xAPI Live - Data & Content Strategy
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This presentation by Learning Ninja's Sean Putman highlights the need to consider a data strategy before developing xAPI enabled learning content. Sean shares his experience with defining what needs to be tracked keeping value and end metrics in mind.
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xAPI Live - Data & Content Strategy
- 2. • Why? Why did people fail? Why?
- 4. Know Your Data What makes the data come into being? How hard is it to get the data I want/need? What’s my Data Supply Chain?
- 5. Data Supply Chain Activity Providers Systems architecture Data management, ownership, and accessibility Potential Data Integration concerns What’s “good enough”?
- 7. Content Strategy Content What activities can provide measurable data? Analysis What data can we (and should we) act on? Technical What data can we get from our systems?
- 12. • xAPI – Collecting more than just completions and test scores
- 14. Who are the Players?
- 15. Strategic Goals
- 16. Strategic Goals Informational Behavioral (micro) habits, individual professional development Behavioral (macro) large scale process or procedural change across BUs or across time
- 17. Obstacles
- 18. Data Stewardship What Lies Beneath? You’ll have to teach someone. When everybody’s in charge, nobody’s in charge.
- 19. What about data quality? Australian Bureau of Standards https://www.nss.gov.au/dataquality/aboutqualityframework.jsp
- 20. We’re ultimately interested in what is: observable measurable actionable
- 22. From Data to Analysis Available Relevant
- 23. What data am I likely to get?
- 24. What Do You Want to Know? Participation Performance
- 25. Participation Related • How are people using resources available? • How much time are they spending? • What elements/resources are proving useful? • What aspects of participation affect results? • What aspects of participation affect completions?
- 26. Performance Related • Are we teaching the right things? • How does course performance correspond to job performance? • Did X have the desired effect on Y?
Editor's Notes
- WE are going to talk about data in the intitial design process. And the use of data to assess the effectiveness of the learning intervention and provide for future design improvements.
- Pp 101 -105
- Needs analysis Gap analysis Strategic Road Map Phased by Ease/Feasibility/Need – Road Blocks / Anticipated Costs Road Map Scoring - Criteria Definition (for example: Ease, Importance, Impact/Benefit, Cost, Strategic Fit) - Scoring and Prioritization of Road Map Items
- We are looking for confirmation that the learner go what they needed to know. And we can ask the question
- We need to figure out what change means to us. If we were just looking to see how many people accessed something numbers are enough. When it comes to really seeing what behavior change our interventaion has made we need to figure out how we measure the change. So we need to figure out
- WE are looking at Collecting more than just completions and test scores, but if we are collecting completions and test scores, what does it actually mean. If I score a 90% on a quiz how does that affect my job performance? What path did I take to get to the quiz, does that affect my score. Why did I miss the last 10%? Was there a job role that scored better than others? Why?
- Data strategy
- L&D Owners L&D Customers Data Owners Data Customers
- Org/Institution (Strategic goals, Impact) L&D (Courses, Strategies)
- Examples: the data isn’t where it should be interoperability over time Change management
- Did the intervention actually work?
- Available? What’s relevant? Where do they intersect? Let’s start with what’s available…
- Kinds data you can get that can be built into evidence, information, tell stories…