1 Introduction

“May you live in interesting times.”

This saying refers to a famous Chinese curse whose origin is not clearly documented. Against the backdrop of the challenges education is currently facing, we indeed live in interesting times. The digitisation of society and, thus, education, discernible in the emergence of new technologies, has dismantled our traditional view of teaching and learning. No longer can both be solely regarded as educational practices where individuals gather in a physical classroom and interact socially face-to-face, using different written learning materials. While the Covid-19 pandemic and the sudden dependence on technological solutions to maintain communication have created various pragmatic answers to mastering the challenge of “emergency remote teaching” (Charlges et al., 2020), they have disguised a more fundamental underlying question.

What appears evident is that we need to rethink how we organise teaching and learning processes. We need to admit, more than ever, that the dichotomy of an “analogue” and a “digital” world has become blurred. Education can no longer be perceived as having a rigid border between classroom and online experiences, computer-based and computer-less activities, or virtual and physical campuses (Dillenbourg, 2008). Although many misperceptions exist and might persist about “digital learning” (Kirschner & De Bruyckere, 2017), studies have demonstrated that several benefits can arise from implementing digital technologies embedded in a proper instructional design (Kerres & Otto, 2022). These benefits include temporal and spatial flexibility, facilitation of the organisation and management of study tasks, more visual forms of learning, and the provision and retrieval of teaching and learning materials (Henderson et al., 2017; Kerres & Otto, 2022). Especially the latter tells us that there is a need to reflect on a contemporary design concept for an educational learning architecture that supports achieving this and other benefits.

However, what is often less obvious in the debate about teaching and learning in the digital age is a subtle, yet far more fundamental question. The internet has perpetuated itself as the central space for teaching and learning, and its growing importance has forced educational stakeholders to reconsider patterns of conceptualising educational offers and traditional models. This sudden appearance of new (business) models is, for instance, visible in the way we understand and publish (open) research and teaching material. While, for a long time, the only way of releasing new research and teaching material was through publishers, this has been challenged by several new online journals and open textbook initiatives (see the chapter by Kimmons and Irvine).

While this case only illustrates one example of new business models, nobody can deny our reliance on the internet. However, where, in the 1990s, the question raised was, “will the Internet transform higher education?” (Baer, 1998), we meanwhile know that answer and have to ask a more fundamental question: how do we want to design the internet as the central space for education?

Based on our assessment, three main narratives can be observed in the current debate regarding this question.

  1. 1.

    The first narrative is the internet as a liberal market. This market is only lightly regulated, and actors are liberated to self-organise and run their business models with minimal restrictions and to provide education at prices that can be freely determined. Private and state actors compete here; state actors can operate in the market. The US could be regarded as one example of this narrative, whose vulnerability was visible in the debate about the prospects of Massive Open Online Courses (MOOCs) for open education followed by the accusation of open-washing (Weller, 2013) and misusing them as a business opportunity (Otto et al., 2018).

  2. 2.

    The second narrative is the internet as a state-regulated space. While in the beginning, the internet was perceived as offering unconstrained freedom without control, countries like China and Russia have demonstrated that, even in the digital age, the opposite end of the regulatory spectrum, which can be labelled “cyberpaternalism”, is possible (Krönke et al., 2018). Education here is a quasi-monopoly under the control of the state, and certain tendencies can be encouraged or prevented, as, for instance, China breaking up its booming private tutoring sector.Footnote 1

  3. 3.

    The third narrative would be the internet enabling education as a public good. This narrative is founded on the conviction that education fulfils much more than an economic function. Consequently, education must rely on free access and open educational material offered at no (or marginal) costs. The internet is configurated to empower education as a public good, and its consumption is characterised by being non-rivalrous and non-excludable. A state intervention is only legitimate when critical defects of the provision of the public good occur that need to be corrected.

