Layers Adapter & MobSOS: Providing SMEs with Scalable Support for Transparent Integration and Analytics of Learning Services

Main impacts

The situation before Layers

Highlights

Before Layers, SMEs faced a situation of limited self-maintained IT infrastructure, coupled with uncoordinated use of public cloud services outside the control of SMEs. Digital boundaries of SMEs were largely unclear and thus hampered a comprehensive understanding of learning processes and a beneficial integration of learning services tailored to the SMEs particular needs.

Description

Before Layers, we found a situation of SMEs with basic self-maintained IT service infrastructure, accompanied by trends among young employees and apprentices to work with own mobile devices and a mix of public cloud services independent of their organizations. Different authentication and authorization mechanisms across service providers required inconvenient multiple authentication. The boundaries of learning contexts thus remained largely unclear. Sharing services and resources among SMEs in clusters was difficult for the same reasons. With the use of different cloud-based media distributed across the Web, comprehensive observation, reflection, and awareness on success or failure of an SME’s learning process as a whole was largely infeasible, as learning process data was not under the control of the SMEs themselves. Integration of custom developed tools with public cloud tools also was unsatisfactory, as it hampered the creation and use of learning tools and resources in an integrated and scalable manner tailored to the SMEs’ or clusters’ learning needs.

What Layers did

Highlights

The Layers Adapter was designed as easily configurable, extensible, and scalable entry point to all Layers services in a Layers box. Its integrated support for OpenID Connect provides a convenient and secure single-sign-on solution for accessing all Layers services with the same account. Its integrated support for MobSOS provides unified information systems success and learning analytics for all Layers services managed under the Layers Adapter.

Description

With the Layers Adapter, we approached the existing challenges with a comprehensive and highly scalable integration concept: data integration for content, metadata and analytics data management; service integration for connecting and bundling existing Layers services; tools integration to make Layers tools by different partners work together via a common infrastructure.

We designed the Layers Adapter as main end point to access all services in a Layers Box, following the Reverse Proxy pattern well-known for its scalability in modern Web service architectures. The Layers Adapter is the main component for providing and controlling access to the underlying infrastructure by Layers client apps and services. It thus defines clear, well-documented, easily configurable, extensible and scalable boundaries and thus shields users and client application developers from the complexity of the underlying infrastructure bundling all Layers services under one virtual service endpoint. Along with the Layers Adapter, we developed a single-sign-on solution for all current and future Layers apps with support for data protection and privacy using the cutting edge standard OpenID Connect (OIDC). The consortium thereby acted as early adopter of this simple, yet powerful and industry-backed identity layer protocol by creating highly re-usable elements such as login buttons for Web and mobile applications and using these for all Layers tools. With MobSOS, we finally integrated support for information systems success and learning analytics into the Layers Adapter as core part of every Layers Box. MobSOS includes technical means for usage data collection, online survey management, and visual data analytics over all apps and services managed under a Layers Adapter. All analytics data remains under the control of the Layers Box owning organizations.

The situation after Layers

Highlights

The Layers Adapter in connection with OpenID Connect guarantees clearly defined boundaries and scalable growth for learning service use within and across SMEs. With OpenID Connect support, all Layers services are prepared for integration with a large and growing ecosystem of services and tools, and thus benefit from a large potential for creating competitive advantage of SMEs using Layers technology. Reusable OpenID Connect components created in Layers receive wide attention beyond consortium outreach in the Open Source Software community.

Description

With the Layers Adapter and OpenID Connect, we not only clearly defined the boundaries of controlled digital media use for learning in an SME’s Layers Box, but also provided a mechanism for federated access between Layers Boxes of different SMEs. With its design as a reverse proxy, we created a very easily maintainable and customizable technological basis for the deployment of Layers Boxes tailored to the needs of particular SMEs or cluster organizations. Several of these boxes are deployed across partner organizations, thus spanning a first lighthouse federation network. For several years, the Layers Sandbox has served and will continue to serve as playground for developers building new applications upon Layers services. With MobSOS as built-in analytics framework, we collected research data on Layers service use and feedback, serving as the foundation for future research, e.g. studies on expert finding in SMEs and SME clusters. We thereby profited from parallel studies of the same technology in similar environments such as the ROLE Sandbox. With our early decision for the wide use of OpenID Connect, all Layers services are now prepared for a seamless orchestration with a large and growing ecosystem of Web services using the same authentication mechanisms. This seamless orchestration will give SMEs more convenient means of integrating different services and data sources, in turn providing competitive advantage. Furthermore, our development efforts with respect to OpenID Connect components, e.g. reusable login buttons for Web and mobile apps used across Layers tools, created wide attention beyond the consortiums direct outreach, mostly in the Open Source Software community.

