Accelerating e-Learning Interoperability

1. Accelerating e-Learning Interoperability Introducing the CLEO Lab Tyde Richards IBM Mindspan Solutions Daniel R. Rehak Carnegie Mellon University

2. Overview • e-Learning interoperability • ADL and the Sharable Content Object Reference Model (SCORM) • Introducing the CLEO Lab • discussion

3. Data Model Data Model e-Learning interoperability? Ability to construct the technology supporting Web-based learning from building blocks that can be easily integrated and reused Large blocks (systems: LMS to HR) About learners, learning, resources exchange Small blocks (content: lesson to lesson) Binding issues syntax, protocol, API

4. Growth of interest in the problem • 1988 - early interest in aviation industry due to special circumstances (AICC) • 1996/97 - Web sparks general interest, many new players • ARIADNE, IMS, ADL, IEEE LTSC • 1998/present – collaboration, division of labor, and still more players • Prometeus, ALIC, SC36, CLEO Lab

5. Many Initiatives, Many Differences • Geography • U.S., Europe, Asia • Intended Learner • Corporate, Military, Higher Ed, K12 • Technical focus • Meta-data, learning management, simulation • Work products • Research, specifications, profiles & conformance, formal standards

6. Working together: the ideal applied research specification development profiles & conformance formal standards CLEO Lab IMS ADL IEEE LTSC AICC ISO JTC1 SC36

7. ADL and SCORM • ADL (U.S. Advanced Distributed Learning Initiative) • Formed 1997 to accelerate e-Learning in U.S. • Critical mass of vendor interest • Recent international outreach • SCORM (Sharable Content Object Reference Model) • Compiles mature specifications from other initiatives • Will be required for U.S. government procurements • ADL will provide conformance testing software

8. The Components of the ADL SCORM CONTENT AGGREGATION MODEL Meta-data XML Binding Best Practice From IMS RUN-TIME ENVIRONMENT Content to LMS API From AICC Content Structure Format Derived from AICC Meta-data dictionary From IEEE Content to LMS data model From AICC

9. SCORM Runtime Communicationthe AICC API Content in Browser LMS/Server HTML “wrapper” from LMS Internet Content API Adaptor From LMS Processing API Calls • Simple API • LMS Initialize() • LMSGet/SetValue(element) • LMSFinish() • JavaScript calling conventions • API Adaptor is part of LMS

10. SCORM Content Aggregationbased on the AICC approach • Key insights from the AICC • Make learning content in reusable units smaller than course • Aggregate content with a document that can be easily changed • Initial SCORM improvements • Use XML for for aggregation document • Incorporate LOM for meta-data • Upcoming SCORM improvement • Use IMS Content Packaging specification as framework • Separates learning organization from resource organization

11. Looking forwardAggregation using IMS Content Packaging Example simplified <manifest identifier="Course01" xmlns:adl=”http://www.adlnet.org”> <organization identifier="sample course"> <item identifier="sco1" resourceref="sco1Res">> <adl:SCORMdata>some data</adl:SCORMdata> <item identifier="sco1" resourceref="sco2Res"> <adl:SCORMdata>some data</adl:SCORMdata> </item> </item> </organization> <resources> <resource identifier="sco1Res" type="webcontent"> <metadata> sco1 metadata record </metadata> <file href="Course01\Lesson01\sco01.htm"/> </resource> <resource identifier="sco2Res" type="webcontent"> <metadata> sco2 metadata record </metadata> <file href="Course01\Lesson02\sco02.htm"/> </resource> </resources> </manifest> learning activities data to support a learning style activities mapped to resources resources for activities LOM record for resource

12. SCORM Meta-databased on IEEE LTSC LOM • Learning Object Metadata (LOM) • Draft standard in IEEE LTSC • Harmonizes work from IMS, ARIADNE (that built on DC work) • Approximately 80 data elements organized by category(general, lifecycle, metametadata, technical, educational rights, relation, annotation, classification) • SCORM usage • Recommends LOM elements to describe three levels of content granularity: course, sharable content object and raw media • Recommends XML binding developed by IMS and ARIADNE

13. Experience with SCORM to date • Positives • Technical approach appears viable • Significant endorsement from content and LMS vendors • Challenges • SCORM design center the conventional self-paced course • What about other approaches to learning? • With interoperability loose important capabilities found in proprietary approaches • User interface consistency across reusable components • Rule-based control of learning activities

14. Introducing the CLEO LabCustomized Learning Experiences Online • Research collaboration on future SCORM capabilities with focus on learning experience customization • Organized under aegis of IEEE ISTO • Participants - CISCO Systems, Click2Learn, IBM Mindspan Solutions, Microsoft Corporation, NETg, U.S. ADL Initiative • Funded research at Carnegie Mellon University and the Open University, U.K. • Duration one year, may be extended • Findings to be contributed to initiatives developing open specifications in support of the ADL SCORM

15. The CLEO Lab approach Learning scenarios drive interoperability requirements academic oversight data models learning scenarios technical framework e.g. learner performance scenario delivery agent services development e.g. platform e.g. sequencing e.g. reusable parts content e.g. rich media

16. CLEO Lab Deliverables • Framework and data models for learning content structure, sequencing, rendering and control used to create customized learning experiences • Learning model descriptions • Technical findings from test bed activities

17. CLEO Lab Scenario Requirements • Define taxonomy of learning models • Assume content samples from participants • Use conventional CBT as baseline • “do it right” • Demonstrate generality with two additional models • Under discussion: collaboration, performance support, intelligent tutoring • Address additional models if collaboration continues past initial year

18. CLEO Lab Framework Requirements • For runtime, authoring, interoperability • Support different “Learning Models” • A content structure representation • Models for behavior and sequencing • Models for rendering look and feel • Content repositories with metadata • Content toSystem communications

19. CLEO Lab “Speculations” • Models and frameworks for specifications • Intended to aide organizations developing open specifications to advance the ADL SCORM • Identified candidates • Content Structure • Content Sequencing • Content Presentation • Content Variants

20. Overview Overview Introduction Introduction Importance Importance Objectives Objectives Objective Objective Objective Objective Objective Objective Prerequisites Prerequisites Scenario Scenario Outline Outline Content Structure Example strategy templates content structuredefined from reusable“strategy templates” Generic Overview Introduction Importance Objectives Content Packaging XML “Manifest” Prerequisites Scenario Outline Unordered max items = 20 Any Any

21. Relation to W3C technologies • Appropriate forum to explore relevance of emerging W3C technologies to e-Learning • Content formats and processing • XHTML, SMIL, SVG, MathML, XSLT • Meta-data • Relation of LOM to RDF, Semantic Web • Data Models • XML bindings assumed, evaluate supporting technologies • Communication • Current JavaScript API, exploring SOAP, XMLP

22. Summary and Discussion The CLEO Lab www.cleolab.org contact Greg Kohn g.kohn@ieee.org