Context is King, Content its Queen

Reiterated from Bill Gates in 1996 wrote the “Content is King” article it was within the context of the development of internet as a business case, and how it was important that content would have to transition from old media and formats in ways that would engage and provide an opportunity for personal involvement that goes far beyond that offered through the old media. He was of course right, and what the advertisement industry learned, was that context is even more important if you really want to profit from the individual. It is now time that we truly extend this insight from the business world and transform it into the driving force for learning experience as well by consciously working to lay the groundwork for the workings of a context sensitive environment for adaptive learning.

Contextual learning

Skjermbilde 2016-04-22 10.17.04Growing numbers of teachers today are discovering that most students’ interest and achievements improve dramatically when they are helped to make connections between new knowledge and experiences they have had, or with other knowledge they have already mastered. This approach to learning recognises that learning is a complex and multifaceted process that goes far beyond drill-oriented, stimulus-and-response methodologies. The idea, is that learning occurs only when students process new information or knowledge in such a way that it makes sense to them in their own frames of reference. The mind naturally seeks meaning in context by searching for relationships that make sense and appear useful.

Contextual learning, a theory based on the constructivist theory of learning, which focuses on how humans make meaning in relation to the interaction between their experiences and their ideas, is thought to have the following characteristics:

  • emphasising problem solving
  • recognising that learning needs to occur within multiple contexts
  • assisting students in learning how to monitor their learning and thereby become self­-regulated learners
  • anchoring teaching in the diverse life context of students
  • encouraging students to learn from each other
  • employing authentic assessment

These characteristics all hint to the need to base education on a more bottom up, individual and adaptive model, where both learning experiences, the role of the teacher and the construction of curricula and learning material lays the ground work for adaptive learning experiences which can relieve the pain points for earners which is often apparent in more traditional top-down approaches.

This post examines the roles of content within multiple contexts when creating learning experiences, as well as looking at possible representations and implementations for both content and context in digital learning.

What are the roles of context and content in learning ?

Skjermbilde 2016-04-22 10.17.18Context” is the setting in which a phrase or word is used (from Latin contextilis “woven together”.

Content” is the words or ideas that make up a piece (from Latin contensum “held together”, «contained»),

These definitions illustrate well our idea that content is to be woven and contained by the power of a context as the defining element to determine the relevant representation of the content at any time.

Furter, in the context of Learning eXperience, we add the learner as weaved together with both context and content when creating an adapted Learning eXperience. Context should then not be seen as stable, but rather dynamically changing in accordance with the learners’ interactions with both context and learning material. Interactions are part of the context, and therefore the context can only be predicted to a certain extent, making the boundaries between context and content fuzzy, since content needs to be as dynamic as context. One generates the other and one may not exist without the other when considering the adaptive needs of the learner. This interrelationship makes content and context bleed into each other, but is still based on the basic dichotomy between content and context as self-reliant stand alone entities in themselves , and as such, we should be able to express a set of intrinsic attributes that each have in accordance to the roles played in a learning experience. This in order to determine how we can design solutions that can create true adaptive Learning eXperiences.

What is a learning context?

The definition of what a context is, as anything else, dependent on what context it is discussed in, so to define the premises that could lead to a definition of what our view of what a Learning Context is,  we should start by breaking it down into constituents:

“Learning” as defined by :

«Learning is the act of acquiring new, or modifying and reinforcing, existing knowledge, behaviors, skills, values, or preferences and may involve synthesizing different types of information. The ability to learn is possessed by humans, animals, plants and some machines.»

This definition of learning comprises most of the properties we see as being part of the learning process. An adaptation of Ambrose & Al.(2010) further completes our view of what learning is and should be:

  • “Learning is a process, not a product.”
  • “Learning is a change in knowledge, beliefs, behaviors or attitudes.”
  • “Learning is not something done to students, but something that students themselves do.”