Learner
Organisation
Development

Impact that Layers created

Bridging learning contexts

With OpenID Connect, we not only clearly defined the boundaries of controlled digital media use for learning in an SME’s Layers Box, but also provide a mechanism that allows learners to move between Layers Boxes of different SMEs.

Improved take-up of Innovation

With our early decision for OpenID Connect, all Layers services are prepared for a seamless orchestration with a large and growing ecosystem of Web services using the same authentication mechanisms. This seamless orchestration will give SMEs more convenient means of integrating different services and data sources, in turn providing competitive advantage. Furthermore, project outcomes, in particular OpenID Connect basic technology, received wide attention in the Open Source Software community.

Reflections on other effects

Improved Awareness on Learning Processes

With MobSOS and its services integrated at the level of the Layers Adapter, we created sophisticated means for information system success and learning analytics across all services hosted under the Layers adapter, thus opening new opportunities for staying aware of an SME’s or SME cluster’s learning process. All collected data remains within the premises and thus under the control of the Layers Box owning organization.

Further Reading

Deliverable D6.2: Customizable Architecture for Flexible Small-Scale Deployment [1]

Deliverable D6.3/Report 4: DevOpsUse - Scaling Continuous Innovation [2]

From Micro to Macro: Analyzing Activity in the ROLE Sandbox, LAK 2013 [3]

Tracing Self-Regulated Learning in Responsive Open Learning Environments, ICWL 2015 [4]

Derntl, M., Kravcik, M., Klamma, R., Koren, I., Nicolaescu, P., Renzel, D., Hannemann, A., Shahriari, M., Purma, J., Bachl, M., Bellamy, E., Elferink, R., Tomberg, V., Theiler, D., and Santos, P. (2014). Customizable Architecture for Flexible Small-Scale Deployment. Deliverable D6.2, Learning Layers Project.

Klamma, R., Koren, I., Nicolaescu, P., Renzel, D., Kravcik, M., Shahriari, M., Derntl, M., Peffer, G., and Elferink, R. (2015). DevOpsUse - Scaling Continuous Innovation. Deliverable D6.3/ Report 4, Learning Layers Project.

Renzel, D. and Klamma, R. (2013). From Micro to Macro: Analyzing Activity in the ROLE Sandbox. In: Suthers, D., Verbert, K., Duval, E., and Ochoa, X. (Eds.), Proceedings of the Third International Conference on Learning Analytics and Knowledge, LAK ’13, pp. 250–254. ACM, Leuven, Belgium, 2013. ISBN 978-1-4503-1785-6. doi:10.1145/2460296.2460347.

Renzel, D., Klamma, R., Kravcik, M., and Nussbaumer, A. (2015). Tracing Self-Regulated Learning in Responsive Open Learning Environments. In: Li, F.W.B., Klamma, R., Laanpere, M., Zhang, J., Fernández Manjón, B., and Lau, R.W.H. (Eds.), Advances in Web-Based Learning - ICWL 2015, Lecture Notes in Computer Science, vol. 9412, pp. 155–164. Springer, Berlin-Heidelberg, 2015. ISBN 978-3-319-25514-9.

References

  1. M. Derntl, M. Kravcik, R. Klamma, I. Koren, P. Nicolaescu, D. Renzel, A. Hannemann, M. Shahriari, J. Purma, M. Bachl, E. Bellamy, R. Elferink, V. Tomberg, D. Theiler, and P. Santos, “Customizable Architecture for Flexible Small-Scale Deployment,” Learning Layers Project, Deliverable D6.2, 2014.
  2. R. Klamma, I. Koren, P. Nicolaescu, D. Renzel, M. Kravčík, M. Shahriari, M. Derntl, G. Peffer, and R. Elferink, “DevOpsUse - Scaling Continuous Innovation,” Learning Layers Project, Deliverable D6.3/Report 4, 2015.
  3. D. Renzel and R. Klamma, “From Micro to Macro: Analyzing Activity in the ROLE Sandbox,” in Proceedings of the Third International Conference on Learning Analytics and Knowledge, 2013, pp. 250–254. DOI: 10.1145/2460296.2460347
  4. D. Renzel, R. Klamma, M. Kravcik, and A. Nussbaumer, “Tracing Self-Regulated Learning in Responsive Open Learning Environments,” in Advances in Web-Based Learning - ICWL 2015, Berlin-Heidelberg, 2015, vol. 9412, pp. 155–164. DOI: 10.1007/978-3-319-25515-6_14