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A Viable Process Model for Learning Analytics

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xAPI Camp DevLearn 2018 presentation by Nick Washburn

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A Viable Process Model for Learning Analytics

  1. 1. A Viable Process Model For Learning Analytics 5th Logic, Inc 459 Herndon Parkway, Suite 8 Herndon, VA 20170 nwashburn@5thLogic.com ©2018 5th Logic. All Rights Reserved Nick Washburn Chief Product Officer
  2. 2. October 23, 2018 2 A Process Model for better “Evaluation” • Drills down into the “E” of ADDIE – Evaluation • Each step in a process model produces artifacts – why are artifacts important? • Justification! - documented reasons for decisions made • Helps to maintain, sustain, prove impact, and more • You can follow this model to implement, grow, and sustain a vibrant learning analytics program • This is highly technical stuff if you hire a consultant demand artifacts, processes, exit strategy, success criteria. • Process works for you – you don’t work for the process ©2018 5th Logic. All Rights Reserved
  3. 3. October 23, 2018 3 Goal. Get to a planned ecosystem. ©2018 5th Logic. All Rights Reserved
  4. 4. October 23, 2018 4 ©2018 5th Logic. All Rights Reserved Image Source: https://baldfatguyandholyrollerblog.files.wordpress.com/2016/07/aaa1.jpg?w=1024&h=1084 Is your learning ecosystem planned?
  5. 5. October 23, 2018 5 A Process Model For Learning Analytics 1. Analysis & Design – Understand current system and “to be system”, prototype, focus groups, Design Architecture, Proof of Concept, more 2. Develop & Implement – Follow the plan, iterate. Build, Data connectors, set up databases, LRS, Implement strategies for collecting digital learning and performance activity data – xAPI reporting to anything digital 3. Acquire the Data – Database(s) Data Stores, collects the contextual data, LRS, other 4. Report & Analyze – Dashboards, Visualizations, Leaderboards, and create reports on the data summative and formative evaluation 5. Adapt to the Data – React - Create rules, take action, automate, adapt, predictive analysis, triggers and rules, big data stuff ©2018 5th Logic. All Rights Reserved Trajectory and goals will determine artifacts.
  6. 6. October 23, 2018 6 A Process Model For Learning Analytics ©2018 5th Logic. All Rights Reserved Yes, I went there. A/D D/I 3 4 5 A D D I E
  7. 7. October 23, 2018 7 1. Analysis & Design POTENTIAL ARTIFACTS • Current system designs and processes • Design to be system designs and processes • Learning Objectives • Profiles – xAPI, Other • Prototype or Proof of Principle • Research documentation, Case Studies, White papers, etc. • Set up source control ©2018 5th Logic. All Rights Reserved Understand current system and design “to be system”, analysis and planning, profiles, etc. • Develop a Sprint Plan, Develop a schedule/budget • Set up change management inquiry within the organization • Project Management Plan • Set Goals and Clear Success Criteria – “What does done mean?” • Decision Analysis & Resolution (DAR) • Estimating Methodologies • Focus Groups, More?
  8. 8. October 23, 2018 8 1. Analysis & Design ©2018 5th Logic. All Rights Reserved
  9. 9. October 23, 2018 9 2. Develop & Implement (Deploy) POTENTIAL ARTIFACTS • Data connectors, • set up databases, LRS, BI • Implement strategies for collecting digital learning and performance activity data • Add xAPI reporting to anything digital • Design new content with xAPI reporting ©2018 5th Logic. All Rights Reserved Follow the development plan, Iterate. • Source Code • Follow Sprint Plan • xAPI Profiles • Track deficiencies • Set up models
  10. 10. October 23, 2018 10 3. Acquire the Data POTENTIAL ARTIFACTS • A Conformant LRS or multiple • Data bases in organization • Share data with other departments for their reporting • Systems integration work to connect data sources • Artifacts Big Data Tools (e.g., Mongo DB, Google Cloud Platform, Elasticsearch) ©2018 5th Logic. All Rights Reserved Database(s) Data Stores, collects contextual activity stream data, LRS, Performance data, HRIS, other • Collect Deficiency data • More?
  11. 11. October 23, 2018 11 4. Report & Analyze POTENTIAL ARTIFACTS • What views or correlations of the data are needed to help reach goals? • Learner audience views • Educator/Instructor views • C-Level Stakeholder views • Artifacts Big Data Tools (e.g., Mongo DB, Google Cloud Platform, Elasticsearch) ©2018 5th Logic. All Rights Reserved Dashboards, Visualizations, Leaderboards, and create reports on the data summative and formative evaluation • More?
  12. 12. October 23, 2018 12 5. Adapt to the Data POTENTIAL ARTIFACTS • Manually change the content according to findings in step 4 • Automate tutoring • Recommendations engine • Use performance data to trigger training needs • Artifacts Big Data Tools (e.g., Mongo DB, Google Cloud Platform, Elasticsearch) ©2018 5th Logic. All Rights Reserved React - Create rules, take action, automate, adapt, predictive analysis, triggers and rules • More?
  13. 13. October 23, 2018 13 Thank you Published materials Learning Solutions Magazine https://www.learningsolutionsmag.com/authors/ 594/nick-washburn Association For Training and Development (ATD) https://www.td.org/Publications/Author.aspx?Ite mId=6BC586A46E8440BE969656516A50E7EF Publications https://www.linkedin.com/in/nick-washburn- 1b51177 ADL including downloadable research paper https://www.adlnet.gov/reaper/ ©2018 5th Logic. All Rights Reserved Nick Washburn Chief Product Officer 5th Logic, Inc 459 Herndon Parkway, Suite 8 Herndon, VA 20170 nwashburn@5thLogic.com IEEE LTSCI TAG Base xAPI Standard Work Group https://www.tagxapi.org/
  14. 14. www.5thLogic.com ©2018 5th Logic. All Rights Reserved

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