While we find no prime example of this third narrative yet, we regard the European Union with its multilevel governance approach as a discursive forum where such a debate should occur. The European Union has the opportunity to establish and implement respective policies to realise the vision of education as a public good on the internet. We are presently in the middle of this negotiation process that is manifest in the various concepts of Open Educational Resources (OER) and Open Education.

With our chapter, we aim to contribute to this discourse by introducing the idea of distributed learning ecosystems (DLEs). This can be regarded as one answer to how, from an educational technology perspective, the internet needs to be configured as a space to support education as a public good. We hope our input contributes to the broader debate.

2 Contemporary Learning Architectures as Ecosystems

To best describe our idea of contemporary educational learning architectures, we use a learning “ecosystem” metaphor. Metaphors are widely resorted to not only in education to elucidate complex objects or relationships by replacing them with something more vital, more descriptive, or semantically richer. A learning “ecology” is a competing metaphor for “ecosystem” that has become popular in educational research. Based on their systematic review, Sangrá et al. (2019) explain learning ecologies as a broad semantic space for characterising innovative ways of learning and for conceptualising the relationships between the formal and the informal as a continuum across several learning contexts, mediated by digital technologies. However, they state that only a few educational applications exist currently that follow such a broader view, particularly regarding recent technology-enhanced learning approaches. Therefore, the term’s broadness might hinder a further conceptual development.

By introducing the term learning ecosystems, we primarily aim to reach beyond the spatial dimension of a traditional view on the organisation of learning, which is strongly associated with buildings, rooms, and walls in physical spaces. The ecosystem metaphor emphasises that we are dealing with an interrelated ensemble of different influencing entities that are in dynamic interplay with each other. In contrast to a spatial view, learning in digital and analogue environments is considered to be dynamically developing and interconnected; there is growth and unexpected changes, parts die off, strengthen themselves, and develop further in an evolutionary way. Therefore, these developments should not be conceptualised as linear, but must rather be understood as emergent processes. Agents’ actions not only have mutual effects but can also give rise to new formations. Knowledge no longer emerges (only) in the mediation via algorithms, programmes, or designed spaces and in the exchange between teaching and learning instances. More actors are coming into focus: The producers of knowledge resources, the editorial offices and agencies that select, evaluate, and provide them, and other intermediary actors that ultimately have a decisive influence on our knowledge environments. In this context, digital technology itself is ascribed the status of an actor. Consequently, digital technology can also be understood as an actor alongside human actors (teachers, learners) (actor-network theory (Fenwick & Edwards, 2010)). The ecosystem metaphor incorporates and broadens this perspective by focusing on actors’ diversity and interactions.

The description of digital (networked) learning technology as part of an ecosystem uses a metaphor originally related to living entities. Learning is no longer (only) considered in spaces that are available to teachers and learners, but as constant renewal of knowledge, which is (re)constructed in the network and regenerated through activities of (re)use. Computers and digital media are technical objects, and in this respect, the question arises to what extent the term ecosystem can be used meaningfully in this context or perhaps contains misleading implications. The hardware consisting of computers and networks and the associated operating software can be described as a “habitat” in which people create, provide, and use digital tools, applications, and content. The term ecosystem in this context means that there are delimited areas in the living environment in which different digital hardware and software elements interact on different levels, which are structured in themselves to function, and which develop in a relatively small exchange with other ecosystems. The users themselves, who contribute significantly to the ecosystem remaining “alive” by providing new contributions and content, also play an essential role.

An economic view of the internet initially shaped the view of digital technology as an ecosystem: The computer industry recognised that it could be attractive not only to sell a device or a software programme but also to engage people through a wide-ranging and tiered offer. Bea and Haas (2016) explain the importance of such an ecosystem for strategic management: thinking in ecosystems opens up a new view of customers and competition. A digital ecosystem comprises several companies that jointly produce values for customers, who are themselves to be understood as part of the system. Messerschmitt und Szyperski (2005) describe that software is neither evidently an intangible nor a tangible product and is, thus, subject to different laws of production and dissemination than traditional goods. Software is mainly created in the ecosystem of a technology provider. Suppliers and producers are active in this environment, which is based on the products and services of these providers. This means that the interaction of the actors plays a key role: it is about building a connected group of entrepreneurs and users, a community that creates shared value over time. The concept of digital ecosystems, thus, emphasises more clearly—in contrast to the market concept—the distinctive interconnectedness of the network of actors as it is well known in the IT world.

