Category Archives: lrmi

LRMI Implementation Case Study: Gooru

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Project lead: Lisa McLaughlin,  Senior Director of Partnerships

“Gooru’s mission is to honor the human right to education. We are dedicated to engaging a community of teachers, developers, and supporters to unleash personalized learning with technology to educate all the students of the world.”

http://www.goorulearning.org/

Gooru serves as a personalized learning platform, incorporating a custom search engine, playlist creation tool, and content aggregator.  The system allows users to find standards-aligned, interactive learning materials that have been curated by teachers; share those materials in the form of custom collections, personalized to meet the needs of individual students; and measure students’ progress across collections and quizzes assigned to them.  Users can search over 2 million CC licensed learning resources, browse through collections, lessons and individual resources and filter search results by grade level, resource type, and Common Core State Standard.

Gooru resource search

Gooru resource search

Gooru is a repository of playlists, rather than a repository of content.  There are currently 18 million resources in the Gooru catalog; 180,000 of these are tagged to instructional standards such as the Common Core State Standards and 50,000 are collections created by teachers and students. Users can also build assessment features into their playlists and the system includes an assessment bank of 1.5 million items. Gooru resources carry a variety of different licences but all are open and free to use. Playlists are currently shared under a CC BY SA licence, however Gooru are in the process of transitioning to CC0 over the course of the next month.  Most content is aimed at the K-12 sector.

Gooru collection search showing CCSS classification

Gooru collection search showing CCSS classification

Gooru has developed an open source learning architecture licensed under the MIT Open Source Initiative approved licence, and a number of APIs that enable developers to build applications based on the Gooru infrastructure. The Gooru APIs are available here: Gooru APIs, and further information about the Gooru development community is available here Gooru Learning Developers.

A custom Gooru Metadata Schema (GMS) composed of 40 fields has been created from various metadata schemas. The Gooru Metadata Schema may be regarded as a variant of the LOM, though to date, GMS has not been mapped directly to LOM. Accessibility Metadata Project fields are used to describe the accessibility of content.

Content with high quality metadata is weighted more heavily in search results, though other factors also come into play, such as how many times a resource is included in other playlists.

Gooru does not ingest metadata through OAI PMH; some metadata is generated by users uploading resources and tagging them using the GMS, but the majority comes from web crawling. Domains are curated through a range of input, both internal and through Gooru’s wider network of partners, before pursuing crawls. Teacher-added domains are prioritized.  Basic metadata including title, author, publisher, description, etc is captured from each domain, and then passed to a QA cleaning team, who manually identify more nuanced characteristics, e.g. educational use, time required, etc. For subjective fields, such as educational use, a script has been created for cleaning the metadata. The QA team is currently focused on cleaning the metadata on all OER collections and Gooru recently launched an OER filter.

Metadata fields are currently stored in an SQL database, however Gooru will move to a no-SQL framework later in 2014.  Paradata is also  stored in similar SQL tables but is returned by different APIs. Only some of the Gooru paradata is currently exposed.

Components of LRMI have been incorporated into the Gooru Metadata Schema and a mapping can be provided from the GMS to LRMI.  Approximately 95% of the Gooru catalog is now tagged with LRMI.

The following LRMI properties and types have been implemented and the Gooru LRMI Metadata schema is available here (.xls).

  • educationalAlignment
  • educationalUse
  • timeRequired
  • typicalAgeRange
  • interactivityType
  • learningResourceType
  • useRightsUrl
  • isBasedonUrl

The GMS includes an Educational Alignment field with alignment types ‘subject’ and ‘educational level’.  Alignment type ‘text complexity’ may be added in the future.

In addition to Common Core State Standards, Gooru content is also aligned to  Texas Curriculum Standards and California Science Standards

Links

Gooru
Gooru Metadata Guide
Gooru LRMI Metadata Schema


Licence information in schema.org and LRMI

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When the Learning Resource Metadata Initiative (LRMI) technical working group started its work it focused on identifying the properties and relationships that were important for educational resources but could not be adequately expressed using schema.org as it then stood. One of those important pieces of information was the licence under which a resource was released, and so the LRMI spec from the start had the property useRightsUrl  “The URL where the owner specifies permissions for using the resource.” When schema.org adopted most of the LRMI properties, useRightsUrl was an exception, it was not adopted pending further consideration–not surprising really given the wide-ranging applicability of licence information beyond learning resources.

