$\mu$Ed API: Towards a Shared API for Education Microservices
Maximillan S\"olch, Alexandra Neagu, Marcus Messer, Peter Johnson, Gerd Kortemeyer, Samuel S. H. Ng, Fun Siong Lim, Stephan Krusche

TL;DR
This paper proposes $d$, a standard platform-independent API for education microservices, enabling interoperable automation like assessment and feedback across institutions to enrich learning experiences.
Contribution
It introduces an initial specification for a universal API for educational microservices, integrating existing systems from four institutions.
Findings
API successfully integrates with existing systems at four institutions.
Initial focus on feedback, assessment, and chatbots.
Enables development of a broader ecosystem of education microservices.
Abstract
Learning at scale often requires domain-specific automation such as assessment and feedback. An organization locked in to a general learning platform without these specialist automations limits its pedagogical offering. An ecosystem of interoperable, platform-agnostic microservices for domain-specific automation would solve this problem. To develop an effective ecosystem, a standard interface (API) for education microservices is required. We propose an initial specification for a standard, platform-independent API for educational microservices, Ed. The API integrates functionality from existing systems in use at four institutions, which are adopting the new API. The API is initially specified for automation of feedback, assessment, and educational chatbots, with further service types planned. The API specification provided here enables the development of an ecosystem of…
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