3 Establishing Distributed Learning Ecosystems Based on Open Repositories and Learning Resources

The remarks made above about learning ecosystems are valid also for the discussion about openness in education. The latter refers to a situation where teachers and learners are not the pure recipients of content produced by others, for instance, publishers or companies, but are empowered to be creators or distributors of learning content. Moreover, it allows teachers and learners to collaborate with others and receive feedback on their materials or help others improve theirs.

Bozkurt and Stracke (see chapter) reconstruct the concept of openness and its relation to the core values of open education. Although openness is a term often bound to its philosophical roots, the authors explore openness in education and argue that it reaches its full potential when practised from the perspective of ecosystems. In this context, openness perceives learning as an ongoing action in coordination with human development, placing people at the centre of the whole learning process, and the ecosystem view offers a roadmap to ensuring the sustainability of learning. From this point of view, the nature of learning and ecosystems is complex and chaotic, yet underlying patterns govern complexity and chaos. Bozkurt and Stracke conclude that openness provides accessibility, transparency, and democratisation, thus stabilising ecosystems. Thus, openness empowers ecosystems, and, in turn, ecosystems amplify openness.

This understanding of the potential of the nexus between openness and ecosystems for interaction and collaboration between actors and networks alike makes it essential to consider the enabling conditions for openness in learning ecosystems more closely. In our view, it is compelling that the entire spectrum of learning ecosystems can only be achieved in a distributed and also open learning infrastructure that is primarily based on open learning resources. Only in that way, the promise of interactive, collaborative, and interconnected ecosystems unfolds its full potential. Therefore, the openness of the different learning ecosystems is vital for enabling actors to find, create, share, and reuse (all available) learning resources.

Why should we think of learning ecosystems as distributed? Looking at repositories in higher education worldwide, we can state that the educational landscape is highly fragmented (Otto et al., 2021; Santos-Hermosa et al., 2017; UNESCO IITE, 2019). One reason is that most countries’ higher education systems guarantee their universities a high degree of independence and autonomy concerning self-management. As a result, numerous higher education institutions have already established (OER) infrastructures to store resources and metadata. However, in many cases, data protection and data access rights have high priority in institutions and prevent free access to materials and metadata.

Given the decentralised nature of the structure of the educational systems in most countries, the establishment and operation of central infrastructures in the form of core repositories or referatories for OER is neither a realistic nor a desirable option, neither for higher education nor across educational sectors. Moreover, since there are already recognised architectures of OER services in many educational areas, independence, subsidiarity, and user loyalty are rated higher by the providers of these than possible advantages of a more centralised structure. As a result, the already grown network is unsuitable for developing visions of single national or European repositories and referatories.

Against this backdrop, the networking and interconnectedness of existing (sub-) infrastructures/ecosystems in a distributed learning ecosystem have to be advocated. A distributed learning ecosystem enables solutions such as aggregation mechanisms for digital learning resources and repositories (e.g., meta-search engines), which address the disparately distributed and partially separated resources and communities and links them based on interoperable verification and exchange routines without restricting the diversity of field-specific offers. Initiatives to bring together international networks, national structures, and local needs are already emerging. Santos-Hermosa (see chapter) investigates some of the currently ongoing initiatives to set up national and European repositories. The initiatives aim to create global, international, or national ecosystems (such as 5Xgon, Open Discovery Space or ENCORE+), while others provide a connected national infrastructure (OERSi and Open Education Austria). They all have in common that they seek ways to influence the future of OER by applying the latest technologies to the educational ecosystems.

