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Learning registry Presentation 2013 04-04


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Presented for the SolaR distributed Doctoral Research Lab (

Presented for the SolaR distributed Doctoral Research Lab (

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  • Thanks for the opportunity to speak about the Learning Registry. It’s always good to hear how new audiences react to it. I’d like to take this opportunity to acknowledge the organizations who provided funding and staff support for the Learning Registry, the US Department of Education and the US Department of Defense. I’d also like to give a special shout out to several organizations who were early testers and experimenters with the LR, National Science Digital Library, a California-based company that specializes in teacher portals, called Navigation North, and the UK higher ed organization JISC which ran the JLeRN Experiment to create and test an LR node at Mimas in 2011 and 2012.
  • I’d like to talk about what we think is missing from the dialogue about learning resources. But first I’d like to remind us about the changing landscape of learning, first by looking back in time…
  • We’re seeing some signs that these practices are becoming less common in K-12 classrooms: judging students learning opportunities by how much they are in formal learning situations hearing lectures, grouping them by age, using paper as the medium for knowledge delivery and exploration; and for all practical purposes, open-loop feedback systems.
  • What’s the evolution of these fading practices? No lectures, more continuous learning experiences, collaborative and personalized learning, and data, data, data.
  • Many see the enablers of these changes being the ability to take advantage of the data intelligently. Closed feedback systems enable learning objects to be improved, let instruments collect assessment data surreptitiously, enable recommendations and adaptations; support engagement, grit, tenacity, and persistence; and keep the human in the loop to create “data curious” consumers who use patterns in data as opportunities for reflection and discussion.
  • That said, to RECOMMEND learning resources, we need to LOCATE them. What’s holding us up?
  • Transcript

