Deep Learning Design for Social Innovation: Participatory Radio for Developing 21C Skills with Disenfranchised Learners

Deep Learning Design has been proposed as an approach to Technology Enhanced Learning (TEL) that foregrounds principles of learning and con-text over simply extrapolating the affordances of new technologies. An original application of this approach has been within contexts necessitating social innovation to promote the inclusion, non-formal learning and employability of disenfranchised learners across Europe – RadioActive101. This approach has actively developed, implemented and evaluated five radio hubs with at-risk young people and other disenfranchised groups to develop digital competencies and employability skills for the 21st Century.

This Learning Design and associated competencies are mapped to a progression and accreditation model linking EU key competencies to RadioActive101 activities and performances that are recognised through open electronic 'badges'. Evaluation findings showed particularly positive results, and impact and value beyond the non-formal learning of technical and employability skills, such as improvements in confidence, self-esteem and general self-efficacy of individuals and organisational learning and development. We conclude this article by asking how and whether current approaches to learning design can accommodate such essential psychosocial dimensions of learning.