Hence, the design of ecosystems must be open and multifunctional and allow room for experimentation so that different approaches can develop for different requirements. Competing approaches should also be supported and tested so that, in the long term, providers and services can emerge that meet the needs of users in a particular way. Distributed learning ecosystems should, thus, encompass a variety of methods and approaches. Therefore, it is necessary to mediate between different existing platforms, projects, and institutions in the diverse ecosystems. Users can only select particularly suitable services and platforms if they are given an overview of the existing offers. Only if services can be used and tested side by side, users will be able to choose based on their own experience. To this end, it seems appropriate to define technical standards for exchanging information in the medium term, which will be regularly reviewed and adapted. In addition, the coordination of measures to create, connect, and integrate different approaches into the distributed learning ecosystems should be subject to the principles of openness and transparency.

The next crucial element for a distributed learning ecosystem is incorporating OER as one of the key components of openness and open learning (Otto & Kerres, 2021). Meanwhile, the concept of OER can look back on a history of almost 20 years and has substantially evolved since the term was initially coined by UNESCO’s, 2002 Forum on the Impact of Open Courseware for Higher Education in Developing Countries (UNESCO, 2002). Although no canonical definitions exist, the latest definition provided by UNESCO defines OER as being

“learning, teaching and research materials in any format and medium that reside in the public domain or are under copyright that have been released under an open license, that permit no-cost access, reuse, re-purpose, adaptation and redistribution by others.” (UNESCO, 2019, p. 3 f.)

The core idea embedded in OER are to facilitate access to educational materials and empower people to the 5Rs; to retain, reuse, revise, remix, and redistribute it (Wiley et al., 2014). Thus, OER is are meant to broaden access to education, reduce material costs, and improve teaching and learning quality. However, regarding their pedagogical value, it needs to be stressed that OER are primarily content and not an educational model or practice per se (Otto, 2019). Therefore, pedagogical concepts have evolved from the debate about the practical implications of OER such as Open Pedagogy and Open Educational Practices (OEP) (see other chapters in this book). While no rigid definitions for both concepts exist, OEP describe open practices that can but do not have to entail the use and creation of OER (Cronin & MacLaren, 2018).

On the other hand, the concept of OER-enabled Pedagogy, defined by Wiley and Hilton as one strand of Open Pedagogy, covers educational practices that are only possible due to the 5R activities (Wiley & Hilton, 2018). It is essential to consider OEP in the light of the repositories, or rather, learning ecosystems. Hiebl et al. (see chapter) clarify that repositories, and infrastructures in general, play a crucial part in constraining or enabling open learning and teaching practices. Their chapter shows how current functionalities of higher education repositories provide the potential for supporting OEP, which they frame within the practice theory. The authors further demonstrate how current functions shape OEP in repositories for learning and teaching resources.

Despite the necessity of OER and adequate infrastructures for the desired OEP in learning ecosystems, it must be stated that the overall adoption of OER is still low in all academic areas worldwide (Otto et al., 2021). As a result, over the past decades, OER research has primarily concentrated on awareness (or the lack thereof) and barriers to OER, which has led to various single case studies (with partly inconsistent results). Systematic reviews (Bozkurt et al., 2019) and meta-analyses (Otto, 2019) that aggregated these findings found that a lack of time, legal uncertainty, and institutional obstacles were the most predominant barriers to OER adoption. An additional difficulty is that teachers are habitually consumers rather than producers of OER and mainly cherish the opportunity to be able to adapt OER according to their individual needs and use them without facing legal problems (Otto, 2019). On the other hand, little is known about the reuse and remix, and scarce activity is observable regarding the redistribution of material. Thus, while some argue that there is presumably a “dark use” of material in education, there is, hitherto, no hard evidence corroborating this assumption (Beaven, 2018).