Back in June the good news came that with version 1.6 of schema.org included a license property for Creative Works that does all that LRMI wanted, and more.

What does this mean for LRMI adopters?

Some adopters of LRMI have already started using useRightsUrl.  Such implementations are valid LRMI but not valid schema.org, which means that they will only be understood by applications that have been written specifically to understand LRMI and not by the general purpose web-scale search applications. This is sub-optimal.

In passing, let me mention another complication. With schema.org you have a choice of syntax: microdata and RDFa 1.1 lite. With RDFa there was already a mechanism for identifying a link to a licence, that is rel=”license”.  Just to complicate a little more, RDFa allows name spacing, and the term license appears in at least three widely used namespaces: HTML5, Dublin Core Terms, and the Creative Commons Rights Expression Language–hopefully this will never matter to you.  To exemplify one of these options I’ll use the HTML that you get when you use the Creative Commons License Chooser (but let’s be absolutely clear, what I am writing about applies to any type of license whether the terms be open or commercial):

<a rel="license" href="http://creativecommons.org/licenses/by/4.0/">

The good news is that all these options play nicely together, you can have the best of all worlds.

If you are already using itemprop=”useRightsUrl” to identify the link to a licence using LRMI in microdata, you can also use the license property and rel=”license”. The following  LRMI microdata with a bit RDFa thrown in works:

<html>
  <body itemscope itemtype="http://schema.org/CreativeWork">
    <a itemprop="license useRightsUrl" rel="license"
        href="https://creativecommons.org/licenses/by/4.0/">
        Creative Commons Attribution 4.0 International (CC BY 4.0) licence
    </a>
  </body>
</html>

If you are using LRMI / schema.org in RDFa, then the following is valid

<html>
  <body vocab="http://schema.org/" typeof="CreativeWork">
    <a rel="license useRightsUrl"
       href="https://creativecommons.org/licenses/by/4.0/">
       Creative Commons Attribution 4.0 International (CC BY 4.0) licence
    </a>
  </body>
</html>

License does what LRMI asked for and more

In my opinion the schema.org license property is superior to the LRMI useRightsUrl for a few reasons. It does everything that LRMI wanted by way of identifying the URL of the licence under which the creative work is released, but also:

  • It belongs to a more widely recognised namespace, especially important if you are wanting to generate RDF data
  • I prefer the semantics of the name and definition: a license can include  restrictions of use as well as grant rights and permissions.
  • the range, i.e. the type of value that can be provided, includes Creative Works as well as Urls

That last points allows one to encode the name, url, description, date, accountable person and a whole host of other information about the licence (albeit at the cost of the not being able to do so alongside LRMI’s useRightsUrl quite so simply)

Summary

The inclusion in schema.org of the license property is good news for aims for LRMI. If you use LRMI and care about licensing you should tag the information you provide about the license with it. If you already use LRMI’s useRightsUrl or RDFa’s rel=”license” there is no need to stop doing so.

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LRMI Implementation Case Study: Jorum

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Project lead – Ben Ryan, Jorum Technical Coordinator.

“Jorum is a Jisc funded Service for UK Further and Higher Education, to collect and share open educational resources, allowing their reuse and repurposing. Jorum’s free online repository service forms a key part of Jisc’s Learning and Teaching digital content offering. It is the first port of call for thousands of resources, all shared and created by those who teach or have been inspired in the FE and HE and professional skills community.”

http://www.jorum.ac.uk/

The Jorum LRMI implementation project began in September 2013 and work is ongoing as the platform develops. Jorum is a DSpace repository containing a wide range of educational resources in many different formats, including a considerable volume of IMS Content Packages. The repository contains approximately 16,000+ resources, most of which are openly licensed. Jorum uses a combination of LOM, DC, LRMI, Jorum metadata, plus custom fields for different collection ‘windows’. LRMI properties are crosswalked to LOM education fields.

