OERs in Practice: Re-use With Modification

Over the years, I’ve never really got my head round what other people mean by OERs (Opern Educational Resources) in terms of how they might be used.

From my own perspective, wholesale reuse (“macro reuse”) of a course isn’t relevant to me. When tasked with writing an OU unit, if I just point to a CC licensed course somewhere else and say “use that”, I suspect it won’t go down well.

I may want to quote a chunk a material, but I can do that with books anyway. Or I may want to reuse an activity, and then depending on how much rework or modification is applied, I may reference the original or not.

Software reuse is an another possibility, linking out to or embedding a third party application, but that tends to fall under the banner of openly licensed software reuse as much as OER reuse. Sometimes the embed may be branded; sometimes it may be possible to remove the branding (depending on how the asset is created, and the license terms), sometimes the resource might be a purely white label resource that can be rebranded.

Videos and audio clips are another class of resource that I have reused, partly because they are harder to produce. Video clips tend to come in various forms: on the one hand, things like lectures retain an association with the originator (a lecture given by Professor X of university Y is very obviously associated with Professor X and university Y); on the other hand, an animations, like software embeds, might come in a branded form, white labelled, or branded as distributed but white label licensed so you can remove/rebrand if you want to put the effort in.

Images are also handy things to be able to reuse, again because they can be hard to produce in at least two senses: firstly, coming up with the visual or graphical idea, i.e. how to depict something in a way that supports teaching or learning; secondly, actually producing the finished artwork. One widely used form of image reuse in the OU is the “redrawing” of an image originally produced elsewhere. This represents a reuse, or re-presentation, of an idea. In a sense, the image is treated as a sketch that is then redrawn.

This level of “micro reuse” of a resource, rather than the “macro reuse” of a course, is not something that was invented by OERs – academics have always incorporated and referenced words and pictures created by others – but it can make reuse easier by simplifying the permissions pathway (i.e. simplifying what otherwise might be a laborious copyright clearance process).

One of the other ways of making use of “micro” resources is to reuse them with modification.

If I share a text with you as a JPG of a PDF document, it can be quite hard for you to grab the text and elide a chunk of it (i.e. remove a chunk of it and replace it with … ). If I share the actual text as text, for example, in a Word document, you can edit it as you will.

Reuse with modification is also a fruitful way of reusing diagrams. But it can be harder to achieve in practical terms. For example, in a physics or electronics course, or a geometry course, there are likely to be standard mechanical principle diagrams, electrical circuits or geometrical proofs that you are likely to want to refer to. These diagrams may exist as openly licensed resources, but… The numbers or letters you want to label the diagram with may not be the same as in the original. So what do you do? Redraw the diagram? Or edit the original, which may reduce the quality of the original or introduce some visual artefact the reveals the edit (“photocopy lines”!).

But what if the “source code” or means of producing the diagram. For example, if the diagram is created in Adobe Illustrator or CorelDRAW and the diagram made available as an Adobe Artwork .ai file or a  CorelDRAW .cdr file, and you have an editor (such as the original, or an alternative such as Inkscape) that imports those file formats, you can edit and regenerate a modified version of the diagram at the same level of quality as the original. You could also more easily restyle the diagram, even if you don’t change any of the content. For example, you could change line thickness, fonts or font sizes, positioning, and so on.

One of the problems with sharing image project files for particular applications is that the editing and rendering environment for working with project file is likely separate from your authoring environment. If, while writing the text, you change an item in the text and want to change the same item as referenced in the image, you need to go to the image editor, make the change, export the image, copy it back into your document. This makes document maintenance hard and subject to error. It’s easy for the values of the same item as referenced in the text and the diagram to drift. (In databases, this is why you should only ever store the value of something once and then refer to its value by reference. If I have your address stored in two places, and you change address, I have to remember to change both of them; it’s also quite possible that the address I have for you will drift between the two copies I have of it…)

One way round this is to include the means for creating and editing the image within your text document. This is like editing a Microsoft Word document and including a diagram by using Microsoft drawing tools within the document. If you share the complete document with someone else, they can modify the diagram quite easily. If you share a PDF of the document, they’ll find it harder to modify the diagram.

Another way of generating diagrams is to “write” it, creating a “program” that defines how to draw the diagram and that can be run in a particular environment to actually produce the diagram. By changing the “source code” for the diagram, and rerunning it, you can generate a modified version of the diagram in whatever format you choose.

This is what packages like TikZ support [docs].

And this is what I’ve been exploring in Jupyter notebooks and Binderhub, where the Jupyter notebook contains all the content in the output document, including the instructions to create image assets or interactives, and the Binder container contains all the software libraries and tools required to generate and embed the image assets and interactives within the document from the instructions contained within the document.

That’s what I was trying to say in Maybe Programming Isn’t What You Think It Is? Creating Repurposable OERs (which also contains a link to a runnable example).

PS by the by, I also stumbled across this old post, an unpursued bid, today, that I have no recollection of at all: OERs: Public Service Education and Open Production. Makes me wonder how many other unfinished bids I started…

2 comments

  1. nessman

    This definitely starts to solve one of the old canards of OERs, that if they are shared in “closed formats” it makes them very difficult to modify. But if instead, as you say, what you are sharing is not just the resulting image but the underlying code that generated it, this becomes a non-issue. Sorry it’s taken so long to grok what you are getting at but the last two posts have helped immensely. I think part of the difficulty is that this makes clear (to me at least) that there needs to be some drastically different approaches to “content” and “teaching” across disciplines – lots of science/engineering/maths/comsci education will benefit from these types of “computational authoring” approaches which might not be as appropriate in other disciplines. Seems obvious, but too often the term “open educational resource” leads us to think of a single solutions/platforms/approaches when there are some dramatic differences across disciplines.

    • Tony Hirst

      @Scott re: “what you are sharing is not just the resulting image but the underlying code that generated it” – not just that, also a prebuilt environment required to run the code (i.e. all required packages installed) and a runnable version of that environment. If the user has to do anything other than just click a link to get into the running and working environment, it’s too hard…

      Re: STEM subjects, my showntell repo also has a music branch (showing how to write musical scores and generate midi/audio files from them, (not sure about score from midi?), and a maps branch showing how to generate different sorts of map.

      On to do list: text analysis, eg for visualising structures of texts and helping search through them (perhaps also w/ demos that link to third party “cognitive APIs”), and image wrangling (eg using imagemagick; maybe also links to the cognitive APIs for parsing features in images etc.)

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