In their chapter, Schuwer and Baas present two process models that visualise educators’ and students’ activities to create educational resources. They connect them with the OER competency framework to support the reuse of OER. Mapping this framework reveals that educators as well as students need professionalisation to acquire the necessary competencies. Competencies in finding, evaluating, and reusing resources are crucial, and institutions should extend their support activities.

The findings mentioned above demonstrate that one significant challenge for the use and reuse of OER, which is also associated with the lack of time, is finding a sufficient number of relevant resources within a reasonable time that are relevant, up-to-date, and of high quality (Heck et al., 2020). Habitually, the first source of information for learners and teachers when looking for resources is their university’s (OER) repository. After reviewing the state of repositories in higher education, Santos-Hermosa (see chapter) demonstrates that there is an increasing number of universities offering institutional repositories for OER produced by their faculty, students, and staff. These institutional repositories allow storing and accessing material produced within the university. In this way, they increase the visibility of those engaged in OER and their activities and create awareness for OER. Repositories also facilitate compliance with Open Access mandates and policies. Santos-Hermosa notes that to increase the suitability of institutional repositories, these need to include ease of access, sharing and collaboration, and profile enhancement (see chapter for further details).

To sum up, repositories appear to be a vital component of learning ecosystems and support teachers and learners in engaging in OER. An often-discussed aspect regarding the increase of repositories is institutional measures such as offering support (e.g., technical, legal) and specific training or developing and implementing policies or institutional strategies. These measures can strengthen a person’s volition, one of the main factors influencing teachers’ intentions to adopt OER (Baas et al., 2019). However, it still does not solve the problem of finding adequate resources in time. The literature emphasises that perceived ease of use and perceived usefulness are the main predictors of teachers intentions to use OER (Hew et al., 2019). Yet, these findings partially contradict those that highlight volition as the main significant predictor.

However, to address the challenge of the ease of use and the perceived usefulness of OER and the related infrastructure, it appears worth concentrating on the overall design of distributed learning ecosystems. Accordingly, if we imagine a teacher looking for OER to equip or enrich their teaching scenarios, habitually the search will start within the institution OER repository, where OER the university staff has produced is available. When the search results in the repository are unsatisfactory, the teacher can search in other OER repositories available worldwide. As time is one of the determining factors, the teacher will only spend a limited amount of it searching each repository individually. Therefore, after a short period that differs individually, most educators decide to use a basic Google search to find appropriate OER (Cortinovis et al., 2019).

On the other hand, more and more meta-search engines such as the Mason OER Metafinder (MOM) and the OERhörnchen have become available to assist teachers in searching for OER. A problem that remains is that these meta-search engines have only limited access to the various OER repositories already existing. This shows that although more and more OER emerge, they are not available in distributed learning ecosystems “as such”. Their provision relies on open technological infrastructures and related open services that should be designed as an open informational ecosystem. Hitherto, even in the case of OER repositories, we mostly find closed informational ecosystems that preserve educational resources within specific boundaries.

4 Opening and Closing Learning Ecosystems

As mentioned, OER is not available “as such”. Its full availability beyond the respective repository and, hence, in distributed learning ecosystems relies on stakeholders’ consensus to jointly provide (meta-) information, particularly outside the distinct boundaries. However, if this does not happen, even OER repositories that are genuinely perceived as open must be considered closed ecosystems that keep educational resources within their boundaries and, therefore, miss their contribution to distributed learning ecosystems and, consequently, open learning.

Whereas obvious closure mechanisms in ecosystems can exist, such as applying a paywall that restricts access via pay per view or pay per subscription, a requirement for registration on a website can also be perceived as a mechanism of “closure” as it restricts immediate access to a resource. In the latter case, users disclose and thereby “pay” with personal information, such as an email or home address. However, it can be argued that some instructional approaches demand registration, for example, when a service provides interactive features, such as enabling the 5Rs for the OER. Concerning distributed learning ecosystems, hiding information behind barriers or hindering their exchange must be seen as critical regarding distributing the material. Search engines will be unable to locate the resources behind such (payment or registration) hurdles.