jorum_search_results

Jorum search returns page

Implementing LRMI in Jorum presented something of a challenge to the project team as DSpace only allows metadata to be added to ‘items’ which are collections of individual files.  Metadata can not be applied at the file level, e.g. an html page within a content package, and there is no way to add microdata to an individual page. If Jorum ingests a resource that already includes LRMI it can be cross walked to map to the LOM fields, however if a content package contains multiple pages that are marked up with LRMI it is difficult to extract this data as there is nowhere to store it in DSpace.  In addition, in order to enable a search engine to access a full set of LRMI metadata it is necessary to generate a page containing the LRMI which the search engine can hit. The default page generated by DSpace only includes title, author and description. To generate a page with a richer set of metadata it is necessary to create a custom theme, which is a non trivial task.

jorum_record_2

Jorum resource page

Despite the technical difficulty of implementing LRMI in DSpace, the Jorum project has made good progress and the team have plans for further development in this area including implementing the new Schema.org License property, implementing the alignmentObject and aligning it to the UK higher education Joint Academic Subject Coding Scheme.  The project team also plan to build a Google Custom Search engine to demonstrate how Jorum LRMI metadata can be surfaced.

Jorum has implemented the following LRMI properties and types, though this is dependent on what metadata has been supplied for each resource.

  • educationalAlignment: plan to implement in the future
  • educationalUse: yes,
  • timeRequired: yes
  • typicalAgeRange: no
  • interactivityType: yes
  • learningResourceType: yes
  • useRightsUrl: no, but plan to implement License property

The Jorum project team have not yet shared their LRMI metadata with the Learning Registry as they are waiting to upgrade their platform to DSpace 4.0 before taking this implementation forward as DSpace 4.0 includes an upgraded OAI PMH interface providing a good flexible way to generate metadata from different schema.  It should be noted that Jorum have already undertaken a successful Learning Registry implementation project, the Jisc funded JLeRN Experiment ( which successfully built a Learning Registry node in the UK and developed a number of prototype services for LR ingest and querying. The same developer responsible for the JLeRN implementation has been commissioned to undertake the Jorum LRMI implementation and this work will be taken forward once the upgrade to DSpace 4.0 is complete.

Links

Jorum
Jorum Case Study Questionnaire
Jorum Blog: Implementing the Learning Resource Metadata Initiative (LRMI) in Jorum


LRMI Implementation Case Study: Open Tapestry

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Project team: Justin Ball, CTO;  Joel Duffin, CEO

“Open Tapestry is all about discovering, adapting, and sharing learning resources, whether you’re a teacher, an instructor, a professor, a corporate trainer, a learner, or just a curious mind! We help you organize your content into categories–or Tapestries–that you create. Open Tapestry’s toolset allows instructors to develop course materials in a fraction of the time, while invigorating and enhancing learners’ experience. We give you the tools to mold and shape content already on the web to exactly how you want it.”

http://www.opentapestry.com/

open_tapestryOpen Tapestry provides tools to enable users to author resources and create and share modules, or tapestries, from existing content.  The system also has some repository-like  aspects in that it searches open content repositories, harvests metadata and enables users to upload resources. Open Tapestry pulls in all types of resources at different levels of granularity. There are currently around a million resources, mostly aimed at higher education, however Open Tapestry has also worked with online high schools and a few primary grades.  While Open Tapestry encourages use of open content, but users are also able to create closed instances for their own organisations.

Open Tapestry is a custom platform built on Ruby on Rails.  The platform uses a number of open source libraries and about ten APIs, but is not currently open source itself. The code used to detect and parse open licences is based on Open Attribute, and Gem is used to interact with Canvas.

Open Tapestry supports IMS LTI to facilitate learning management system integration.  This allows users to manage content outside the LMS and then present it inside the system.