    • 1. + i sk The Learning w ko Registry: Building a en Bi ie Foundation for ar M Learning Resource al Analytics n tio na er nt II SRFunding from US Dept of Education US Dept of Defense Numerous contributions from the Learning Registry Open Source Community. Special thanks to NSDL, JISC, and Navigation North
    • 2. Why worry about learning resources?2013-04-04
    • 3. Fading Education Practices• Hour-long classes, “seat time” requirements• Students grouped by age• Lecture-based teaching• Paper textbook as primary learning resource; No cell phones in class• Small, delayed and disconnected data: some testing feedback, reports (midterm, final), attendance, free lunch eligible
    • 4. Deeply Digital Learning• Flipped classroom w/online practice and homework via adaptive tutors• More engaging and inspiring 24/7 learning: games, projects, badges for competencies• Learners collaborate by ability, interest• Digital media/platforms for open or personalized learning• Data ecosystems including the Internet of Learning Things
    • 5. Analytics and Data Mining• Continuously improving courses, curricula, and apps• Continuous and stealth testing• Personalized, adaptive learning pathways; recommended online learning resources• Students succeed with the right challenge, right encouragement, and right engagement• Interactive data visualization systems (aka “dashboard”) for learners, teachers, leaders
    • 6. Stovepiped repositories hold data andshare through pipes like OAI-PMHMetadata grows stale as people refuse toupdate or even add at the outsetData exhaust is wasted: it’s not poweringanythingLearning resources languish “on the shelf”Data is locked in and locked down
    • 7. Stovepiped repositories hold dataand share via pipes...Vs.Data is shared in the open foraggregation, amplification,analysis…
    • 8. Metadata grows stale as peoplerefuse to update or even add at theoutset (“We can’t plan on goodmetadata.”)Vs.Enrich the data pool with socialusage data (attention metadata,paradata) to add nuance tometadata
    • 9. Data exhaust is wasted−it’s notpowering anythingVs.Data exhaust is collected to powerthe social life of learningresources
    • 10. Learning resources languish onthe shelfVs.Resources live in a richecosystem
    • 11. Data is locked in and locked downVs.Democratization/Liberation ofdata
    • 12. Data is shared in the open foraggregation, amplification, analysis…Learning Registry is a distributedsystem that permits sharing of metadataabout learning resources…developed through an open communityprocess that engages learning resourcecreators, publishers, curators, andconsumers.
    • 13. Learning Registry is a store-and-forward data exchangenetwork—not a destinationwebsite, search engine, orrepository—upon which diverseuser services can be built. Enrich learning resource data with paradata to add nuance to metadata…
    • 14. LAK 12
    • 15. Annotational Paradata Kinematic Paradata Pedagogical Paradata 15 Refines descriptive Illustrates diffusion through Refines educational context metadata user actions and utilityTagged (as…) Clicked User demographics aggregatedfrequency by tag accessed, # of hits, … by paradata contributorRecommended / Included in Viewed Embedded (in…)Group Collection watched, interacted with, …# of times Correlated / Aligned (to…) Downloaded to standard, to grade level, to curriculumCommented / Discussed saved a local copy# of times – content of comments/discussionshandled as annotations Favorited / Included in Modified reused, created derivative work, added to, Personal Collection contextualized, personalized, enhanced,Rated foldered, listed, bookmarked, favorited, combinedavg rating by community, star rating, usability playlistedrating, … ===================== -implemented (in context…) Shared to Social MediaVoted frequency by platform (Facebook, Twitter…) -republished (as…)up/down, liked/disliked, … ===================== -researched================== -subscribed -saved/shared searches-related to other resources -linked to-cited -featured-awarded Data exhaust is collected to power-ranked the social life of learning resources
    • 16. Resources live in a rich ecosystem 2010-09-27 LAK 12
    • 17. + Liberate the data…2010-09-27 LAK 12
    • 18. + LAK 12 Liberate the data…
    • 19. Many learning resource systemscan be connected into the LearningRegistry network through publishand consume APIs Learning Object Repositories, Teacher Portals, Search tools, Learning Management Systems, and Instructional Improvement Systems. LAK 12
    • 20. Currently the Learning Registry mainly contains metadata, published+ from a number of collaborators, about resource classification and usage data. SHOW JIMS MAPPING HERE
    • 21. Built on CouchDB document distributionsystem: easy to set up new nodes andreplicateMetadata agnostic: uses JSON key-valuepairs to encapsulate metadata in anyschemaSocial usage data modeled on NSDLCom_para and activity streamsUses URL to identify resources; submitteridentity verified by digital signature
    • 22. Paradata Schema-- actor (required, except for assertions): the person or group whodoes some-thing; a string or a compound object (as shown below) thatdescribes characteristics of the actor object-type: the actor value description: information about the actor-- verb (required): the action that is taken; it can be a simple string. Ifit is a compound object, then verb contains: action: the verb value measure: the occurrences of the verb (whether counts,averages, ratings, or other things). date (optional): start time / stop time when the action occurs. context (optional): place where the action takes place-- object (optional): the thing being acted upon. The important part ofan object is the URL (or URI) where you can find out about the object(or get the object, or ideally both).-- related (optional): describes a relationship between the object(above) and other objects listed within-- content (optional): a human-readable string description of what theparadata item expresses
    • 23. DataServices
    • 24. Some Active Adopters/ExperimentersNaviation North: Brokers of Expertise and CTEOnline http://www.commoncorelabs.cominBloom K-12 Student Integration Systems: Experiment:http://jlernexperiment.wordpress.comState Improvement Systems
    • 25. Recommendations by clustering users or bybuilding a social network graph and thenrecommending resources among a cluster ornetwork.Feedback to developers about the utility of theirresources, about who adapts them and how, andcould eventually cause “widespread sharing” oflearning resources to learners at the appropriatetime.
    • 26. What’s Next? Work on identity, creating the “network effect,” digital signing for spam control, fear of loss of competitive advantage from data sharing Gathering performance statistics LRMI validation (tip the preference to LRMI) Accessibility metadata
    • 27. ReferencesBienkowski and Klo. Forthcoming. The Learning Registry:Applying Social Metadata for Learning ResourceRecommendations. in Nikos Manouselis, Katrien Verbert,Hendrik Drachsler and Olga C. Santos, Eds. RecommenderSystems for Technology Enhanced Learning: Research Trends &Applications, Heidelberg: SpringerLee A, Hobson, J. Bienkowski, M. Midgley, S. Currier, SCampbell L M, Novoseova, T. 2012. Towards NetworkedKnowledge: The Learning Registry, an Infrastructure for SharingOnline Learning Resources. Educational Technology. V. 52, N. 6.November-December. pp 14-19.Bienkowski, M., Brecht, J., & Klo, J. (2012). The LearningRegistry: Building a Foundation for Learning Resource Analytics.Learning Analytics and Knowledge 2012 (LAK12): 29 April – 2May 2012, Vancouver, BC, Canada.
    • 28. +Learning Registry Ac kn ow l ed ge m en Kl Mai o n ts , S LR RI C & om W m al it Many slides courtesy of: t G te Steve Midgley ra rs: ta Jim Office of Ed Tech ,A DL US Department of Education Susan Van Gundy & Formerly UCAR/NSDL Daniel R Rehak, PhD (former) ADL Technical Advisor Department of Defense