The previous explanations of OER and ecosystems have shown that educational resources are not automatically open to learners. Even “open” material faces challenges in terms of, e.g., use and availability, so it would be naïve to think that when teachers put resources “on the web” for others, there are no intermediary entities—private or public institutions—that are ultimately responsible for making these resources retrievable on the net. Although the production chain behind resources and the processes for making them available are less visible and the processing is seamless, it is still the network behind the network that decides; for example, if and how others can find resources, how these interconnect with other resources and services, how they eventually reach a course, and how changes or enhancements to an (open) resource can be traced back. For that reason, the discussion about OER specifically and open education in general occasionally ignores the relevance of the openness of repositories and related intermediary services like, for instance, meta-search engines and how they operate.

Consequently, many ecosystems cannot initially be regarded as open. On the contrary, they might entail tendencies to opening as well as closing their boundaries. However, flourishing ecosystems must be open enough to encourage teachers and learners to develop new resources and services in them. Likewise, they must be close enough to enable teachers and learners to remain in control, to track their resources and control how they can be further used. Recent studies with OER-experienced lecturers about the design of OER repositories confirm that they want to be informed about changes or improvements to their resources made by others and want to receive feedback on their published material (Otto, 2021). The results further demonstrate that users need assistance and support systems, for instance, when they upload resources in a repository or assign metadata to resources. One of the most important problems with the latter is the scarcity of quality metadata that adequately and comprehensively describe resources, and there are many incompatible standards to specify these metadata (Cortinovis et al., 2019). An additional key challenge is a well-known reluctance of most authors of resources to even provide metadata at all. Several studies have suggested metadata sets that describe OER more systematically and, thus, enrich and facilitate the metadata report to improve OER availability and OER description (Herrera-Cubides et al., 2022).

Menzel (see chapter) demonstrates how commonly agreed metadata standards contribute to distributed learning ecosystems. In his case study, he describes how operators of different OER repositories from several federate states in Germany (HOOU, Twillo, ORCA.nrw, VCRP, VHB, ZOERR) collaboratively developed a metadata profile in the area of higher education. Against the backdrop of the FAIR principles (Findable, Accessible, Interoperable, and Reusable), it is shown how meaningful metadata description can be achieved by balancing the prima facie antagonistic demands of describing resources as detailed and accurate as possible while only providing essential information to keep the threshold for authors as low as possible. In conclusion, Menzel emphasises that metadata standards are crucial to connecting repositories, thus permitting federated search, and harvesting metadata, e.g., by search engines or other interested parties.

The metadata standard problem exemplifies the general importance of the discoverability of OER, and there are many ongoing attempts to address this (Cortinovis et al., 2019; Otto et al., 2021). Predominantly, these attempts encompass establishing new OER repositories with search services or federated repositories that bundle resources from different institutions. However, the question is whether developing an additional OER search portal or engine improves or rather fragments the current landscape and the discoverability of OER further. Odds could be that teachers and learners go astray on their way to finding OER because of the difficulties of searching and locating OER, which, ultimately, retain teacher and learners within, e.g., Google or YouTube. Recent literature reviews reaffirm that searching and locating OER is still a significant problem (Abri & Dabbagh, 2018).

As already described, poor metadata allocation is one key aspect that makes it difficult to locate resources. However, the more pressing challenge regarding the overall structure and, thus, the aim to establish distributed learning ecosystems is that the different repositories must be interconnected. Networks of connected servers or services on the internet conjointly or cooperatively establish an environment for finding and providing resources to a larger public. This includes functions for delivering content and related, complex, value chain functions, like generating, editing, assembling, annotating, tagging, commenting, or linking information resources. In such ecosystems, several providers coexist; hence, their collaboration relies on common standards for interface content and metadata.