Open Tapestry harvests metadata using OAI PMH, web crawlers and RSS harvesters.  The application tries to be as inclusive as possible; any format of metadata that is found, e.g. Dublin Core, LOM, LRMI,  will be parsed and stored internally. This internal metadata can then be transformed into any number of other formats.  The system also facilitates some cross walking.  All harvested metadata is retained and users are able to add to that metadata.  A small number of vocabularies are built into the system, e.g. licence.

The metadata that exists for any given resource depends on what has been harvested, or created by users, however if a page has no metadata, Open Tapestry will produce basic fields used for indexing and searching.  Open Tapestry has two main levels of content granularity;  resources and collections (tapestries) and metadata is applied at both of these levels. Collections can be combined from multiple sources and metadata is provided for each source.

Open Tapestry has fields for all LRMI elements but to date, users have tended not to fill them in.

  • educationalAlignment
  • educationalUse
  • timeRequired
  • typicalAgeRange
  • interactivityType
  • learningResourceType
  • useRightsUrl
  • isBasedonUrl

One way to encourage greater adoption of LRMI suggested by Open Tapestry is to focus on providing targeted search for a particular audience or usecase e.g. learning management systems.  LMS are currently grappling with how to integrate openly licensed resources with closed content and LRMI could potentially provide a solution to this problem.

Open Tapestry does not share metadata records with the Learning Registry as the system is primarily a metadata aggregator, very few new metadata record are produced by Open Tapestry.

One significant issue surfaced by Open Tapestry is how to track metadata assertions as resources, and metadata records are edited and aggregated.  This is particularly important for derivative works, where it is necessary to keep track of entire genealogies of who is making the assertions recorded in the metadata.  While cataloguers are aware of the necessity of creating and maintaining high quality metadata, content creators often have low awareness of the importance of metadata until they have a problem, e.g. concerns about who carries liability for a resource or assertion. Technical solutions are required to address this problem.

Links:

Open Tapestry
Open Tapestry Case Study Questionnaire


LRMI Implementation Projects Case Studies

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As part of our work for Creative Commons on the Learning Resource Metadata Initiative (LRMI), my colleague Phil Barker and I have been writing short case studies on a number of LRMI implementation projects that were funded between 2013 – 2014. Ten different OER platforms received small grants from the Gates and Hewlett Foundations to implement the LRMI specification and share their experiences with other developers. I’ll be posting the case studies here over the next couple of weeks and once all case studies have been completed we also plan to produce a high level technical synthesis of the projects’ outputs.

An early overview of some of the implementation projects was presented at the Cetis 2014 Conference at the University of Bolton in June.

LRMI Implementation Projects

Connexions / OpenStax CNX

Connexions, now OpenStax CNX, was launched in 1999 at Rice University to provide authors and learners with an open space where they can share and freely adapt educational materials such as courses, books, and reports. Today, OpenStax CNX is a dynamic non-profit digital ecosystem serving millions of users per month in the delivery of educational content to improve learning outcomes. Tens of thousands of learning objects called pages, are organized into thousands of textbook-style books in a host of disciplines, all easily accessible online and downloadable to almost any device, anywhere, anytime.

Curriki

Curriki provides peer reviewed open educational resources, curricula and instructional materials to support teachers, professional educators, students, lifelong learners, and parents, primarily in the domain of K-12 education. Curriki is a nonprofit organization and the majority of the resources is provides carry Creative Commons licences.

GooruLearning

GooruLearning an open and collaborative online learning community. Gooru enables teachers and students to find standards-aligned, interactive learning materials that have been rated by fellow teachers, share those materials in the form of personalized custom collections, measure students’ engagement, comprehension, and progress, and contribute to an active community of teachers and students by sharing your collections and best practices.

ISKME

ISKME is an independent, education non-profit company whose mission is to improve the practice of continuous learning, collaboration, and change in the education sector. ISKME supports innovative teaching and learning practices throughout the globe, and is well-known for its pioneering open education initiatives. ISKME also assists policy makers, foundations, and education institutions in designing, assessing, and bringing continuous improvement to education policies, programs, and practice.

