read text makes the technology capable of shifting from imaging-centric configuration to a “whole patient” perspective, as AI has the potential to use all data in patients’ electronic health records. Radiographers will need to develop enhanced skills and knowledge on how AI systems are created, evaluated, and used in radiology imaging and therapy, along with quality, safety and risk management and ethical issues with the future integration of AI into radiography. There is a need for an educational curriculum to include more AI training, such as terminology, statistics, AI applications, patient-centred care, ethics, and validation techniques and bringing humanity to the machine-patient interface when using AI. With the demographic development among citizens in the European Union (EU) it is expected that we will have even greater patient workload and continuous increases in demand for imaging to support the diagnosis, treatment and monitoring of disease, we should expect all radiographers to achieve a range of modality and technology-interfacing competencies. In this changing future, it may be reasonable to expect radiography graduates to have the threshold competencies to operate and supervise image acquisition across the range of imaging modalities thereby increasing workforce flexibility. This calls for changes in education as schools and healthcare employers must provide opportunities for students, lecturers, and radiography graduates to upgrade their skill sets to ensure comparative knowledge 2 Radiography4Future around AI. Lifelong learning and micro-credentials Digital and technological advances have created a need for more flexible and inclusive education paths as the popula-tion is becoming more diverse, and the learning needs are more dynamic. The future radiography students, lecturers and radiography graduates are expected to demand lifelong learning, in the attempt to reskill, upskill, and upgrade their professional development to ensure that future demands and requirements in the profession are fulfilled. This calls for changes in the education area to fit this transformative movement toward lifelong learning and personal-ised education needs. Innovations such as micro-credentials may support lifelong learning. Micro-credentials provide formal and systematic ways to develop and assess the competency acquired in an individual’s profession and support their progress and career advancement over time. Micro-credentials are short (micro) and intense groups of tailored, competency-based courses that allow learners to earn proof of qualification (credentials) by demonstrating proficiency in the skills, knowledge, and behaviours required by the corporate, academic, educational, and professional sectors. They are not time-limited and offer flexible pro-gramming that deviates from traditional courses or classes. They may be offered at a lower cost, making it more cost-effective and sustainable for a broader target group e.g., across educational levels, settings, institutions and across countries. Micro-credentials can resolve the need for changes and lifelong learning in the radiography profession. Education around AI has the potential to be developed and provided across institutions and countries, which is an important as-pect, as there seem to be regional differences in education and profession among radiographers across the EU, lead-ing to a difference in skills acquired across member states. This hinders professional mobility and may result in hetero-geneity in the level of care offered to patients, creating a need for more standardised requirements regarding training programmes for radiography across the EU countries. The development of cross-country micro-credentials within AI for the radiography professions may fill the gap be-tween formal education and the needs of a fast-changing society and labour market within the area of AI to maintain and acquire skills that enable people to participate fully in society, and successfully manage transitions in the labour market, everywhere in the EU. Thus, to ensure the healthcare systems within the EU offer equal high-quality services in the radiographer profession. 1.3 Project description The overall aim of the project is to: To develop a set of micro-credentials on artificial intelligence for radiography students, lecturers, and graduates to be offered across Higher Education Institution in European countries. To fulfil the aim, radiography researchers and lecturers need to develop an AI educational curriculum that encounters the needed knowledge, skills, and competences for radiography students, lecturers, and graduates to understand and master the use of AI in their profession. In addition, there is a need to identify the most appropriate way of providing micro-credential-based courses across Higher Education Institutions (HEIs) in European countries. To do so, there is a need to: a) Identify the existing AI skills and competences within the radiography profession. b) Identify radiographers’ ability to integrate technology and AI in the person-centred care for patients. c) Elaborate on the needs and expectations from patients, when using AI in the radiography profession. 3 Radiography4Future d) Developing the content of a curriculum for AI in radiography suitable for micro-credentials courses. e) Developing a platform for offering the micro-credential courses in a timely and updated across the involved HEIs. f) Pilot-testing and evaluating the AI micro-credential courses at the involved HEIs to identify the most appro-priate and feasible micro-credential courses for the radiography profession in the future. Result one is the development, pilot-testing and evaluation of micro-credential courses that encounter the needed knowledge, skills, and competences for radiographers to master the use of AI in their profession. The courses will be based on AI educational curricula, existing knowledge and expected needs expressed by the profession and patients. Result two is the finalisation of a set of micro-credentials on AI for radiography students, lecturers, and graduates to be offered across the EU countries. To ensure long-term sustainability and adaption, the project will be based on a collaboration between HEIs across the EU within the radiography profession. 1.4 Partner search. This project will build on a strategic partnership between HEIs with educational programmes within radiography. University College of Northern Denmark (UCN), the applying institution has experience as both coordinator and part-ner in various ERASMUS+ projects. Currently UCN is coordinator of 5 ERASMUS+ KA2 projects and is partner in other KA2 projects. We also have project experiences from HorizonEurope, InterReg, ESF, ERDF, national and private funds. 1.5 Budget and duration The budget will be 400.000 Euro in total, and the project period will have a duration of 36 months.

Si estás interesado en recibir más información ponte en contacto con nosotros aquí

En esta página se encuentra una selección de oportunidades de colaboración tecnológica que se han extraído de la base de datos global de la Enterprise Europe Network que puede consultar en la web del consorcio EEN-GalacteaPlus , del cual FICYT es entidad coordinadora. También se incluye una selección de brokerage events y misiones, así como las convocatorias de programas europeos que se consideran más importantes para las empresas del Principado de Asturias.