When creating and editing content, modifications and adjustments can result in new resource versions. Schroeder (see chapter) discusses these concerns of managing versions in distributed learning ecosystems by addressing the main obstacles such as metadata and persistent identifiers, tracking changes, further developments, and availability of new versions.

Open ecosystems allow any content provider to “plug into” the ecosystems by providing metadata that can be retrieved from a reference platform (referatory). On the other hand, closed ecosystems can entail a one-stop solution that combines all the described functions. They can, however, also be a network of confederated servers that jointly keep the system’s boundaries closed.

Ebner et al. (see chapter) present a compelling example of how a repository can contribute to an open ecosystem. The case study about their experiences at Graz University of Technology illustrates how a plug-in and appropriate interfaces were integrated into the learning management system (LMS). This integration into the LMS enables course components publication in the university’s OER repository.

Moreover, the authors demonstrate how adding the appropriate metadata renders resources findable in the Austrian OER referatory. Finally, besides the technical concepts and their implementation, the authors clarify the essential strategic considerations for steering this process, such as appropriate training and mechanisms for quality assurance.

Abdel-Qader et al. (see chapter) provide another example from a rather technical point of view. They disclose specifications and requirements for connecting different OER repositories using the Learning Object Metadata (LOM) standard. The authors disclose how this process works at the backend and explain the entire process of connecting repositories. They start with harvesting the metadata and end with how to store the processed data into files to be used in the frontend. The chapter comprehensively describes how to connect OER repositories using the LOM standard, while trying to be as straightforward as possible to enable non-technical staff to replicate such a process or at least stages from it.

5 Conclusion: Towards Distributed Learning Ecosystems in Education

This chapter contributed to the emerging discussion about designing contemporary open infrastructures for teaching and learning in the digital age. Therefore, we introduce the idea of learning in distributed learning ecosystems. We use the metaphor of an ecosystem as it acknowledges that teaching and learning, the communication of knowledge, and collaboration on the internet are not merely about learning spaces but about how the different learning spaces are interconnected. The spatial dimension predominantly focuses on the features and design of the space and ignores what lies between the spaces, the interconnectedness and relationality of spaces. When we speak of ecosystems, the characteristics of entire areas of the internet come to the fore. The question we bring up is how these areas should be structured to enable open teaching and learning.

First, it is essential to accept that ecosystems can include closing and opening mechanisms that must be considered crucial elements for designing distributed learning ecosystems. Only if ecosystems remain open beyond specific, often invisible boundaries, they can unfold their potential.

As described, these boundaries are normally obvious, as in the form of paywalls or a mandatory registration with an email and sometimes even a postal address. However, equally importantly, boundaries can be hidden or invisible; for instance, if ecosystems are not providing compatible technical standards or mechanisms to exchange metadata.

We then present the implications of this rather conceptual discussion using the debate on OER and the related repositories and referatories. In general, the concepts of OER and openness constitute critical components to facilitating distributed learning ecosystems. However, we first outline that OER are facing several challenges regarding their adoption in education. While these challenges are often related to individual or institutional factors that hamper or facilitate the use of OER, we aim to point out the importance of the overall learning architecture perspective. If the various existing ecosystems are operating as open learning ecosystems, meaning that they allow the exchange with other ecosystems, they can contribute to what we describe as a distributed learning ecosystem (see Fig. 1).

Fig. 1
An illustration represents the sharing of metadata between universities 1 and 2 through a connecting system. Service providers share data through federated referatory.

Distributed learning ecosystem 1

Full size image

To illustrate the practical implications and the contribution of open learning ecosystems to a distributed learning ecosystem, we refer to the other chapters in this book. The authors of the chapters show innovative and pragmatic solutions to how technological developments and repositories can add to a distributed learning ecosystem; for example, via integrating plug-ins into LMS or connecting OER repositories using the LOM standard. Still, these examples are only a fraction of the possibilities that may arise from open thinking about the design of open ecosystems.

We invite researchers and practitioners to provide further input and thus expand the range of distributed learning ecosystems in education!