Gaining Advantage in e-Learning with Semantic Adaptive Technology
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The document outlines a webinar on end-to-end smart publishing and e-learning hosted by Impelsys and Ontotext, focusing on the integration of semantic adaptive technology. It details the capabilities and partnerships between the two companies, which aim to provide personalized learning solutions and improve content delivery through semantic enrichment. Use cases and production processes for adaptive learning and course development are also discussed, highlighting the advantages of adopting their technology over traditional systems.
Gaining Advantage in e-Learning with Semantic Adaptive Technology
- 1. Ontotext – Impelsys Webinar Series END-TO-END SMART PUBLISHING AND E-LEARNING GAINING ADVANTAGE IN E-LEARNING WITH SEMANTIC ADAPTIVE TECHNOLOGY THURSDAY 28 JULY | 11AM EDT | 4PM BST | 6PM EEST July 2016
- 2. We will talk about… Introduction About Impelsys and Ontotext Adaptive Semantic Solution Adaptive Semantic Platform Use cases Demonstrations Adaptive Semantic Solution – Production Process Questions & Answers
- 3. Impelsys & Ontotext: Partnership Publishing x Technology | Content x Semantics Introduction1
- 4. About Impelsys 15 YEARS 100%PUBLISHING & EDUCATION FOCUS 350+ EMPLOYEES New York HEAD QUARTERS • Digital Product Development • Content Delivery Solution – iPublishCentral • Authoring & Editorial Workflows • Mobility & Bespoke solutions • DRM & Analytics Bangalore R&D • Global team, local sales & accounts support • Innovation Hub & Global Delivery Center at Bangalore • Technology partners • Cutting-edge infrastructure on Amazon & Rackspace New York Bangalore London SFO
- 5. iPublishCentral – Global Reach Millions Of B2B Users Students Instructors Professionals 15,000 LIBRARIES Million+ B2C Users LIVE PORTALS 100+ TITLES 250,000 Global Customer Presence
- 6. Supporting Content Delivery For Global Brands
- 7. About Ontotext 16 YEARS 100%SEM.TECH. FOCUS 350+ EMPLOYEES Sofia HEAD QUARTERS • Semantic graph database engine combined with Content management solutions • Interlinking text and data to unveil meaning • Delivering unmatched search and exploration Sofia R&D • Global team, local sales & accounts support • R&D Center at Sofia, Bulgaria • Serving BBC, FT, Wiley, Oxford UP, IET, … • SaaS infrastructure on Amazon and on premise New York Sofia London Frankfurt
- 8. Ontotext Capabilities Integrate proprietary databases and taxonomies with Linked Data Infer facts and relationships Interlink text and with big data Better content analytics, retrieval and recommendation
- 9. Positioning in Graph DBs “Despite all of this attention the market is dominated by Neo4J and OntoText (GraphDB), which are graph and RDF database providers respectively. These are the longest established vendors in this space (both founded in 2000) so they have a longevity and experience that other suppliers cannot yet match. How long this will remain the case remains to be seen.” Bloor Group whitepaper Graph Databases, April 2015 http://www.bloorresearch.com/technology/graph-databases/
- 10. Ontotext Clients (selection) Major financial Information agency Major business and legal Information agency
- 11. Why Impelsys & Ontotext Impelsys Ontotext Semantic publishing and eLearning technology platform Semantic enrichment and personalized recommendations Graph database, data and knowledge representation Authoring solution Content transformation & SMEs Content & e-learning delivery Offer semantically enriched solutions to publishers and e-learning providers E-Learning Authoring & Editorial workflows Semantic Content Enrichment, Knowledge Graph management, Thesauri and Ontology management, Linked Open Data integration Transformation services/Content authoring and editorial outsourcing Delivery, personalization and recommendation solutions Together Impelsys’ iPublishCentral/publishing BPO and Ontotext’s Semantic Publishing Platform bring end-to-end semantic publishing and content editing/transformation services to the market
- 12. Personalized learning for effective and efficient learning outcome Adaptive Semantic Solution3
- 13. Adaptive Learning Adaptive learning is an educational method to orchestrate the allocation of mediated resources according to the unique needs of each learner.