Context as defined by

When trying the same lookup for «context», the definition does not lend itself as readily, as it is of course contextually ambiguous . If we follow the link to Wiktionary’s definition: we find a generic definition which serves well as a basis to build on:

«The surroundings, circumstances, environment, background or settings that determine, specify, or clarify the meaning of an event or other occurrence»

combined with the definition given In de Figueiredo 2005 :

«the set of circumstances that are relevant when someone needs to learn something»

then, if we specify that the set of circumstances should be relevant to the learner’s specific needs in order to learn optimally, the following definition is closer to the scope and context of this article:

«A learning context, is the set of circumstances that determine, specify, or clarify the meaning of an event, statement, or idea, in terms of which it can be fully understood, and in which it meets a learner’s specific needs in order to learn optimally»

Two main types of learning context

In theories and philosophies of learning, the definition of what a learning context is, seem to fall into two main camps:

de Figueiredo 2005 states that one is the view that a learning context is external to the learner and the activities in which the learner is engaged. It is, thus, seen as the environment where the activities take place. Context is then delimited, in the sense that we feel capable of recognizing where it begins and where it ends. It is also seen as stable and driven by immutable laws, so that we can predict its evolution over time and space, even if it changes. Thus, when developing content for a given course, we take context in account beforehand, in the elaboration of our materials, and then forget about it, trusting that its behavior will always be as expected.

In contrast, within the context of learning experience and the constructivist paradigm, context cannot be located and delimited. Context is only perceived through its interactions with the learner, the interactions organising the context as much as they organise the learner’s experience. To a large extent, context is the interaction. Taking this into account, we should then be able to refine our definition of what a learning context might be:

«A learning context, is the set of dynamically perceived circumstances compiled through the learner’s interaction with learning material, that determine, specify, or clarify the meaning of an event, statement, or idea, in terms of which it can be fully understood and in which it meets a learner’s specific needs in order to learn optimally»


Source: then, can be considered to be content in our evermore complex and interconnected world? First of all, we need to set the premise within this discussion, that we are talking of digital content, specifically digital learning content.  In the context of our previous discussion, content is increasingly perceived as needing to be adapted in order to feel relevant to the individual. Mitchell Kapor likened getting content from the internet to taking a drink from a fire hydrant, indicating that the problem of information overload and info glut which was a primary concern in the early stages of the internet, hasn’t really improved. The shift towards a content-centered, connected, and slowly, but increasingly, more intelligent internet has laid the ground for the emergence of tools needed to overcome the content tsunami, but we still need to apply them systematically, especially within the field of education in order to reach our goal of creating effective Learning Experiences. The question is; what then, are the measures needed to achieve what we could call «digital wisdom». A quote from Daniel J. Boorstin pinpoints our challenge:

«Technology is so much fun but we can drown in our technology. The fog of information can drive out knowledge.»

The technology applied has to lead to a convergence for the individual instead of becoming part of the divergence translating further into the increasing amount of generalised and fragmented content, including learning content produced for consumption on the internet.

According to a presentation made by Steve Wheeler on digital pedagogy, the learners’ experience entails, among other things, to answer these questions:

  • How do I find stuff?
  • How do I know it’s accurate?
  • How do I share content?
  • How do I filter content?
  • How do I keep up with all the news?
  • How do I organise content?
  • How do I categorise content?

These are all pertinent questions about content in an objective or general context, but in order to find content that is individually relevant, the following question has to be answered.

«How do I find learning content adapted to my needs

The amount of commercially adapted content we are seeing today in commercial services such as Google and Netflix, are examples of the need for adaptation being  increasingly met with the growth of more sophisticated functionality implemented in the web as a whole. Based on big data analysis and recommendation algorithms, it is in many cases sufficient when providing product recommendations for commercials and the like to the individual. An optimal learning experience though, demands a higher degree of accuracy to be effective enough. Learning software and frameworks provide a more constrained environment within which it is easier to implement and apply the mechanisms needed to answer the above questions, and if we do, it might in the long run, lay the ground for-, and providing the data needed to provide a higher degree of accuracy to the internet as a whole

A tentative definition of learning content, then could be:

«any digital artefact intended for learning, capable of carrying meaningful information to the end-user»

This definition works in a more objective context, but as we’ve already established, content needs to be adapted to the user’s needs, and so the definition needs to convey this:

«any digital artefact intended for learning, capable of carrying adapted, relevant and meaningful information to the end-user»

Repurposable modular content

Creating adapted content suggests that one to a certain extent, needs to operate with content elements that are repurposable in different context, and as such, as modular as possible. This in order that they might be mixable and re-mixable in concert with other elements, and still form a coherent whole. This is somewhat a challenge to say the least, especially in a traditional educational context, since creating modular content would be quite dependent on context during production, and would become an impossible task when wanting to manually create content for an infinite multitude of possible contexts. Digitally, we think there is a possibility to create software which has the ability to understand and define what would constitute for instance the boundaries of meaning of a given piece of content, how it interfaces with other content, as well as the needed granularity of a given content module.

