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

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

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

Growth of interest in the problem 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

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

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

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

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

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

SCORM Content Aggregation based 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

Looking forward Aggregation using IMS Content Packaging <manifest identifier="Course01" xmlns:adl=” > some data some data sco1 metadata record sco2 metadata record data to support a learning style resources for activities LOM record for resource activities mapped to resources learning activities Example simplified

SCORM Meta-data based 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

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

Introducing the CLEO Lab Customized 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

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

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

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

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 to System communications

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

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

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

Summary and Discussion The CLEO Lab contact Greg Kohn