This paper examines how Digital Educational Systems (DES) structure learning through the dimensions of learner agency and institutional legitimacy, suggesting how AI could algorithmically regulate these for improved educational outcomes.

In plain terms

Digital Educational Systems (DES) are platforms that help people learn new skills, using everything from simple textbooks to complex recommendation algorithms. This paper explores how these systems are structured by identifying two core design dimensions: "agency" and "legitimacy." **Agency** refers to the degree of decision-making power a learner has within the system, like choosing what to study or how fast. **Legitimacy** relates to how institutionally recognized and credible the platform and its learning outcomes are, such as granting official degrees. The authors mapped various existing DES onto a plane defined by these dimensions, revealing different design philosophies. They found that this mapping can highlight gaps in current DES designs and suggest how artificial intelligence (AI) could algorithmically adjust a learner's agency and a system's legitimacy to enhance the learning experience.