- 16. Presentation of Concepts – Typical Courseware
- 17. Presentation of Concepts – Adaptive Courseware
- 19. Value Proposition Traditional server based Adaptive system is: Costly Complex to implement Not flexible SemTech powered Adaptive Technology is: Inexpensive Simple to implement Flexible Platform independent
- 20. Adaptive Semantic Platform2 eLearning vertical
- 23. API stack
- 25. Mapping Content and Curricula: Details
- 27. Adaptive Semantic Technology: Details
- 28. Use cases4
- 29. • Goals − Better management and enrichment of e-learning content − Improved reuse of legacy content − Increase user engagement • Challenges − Content locked only for specific products instead of being enriched and reused for development of dynamic content offerings • Approach − Semantic enrichment of learning objects across different subjects and product lines − Smarter search and contextual recommendations of relevant learning objects Use case 1: Global Educational Publisher
- 30. • Goals − Improved and more efficient vocabulary management − Metadata enrichment of all available assets − Efficient search and relevant recommendations − Automatic association of assets to curricula • Challenges − Lack of integration between the different systems of the customer − A lot of manual operations on metadata enrichment and association of asset to curricula • Approach − Knowledge Base development, responsible for managing vocabularies, curricula, ontologies, assets metadata − Semantic enrichment of metadata − Semantic recommendation engine Use case 2: Global Provider of Multimedia Assets for Educational Publishers
- 31. Use case 3: RCNi Learning (Royal College of Nursing) Requirement • Learning management platform to deliver learning modules to practicing nurses and nursing students. • Platform to help practicing nurses meet their continuing professional development (CPD) requirements. • Course modules to be developed from existing RCNi journals. Impelsys Approach • iPublishCentral Learn platform with administrator, instructor and student access. • Dedicated native mobile apps for anytime, anywhere access. • SMEs’ (Subject Matter Experts), cognitive scientists and instructional designers to convert journals to learning modules. • Adopted semantic technology to automate courseware development process.
- 32. Demonstrations5
- 33. Demo 1: Impelsys Adaptive Content
- 34. Demo 2: BBC Wildlife Portal
- 36. Production Process SMEs and IDs analyze the subject/ topic, identify Concepts and prepare the Courseware Prepare different levels of concepts (normal, medium, and detailed) Specify different kinds of content (textual, A/V, simulation, etc.) Prepare Pre-test, topic level tests and transition rules Transition rules are created as a special language interpreted by Adaptive Engine
- 37. Analyze Atomize & Enrich Reprocess Package, Test & Deploy Analyze - Assets (text, A/V, Images, Simulations) - Learning Objects - Topics - Assessments - Metadata and taxonomy / ontology analysis - Data consolidation analysis Chunking & data modelling - Breakdown into smaller LOs (Nodes) - Assign weights to Nodes - Create concept-wise mini quizzes - Associate Nodes with quizzes - Identify Node transition paths & conditions - Ontology & Thesauri Semantic enrichment of content - Repackaging of content (eg. Text with images, etc) - Automatic tagging of LOs Quality assurance - Verify Atomized Content by SMEs and Customer - Verify data model and semantic enrichment Reprocess - Create pre-test to measure learner’s initial knowledge level and learning reference Create instrumentation at each Node (using xAPI or TINCAN) - Define rich LOs in the knowledge graph - Specify transition rules for each node - Create initial Learning Path using Instruction Design and Pedagogic principles Quality assurance - Verify transition rules with SMEs and teachers / trainers Package - Create UI - Package as per SCORM or plain HTML5/ JavaScript Test - Test UI transitions - Verify content Quality Check - Verify Adaptive Course with SMEs and teachers / trainers - Verify UX and Adaptive Course with pilot user groups Non- Adaptive Course Adaptive Course Production Process - Detailed
- 38. Analyze Atomize & Enrich Reprocess Package, Test & Deploy 2-3 weeks 1-1,5 months 3-4 weeks 1-2 weeks Non- Adaptive Course Adaptive Course Production Process - Timeframe