A Viable Process Model for Learning Analytics
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This document outlines a 5-step process model for learning analytics that includes analysis and design, development and implementation, acquiring data, reporting and analysis, and adapting to data. Each step produces artifacts to document decisions and justify the process. Following this model can help implement, grow, and sustain an effective learning analytics program.
A Viable Process Model for Learning Analytics
- 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. 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. October 23, 2018 3 Goal. Get to a planned ecosystem. ©2018 5th Logic. All Rights Reserved
- 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. 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. 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. 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. October 23, 2018 8 1. Analysis & Design ©2018 5th Logic. All Rights Reserved
- 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. 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. 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. 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. 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. www.5thLogic.com ©2018 5th Logic. All Rights Reserved