Introduction

„What should an LMS look like in the age of Social Media, Cloud Computing, Machine Learning, Cyber Warfare, Life-Long Learners, Competency-Oriented Learning, and increasing diversity of students?”

The question is intentionally buzzword-loaded, yet it properly reflects the fact that university-education will be subject to radical paradigm shifts over the next decade.

This shift will have been accelerated by the Corona-crisis, which already brought about irreversible changes. Not only did the crisis bring about a new openness to and dependence on the application of online learning technologies, but also a new appreciation for the value of face-to-face instruction and the interplay between the physical and virtual realm. The demise and creation of whole industry segments highlighted the already anticipated necessity for life-long learning and retooling in adaptation to an ever more rapidly changing employment landscape. Many institutions of higher education are reconsidering their role and sources of income in this new era, as purely residential versions of education are called into question.

Postulates

The next generation of learning management system will need to adapt to this changing landscape of higher education, which leads to some postulates for its design.

The era of the Course Management System is over

When Course Management Systems (CMSs) first appeared on the landscape two decades ago, there were no Social Media, ubiquitous Internet, smart phones, cloud services, or online collaboration tools of significance. At the time, it was possible to create a monolithic web application that combined rudimentary communications, content management, assignment management, gradebook, and quizzing functionality. Most instructors were happy to upload syllabi and PDF-documents, as well as to email the whole class. With the emergence of Learning Management Systems, the learning process shifted into view, and meanwhile well-established practices like formative assessment and immediate feedback were fueled by this shift.

Today, user experiences and expectations differ vastly between what is possible inside Course Management Systems and most anywhere else in a user’s digital life. Tools that are hardwired into a single system that is supposed to do everything can hardly compete with what readily available specialized tools can offer in terms of usability, features, and polish. In addition, unlike most CMS, these tools can easily be used in any circumstances and on any device.

This may be one of the reasons that many instructors use CMSs only for the most basic of functions, at times simply to fulfill university requirements, and instead make extensive use of external tools – much to the dismay of students who have to juggle a slew of different websites, identities and logins.

On the other hand, current and future students grew up in a connected world and cultivated their own digital environments and expectations and often cannot relate to why they should abandon the familiar in favor of some cumbersome technology. They evade the provisioned learning environments and instead construct their own from building blocks outside the realm of learning technology, thereby thwarting purpose and intent of Learning Management Systems.

Teachers and learners alike embrace current technologies and want to employ them. However, they want to freely design teaching and learning processes, interactions and spaces, implement them by composition of available services and are prepared to fill gaps with their own contributions. A rigid environment, that oftentimes represents the least common denominator between competing and conflicting expectations and requirements, does not cater well to these needs.

The expectation is a wide array of functionality, however, in some way integrated in an overarching architecture that glues it together and manages identities. On can think of an “app store,” from which instructors can assemble not only the content, but also the functionality for their course from more than one provider.

Another limitation of classical CMSs is the “course container” – both users and content exist within the container of the course that is being managed. As was emphasized during the workshop, the concepts of a life-long learner and multi-institutional study pathways are incompatible with a course container – and so is the necessity to sustainably offer online educational experiences across courses and semesters.

Learners, teachers and resources exist outside any CMS container and independently of one another. They come together in courses, in which they are exposed to each other in a safe environment that facilitates interactions between them. This stands in contrast to how the corresponding entities are represented in typical Course Management Systems.

Open Educational Resources need to be reinvented

Creating new content for online courses is overwhelming, so in a culture where sharing is well- established through the publication of scientific results, the idea of Open Educational Resources (OERs) has been around almost as long as Course Management Systems have. Unfortunately, OERs never quite lived up to the hype – even when MOOCs appeared to finally push them into the limelight, it fairly quickly became clear that MOOCs are not really “open” in terms of reusable and remixable content.

