A Philosophy of Open Digital Badges (original) (raw)

2016, Foundations of Digtial Badges and Micro-Credentials

One of the most promising educational technology tools, open digital badges, is quickly changing curricula, job acquisition and workforce credentialing. Learning data, assessments, and expert validation made accessible in social media creates a transparency that may well be suited for critical questions in education. This “philosophy” of digital badges addresses a variety of epistemological concerns including the intersection of educational enterprise and communities of learners, ethical questions of education as a human right, and data usage in badge analytics. Operating from a framework of establishing how badges are currently employed in learning—the influential contexts of individuals and communities, and data aggregation—raise questions concerning the roles of instructors, badge providers, and learning management systems. These concerns are framed around understanding how current work in digital badges can potentially transform learning; this is both an acknowledgment of how badges are beginning to change ecosystems of informal and formal learning as well as an attempt to demonstrate how an epistemological philosophy of badges can change educators’ thinking and accelerate innovation. This framework of digital badges will help respond to three distinct, yet interrelated, philosophical questions: As the roles of the educational technology entrepreneur, instructor, student, and institution change with badging, what can be known about how the educational enterprise and the communities of learners change with it? How can badging create opportunity to elevate autonomy and active engaged learning? What kind of educational shift would this need? As Internet and technological capabilities advance, and thus online education and badging becomes more readily available, what might be known about education as a human right? Do notions of ethical uses of education change with badging? Open digital badges produce useful learning data quite that developers, entrepreneurs, and institutions can analyze. How might inferred and deduced data influence development, innovation, and acceleration of transparent education?