Jorum

Jorum is a Jisc funded Service for UK Further and Higher Education, to collect and share open educational resources, allowing their reuse and repurposing. Jorum’s free online repository service forms a key part of Jisc’s Learning and Teaching digital content offering. It is the first port of call for 1000’s of resources, all shared and created by those who teach or have been inspired in the FE and HE and professional skills community.

MERLOT

MERLOT is a free and open peer reviewed collection of online teaching and learning materials and faculty-developed services contributed and used by an international education community. The MERLOT collection consists of tens of thousands of discipline-specific learning materials, learning exercises, and Content Builder web pages, together with associated comments, and personal collections, all intended to enhance the teaching and learning experience.

Open Tapestry

Open Tapestry is a toolkit that enables teachers, instructors, professors, corporate trainers, students and learners to discover, adapt, and share learning resources. The Open Tapestry toolkit allows instructors to develop course materials and organise content into categories, or Tapestries, to enhance learners’ experiences.

Peer2Peer University

Peer 2 Peer University is a grassroots open education project that organizes learning outside of institutional walls and gives learners recognition for their achievements. P2PU creates a model for lifelong learning alongside traditional formal higher education. Leveraging the internet and educational materials openly available online, P2PU enables high-quality low-cost education opportunities.

Untrikiwiki

UntrikiWiki were funded to develop a MediaWiki extension to allow the use of schema.org markup in Wikitext. As part of this project, UntrikiWiki advocated the use of open-source extension HTML Tags on wikis.


You are free to adapt the What is Schema.org briefing

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Editable files for the What is Schema.org briefing are now available from the Cetis Publications site. The process of enabling editable copies of this publication has leads me to some reflections on the publishing workflow behind it.

We published What is Schema.org? a Cetis briefing paper for LRMI in June, as with most of Cetis’s publications it is covered by a CC Attribution licence so, according to the terms of that  licence

You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material

Who is using LRMI metadata?

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One question that we always get asked about LRMI is “who is using it?” There are two sides to this, use by search service providers and use by resource providers, this post touches on the latter.

In phase 2 of the LRMI project, various organizations were given small amounts of money to implement LRMI in their systems and workflows. Those organizations are listed on the Creative Commons web site, and Lorna is in the process of gathering together the lessons they learnt which will be reported back shortly. Perhaps more importantly, at least from the point of view of sustainability, are implementations that arise spontaneously, either by organizations with learning resources to disseminate who make a conscious decision to use LRMI, or those who in using schema.org markup find that one of the properties that LRMI added is appropriate.  Of course no one doing this is under any obligation to inform us of what they are doing, so it is harder to keep track of such use. Fortunately the Google Custom Search Engine Wilbert and I cobbled together  can be used to discover such implementations. It’s a bit hit-and-miss, you need to search for common topics (Math, English) and trawl through the results for new sites,  but it’s better than nothing.

Announcing “What is schema.org?”, a new technical briefing paper from Cetis

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As part of my work with Cetis  for Creative Commons on managing the Learning Resource Metadata Initiative (LRMI), Cetis today publish a new technical briefing paper “What is schema.org?”.  LRMI is built on and expands schema.org so that it can be used to describe educationally significant characteristics of resources. I often find when explaining LRMI at a technical level, mostly I am explaining schema.org, hence this briefing as the first of a series coauthored by me and Lorna M Campbell, planned to explain LRMI.

Explaining the LRMI Alignment Object

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The educational alignment property and the associated alignment object that LRMI introduced into schema.org have been described as the “killer feature” for LRMI. However, I know from the number of questions asked about the alignment object and from examples I have seen of it being used wrongly that it is not the easiest construct to understand.

Perhaps the problems come from the nature of the alignment object as a conceptual abstraction, so maybe it will be help to show some concrete examples of how it may be used. However, bear in mind that the abstraction was a deliberate design decision made so that the alignment object should be more widely applicable than the examples given here. So I will first discuss a little about why some simpler more direct approaches were considered and rejected (as were some approaches that would be even more abstract).