Modular content would have to satisfy at least the following points:

  • It has to be repurposable
    • making it possible to create multiple versions of the same content for different contexts
  • It has to have a clear, maybe standardised structure
    • smaller chunks of content that represent clear topics as building blocks
  • It has to be presentation-independent
    • raw content without formatting
  • It needs meaningful metadata
    • describing the content for easy querying

The challenge then, is the need to make content reusable and repurposable on the fly based on dynamically assembled attributes from the learner’s context(s). As we have established, the context should always be in the driver’s seat, providing the clues to the whats, hows and whens of the learning experience. And as important, the context should also, to a significant degree, inform the composition of the content itself. Letting context completely determine the composition of content may never be completely possible to achieve, but we believe one can at least reach a close approximation of it. What is needed in any case, is to define what would be the smallest self-sufficient modular content element.

Designing self-sufficient modular content : a concept centered approach

As a company, we have since the early beginnings believed in, and championed topic centered learning in the context of the constructivist learning paradigm. We believe in a topic centered, networked approach to information architecture in aiding learning for the individual, which in many cases aligns with what we believe to be part of how the human brain understands and structures information. A topic centered approach to content aligns with the thoughts of modularity and repurposing, and we’ve been researching what it means for content to be atomic and repurposable.

We find the approach of The Darwin Information Typing Architecture (DITA) to be very interesting in that sense. It is an OASIS standard targeted at structuring content for reuse, based on the assumption that the smallest self-sufficient content element would have to be based on a topic centered approach. A key feature of DITA is that information is organised and stored as modular chunks of content. The chunks, or topics as they are known, can be reused as building blocks of content. Topics can also be “typed”. That is, you can create different types of topics with a predefined structure that is appropriate only to that topic type. All topics in DITA are built on a single model of a generic topic. This generic topic type defines the elements that are common to topics of all types, however, DITA recognises that different topic types need different substructures and allows for variances which makes it interesting in the light of wanting to deal with multiple contexts. The DITA standard content model breaks information down to the element level, e.g., section, paragraph, sentence etc. and assigns topics to these elements. In fact, this passage from the DITA 1.2 spec describes an approach to our exact conundrum:

«Classically, a DITA topic is a titled unit of information that can be understood in isolation and used in multiple contexts. It should be short enough to address a single subject or answer a single question but long enough to make sense on its own and be authored as a self-contained unit. However, as content in many cases won’t behave in a regular manner, DITA topics can also be less self-contained units of information, such as topics that contain only titles and short descriptions and serve primarily to organize subtopics or links or topics that are designed to be nested for the purposes of information management, authoring convenience, or interchange.»

This approach is certainly a viable starting point for modelling modular content, as one can easily imagine traditional document elements like titles, sentences, tables, lists etc. as being instances of a smallest modular element, being capable of both standing alone, as well as being dynamically repurposed and orchestrated in different contexts. If one then assigned metadata to these elements, say from a given ontology representing some knowledge domain, it would be possible to make computational inferences relying on the collected contextual information for a given Learning eXperience, and then to dynamically create adapted content for it. As discussed above, orchestrating perfect content by query and assembly is quite a challenge, since the initial production of content is inherently context aware, but this approach might be able to take us a long way in creating content that is meaningful. In addition, we can imagine the possibility of applying measures such as Natural Language Processing (NLP) algorithms as well as other algorithms from the world of machine learning, to the resulting automatically assembled content in order to improve the text to achieve an even greater degree of coherence.

If we can achieve this, a more complete definition of adapted content might be:

«any digital learning artefact, capable of carrying adapted meaningful information to the end-user, simultaneously capable of standing alone as well as functioning in concert with other artefacts within multiple contexts»

Context + Semantics to produce Adapted Content

Within our definition of learning context, we have to consider the hypothetical possibility that there are as many different contexts for a given piece of content as there are individuals. In real life, realities and individual contexts  group into fewer facets, given the somewhat objective nature of our common reality. The fuzzy distinction between context and content, driven by the individual’s prerequisites, creates the dynamic that should underlie the composition of adapted content and context in order to produce effective learning experiences.