There are several possible reasons for the limited penetration of OERs, some of which may be:

  • Locating content: OERs are distributed over a plethora of repositories, and their associated metadata does not allow to effectively search, as level, context, and prerequisites are not catalogued to the required level. Since OERs need to be downloaded from repositories, there is currently no way to automatically gather these metadata from usage context.
  • Evaluating content: Short of peer-review, which introduces a bottleneck for the incorporation of new content into repositories, as well as hesitancy on the part of potential content contributors, there are no efficient quality control mechanisms for OERs. Again, not being able to extract usage and learning analytics data from actual usage in learning scenarios hinders learning more about the content.
  • Incorporating content: OERs are oftentimes embedded into larger content structures, having branding and navigation elements. Their granularity thus frequently does not allow for modular incorporation into online curricula. Also, for some instructors, downloading content with all dependencies and then reuploading it into a Course Management System may be “last mile” hurdle.
  • Supporting interactive content: Interactive content frequently needs server-side functionality. While there are some interoperability standards, they oftentimes only support the least common denominator of the currently available Course Management Systems and bring along another set of complexities. This strongly limits the level of interactivity that reusable content resources can have.
 

There are also additional hurdles. On the other hand, it is hard to overstate the importance of OERs for the future of learning. The next generation of LMSs thus needs to overcome the above hurdles – particularly the need for assistance with locating appropriate content appeared in several stories.

The "fear" of data security and privacy can be paralyzing

Almost anytime that data analytics, artificial intelligence, machine learning, and data-driven decision making are mentioned, it is followed by a disclaimer that – of course – privacy and data security regulations need to be respected. This, in turn, seems insurmountable. Also, the need for “erasing data” is frequently mentioned as if that were realistically possible in redundant, multiple backed-up systems with interlinked data sources, especially if that same data would be needed again once a user reenters degree or certification programs at the same or another institution.

It seems that most online platforms are successful because they make the user consent to all kinds of data usage; while that practice might be acceptable for voluntary activities, it is unacceptable for public institutions of higher education. It also seems that at any given time, laws about data usage are years behind what is actually happening in online platforms, which could mean that a data usage that is acceptable today may not be acceptable anymore tomorrow. Any next generation LMS needs to provide a way for the users to control and own their data.

It becomes very apparent that data privacy and copyright regulations introduce a high degree of uncertainty in users, manifesting either in fear of potential consequences in cases of accidental oversights or a general “all open”-attitude, ignoring any consequences until they actually arise. Future systems need to ensure that regulations are adhered to and reduce uncertainty e.g., by transparently informing users about implications of specific actions. Diminishing this uncertainty will build trust and might lead to more openness across boundaries.

Content and functionality belong together

For content to become more reusable and remixable, it needs to turn into a package of content and functionality. Such a package is able to provide its own environment to display itself in different contexts, interact with the user, process submissions, and exchange data with all parties involved. These containerized applications may be anything from simple parsers to AI-agents and even components of what are considered Course Management Systems today (e.g., a containerized Moodle might travel alongside content that requires it).This choice also makes participating systems more easily maintainable and extensible, as app-like functionality would be published in the same way as content

Users and their data belong together

Users need to bring their own data with them, which can exist in “data pods”. Among other data these pods capture educational experiences the user had participated in. They exist in encrypted form, and the user is able to lock and unlock specific parts of these pods for other experiences.

In its most advanced form, these data could include certified credentials, like whole degrees. But also fine-grained interaction data is relevant: users can benefit from their accumulated interaction data throughout their life-long educational experiences – most notably through the use of artificial intelligence.

Artificial Intelligence is here to stay

Even though today, the use of Artificial Intelligence (AI) in education is limited and not always well-advised, the future potential in this technology of this technology is virtually undisputed.

There is an apparent conflict between users’ control over their data and the need for AI to be data-driven; an important architectural concept may be that on the one hand, users have their own “private” AI-agent for personalized decisions, but on the other hand, data is gathered from all users in depersonalized form – the private AI-agent is operating on the depersonalized data from other users.