Teaser: Plagiarism* is Good

[fusion_builder_container hundred_percent=”yes” overflow=”visible”][fusion_builder_row][fusion_builder_column type=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none”]

Rocket Science Remix

Photo Credits: @duiceburger/flickr remix of NASA images and skeletalmess used with permission.

Rocket Science Remix

Plagiarism is Good™ (Revised)

I propose a new metric to evaluate the use of open educational resources (OER); by running a plagiarism-style detector, like TurnItIn, against the web, we should be able to find additional occurrences of text from open educational resources. In this case, Plagiarism is Good™, very good. The act of copying or remixing all or part of an OER is an important activity. By finding where and how OER text is used, we’ll be able to tell who is using/re-using it and perhaps what they’re doing with it. Given that most OERs are licensed to permit copying and modification (with attribution), finding additional occurrences on the web at large is the exact sort of thing we’d expect/hope to happen.

One of the reasons I haven’t written this up before is that I haven’t fully though through the idea. But it seems like now is a good time to start. My impetus, recently, S.M. Duncan published his Ph.D. dissertation on Patterns of Learning Object Reuse in the Connexions Repository. At the end of the dissertation, he describes some of the limitations of her empirical study and some methods to investigate further.

He says:

Potential methods to overcome some of these limitations include analysis of blog track-backs (i.e., web of science-like reverse referencing for blogs), use of technology like Google’s “link:” search operator (e.g., reverse linking for a selected URL), and software designed to identify plagiarism in texts.

— S.M. Duncan

Source: Duncan, S.M. (2009). Patterns of Learning Object Reuse in the Connexions Repository. Doctoral Dissertation, Utah State Unviersity. Retrieved June 11, 2009 from Internet Archive Web site: http://www.archive.org/details/PatternsOfLearningObjectReuseInTheConnexionsRepository

Keep reading for the history and how I might go about doing it.

Building on Thinking While at COSL

It’s great to see the idea that I first suggested at COSL probably 2-3 years ago get mentioned in print somewhere! To be fair, Tom Caswell and I have talked briefly about this idea a couple times over the last year and a half or so. But, I still haven’t gotten around to writing it up.

My original plan was to post the idea here inline in my blog, but as I started writing the reasoning I thought it might be better to post the work in progress as probably a Google Doc. I’ll be able to go back to the document, edit it, expand it and add to it. Really this idea wants to be a whitepaper or journal article, not just a blog post.

So this is the teaser. I wanted to get it published relatively quickly. I’ll updated this post in the next week or so with the link to the work in progress.

What do you think? Is this a good idea?
Do you want to work on this project? (There’s no funding by the way…)

*Aside: Let me be clear, I’m not really talking about plagiarism. Since I’m talking about OERs that are openly licensed, I’m talking about using and modifying them within the bounds of their license to create modifications and derivative works. In Creative Commons speak: “to Remix — to adapt the work”. And most importantly to properly attribute the author as required by the license. Once again in Creative Commons speak: “Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work).” (Which most people using Creative Commons licenses don’t provide, and I’ve been exploring plugins that work well to do that for this blog).[/fusion_builder_column][/fusion_builder_row][/fusion_builder_container]

1 reply

Trackbacks & Pingbacks

  1. Plagiarism Detection to Track OER Reuse « Open Education News says:

    […] 14, 2009 · No Comments Brandon Muramatsu at MIT has a new blog post suggesting the use of plagiarism software to detect OER reuse. Muramatsu […]

Comments are closed.