In Gilliot, Garlatti 2009 it is stated that technology ­enhanced learning systems must have the capability to reuse learning resources and web services from large repositories, to take into account the context, and to allow dynamic adaptation to different learners. It further states that reuse of learning resources requires interoperability at semantic level and suggests that knowledge models and pedagogical theories can be fully represented by means of a semantic web approach.

In Guescini & al. 2006, the need for a poly-faceted information architecture is discussed as a way of modelling the multifaceted nature of reality and the artefacts contained within them in order to combat information overload. It argues that information should be consciously designed in terms of horizontal and vertical levels, where each dimension provides its own multifaceted approach to the design, forming a coherent whole together.

The Horizontal level should be determined in practice by attributes like the choice of subject, terms of the language, epistemological assumptions, methods for establishing facts, representation techniques etc. While the vertical level would take into account the different levels of granularity as discussed above regarding atomic and modular content, and as such would take the form as modular elements with varying degrees of detail. The result of this information architecture forms a detailed coordinate system which can serve as a basis for the assembly of content with desired granularity, relevant within the desired perspective context for an adapted Learning eXperience.

Guescini & al. also discusses the technological aspects of how one can implement a polyscopic or multi faceted information architecture by the  use of Topic Maps. This aligns somewhat with the topic centered organisation of the DITA information architecture, which makes the DITA a possible contender for the representation of both the horizontal and the vertical facets as discussed above. In addition, DITA provides a full-fledged model for document structure representation, all serialised in XML, making it well suited for computational processing when needing to automatically assemble adapted content.

The ‘Topic Map’ elements in the DITA standard seem to be modelled loosely on the Topic Map standard, suggesting that it might pair well with Topic Maps when wanting to add semantic technology as the driving force behind a learning experience application. The DITA standard is by no means closely coupled to the Topic Map standard, and one could easily choose RDF when implementing a semantic backbone. What is important, is that it operates with topics, topic types, and the notion of perspective, which is most easily modelled with Topic Maps, but can also be done with RDF by jumping some extra hoops. Even more important; DITA operates with the notion of ‘relational tables’, making it possible to express interconceptual relations, in effect creating ontologies, making it very suitable in tandem with semantic technologies.

If one considers these technologies in terms of the context / content dynamic, they do not clearly place themselves within one or the other, but the emphasis on content structures in DITA suggests that it would be more instrumental in representing content, while semantic technologies could be more instrumental in modeling contexts, as well as providing the tools needed to infuse logic and intelligence, resulting in adapted learning experiences.


We have examined the roles of learning content and learning context and found that the boundaries between them are fuzzy, and that learning content needs to be as dynamically defined as learning contexts. In the context of Learning eXperience, the one does not provide the learner an adapted experience without the other. We have expressed tentative definitions for both, trying to express as accurately as possible their nature and function as part of an adaptive learning experience. We have looked at possible technological representations for both, providing a starting point for further research within the more limited scope of learning environments, with the goal of providing a possible technological ground for a more adaptive learning experience outside these environments as well, as the internet as a whole is still in dire need of more structured ways of adapting content and context for end users.


Ambrose, S.A., Bridges, M.W., DiPietro, M., Lovett, M.C., & Norman, M.K. (2010). How learning works: Seven research-based principles for smart teaching. San Francisco: Jossey-Bass

An adaptive and Context-Aware Architecture for Future Pervasive Learning Environments Jean-Marie Gilliot, Serge Garlatti {jm.gilliot, serge.garlatti} 29/09/2009

Guescini, Karabeg, Nordeng (2006), ‘A Case for Polyscopic Structuring of Information, Charting the Topic Maps Research and Applications Landscape’, Volume 3873 of the series Lecture Notes in Computer Science pp 125-138,

de Figueiredo, A. D. (2005), ‘Learning Contexts. A Blueprint for Research’, Interactive Educational Multimedia 11 , 127-139 .


CC BY-SA 4.0 Context is King, Content its Queen by Rolf Guescini @ Cerpus AS is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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