Learning Tracking Out of the LMS and Embracing Learning Analytics
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This document discusses learning analytics and tracking learning outside of learning management systems (LMS). It notes that most LMS features are unused and current analytics are just visualizations that provide little insight. True analytics can provide valuable insights from data, as demonstrated by companies like Deere that saved over $1 billion using analytics. Learning analytics is now possible through new learning record store (LRS) systems that can track more learning data. Web analytics packages can provide initial insights, and the document provides an example analysis of usage data that led to insights about content, usability, and player behavior.
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Learning Tracking Out of the LMS and Embracing Learning Analytics
- 1. Tracking Learning Outside of the LMS Embracing Learning Analytics
- 2. The LMS
- 3. What have you done for me lately?
- 4. 80% of features are never used
- 6. Much of it is junk
- 7. It’s just useless visualization on data
- 9. Analytics is just around the bend in learning...
- 10. It’s been around in business for a while...
- 11. Between 2002 and 2005, Deere & Company saved more than $1 billion by employing a new analytical tool to better optimize inventory.
- 12. It’s been around in web/marketing for a while...
- 13. Wikipedia has 45 web analytics packages in their “List of web analytics software”.
- 14. Where are we?
- 15. Image courtesy of Wikipedia, Natebailey Where are we?
- 16. Image courtesy of Wikipedia, Natebailey Where are we?
- 17. Why is this?
- 18. Analytic’s Purpose is Insight
- 19. This insight requires data. Lots of it.
- 20. Our cupboards are bare.
- 21. That’s about to change.
- 22. The LRS is all about data.
- 23. What will this bring?
- 24. But I don’t want to wait!!!
- 25. Get started with web analytic packages.
- 27. • 20-25% of visits last between 10 - 30 minutes • Users returned to the app in less than a day 76% of the time • When asked 67% of the users posted their score to the leaderboard • Games rules comprised <1% of the consumed content in game • The most commonly missed question was only missed ~2% of the time The Numbers
- 28. • 20-25% of visits last between 10 - 30 • Players were playing multiple levels minutes • They liked it enough to return • Users returned to the app in less than a day 76% of the time • When asked 67% of the • Users were competitive, wanted to users posted their score show off to the leaderboard • Games rules comprised • It was easy to use <1% of the consumed content in game • The most commonly missed question was • Players knew the information, though only missed ~2% of the time there was little commonality in what they didn’t know The Insights
- 29. • The content may exhaust itself • Players were playing multiple levels sooner than imagined • They liked it enough to return • We should ensure the experience y stays fresh • Our incentivization needs are less • Users were competitive, wanted to than we anticipated show off • Usability wasn’t as large a concern as • It was easy to use we thought, help content is not as important as thought • Players knew the information, though there was little commonality in what • We should re-examine the source they didn’t know content, and verify the instructional design was sound The Next Steps
- 30. The future is here, but it’s getting brighter.
Editor's Notes
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- Everyone is either going to or leaving an LMS... But for what? What does it brign them? Big promises? Does it delvier?\n
- Common rule of thumb for software usage.\n\nLMSes have become bloated... Do a LOT of things, but not really many of them are done well.\n
- You know the drill...\n\nWhat do you measure?\nStart, completion, score?\n\nWhat about operational data? Performance? Application in the real world?\n
- Even the reports and the data that is in the system is probably inadequate.\n\nIs it tied to other real world systems? Simulators? CRM, SCM, ERP? How do we know they are doing their job better?\n\n
- Ah, chart junk.\n\n3 minutes... Log into your LMS if you can find me the most useless report you can.\n
- Worthless data, provides no useful infomration, you gain no insight and therefore can offer no recommendations to your mgmt.\n
- It&#x2019;s pretty clear that we are on the verge of something big here.\n\nCloud services, more robust tracking tools, mobile performance support and on-the-go learning.\n\n\n
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- Davenport, Thomas H.; Harris, Jeanne G. (2007). Competing on analytics&#xA0;: the new science of winning. Boston, Mass.: Harvard Business School Press. ISBN&#xA0;978-1-4221-0332-6.\n\nAnalytics have been used in business since the time management exercises that were initiated by Frederick Winslow Taylor in the late 19th century. Henry Ford measured pacing of assembly line. But analytics began to command more attention in the late 1960s when computers were used in decision support systems. Since then, analytics have evolved with the development of enterprise resource planning (ERP) systems, data warehouses, and a wide variety of other hardware and software tools and applications.[3]\n[edit]\n\n\nBusiness analytics depends on sufficient volumes of high quality data. The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available.[3]\nPreviously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year. This type of data warehousing required a lot more storage space than it did speed. Now business analytics is becoming a tool that can influence the outcome of customer interactions.[4] When a specific customer type is considering a purchase, an analytics-enabled enterprise can modify the sales pitch to appeal to that consumer. This means the storage space for all that data must react extremely fast to provide the necessary data in real-time.\n\n
- Books written in 2001, 2002\n
- Google Analytics\nWeb Trends\nOmniture\n\n
- Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning.\nand its criticism:\n"I somewhat disagree with this definition - it serves well as an introductory concept if we use analytics as a support structure for existing education models. I think learning analytics - at an advanced and integrated implementation - can do away with pre-fab curriculum models". George Siemens, 2010.[2]\n"In the descriptions of learning analytics we talk about using data to "predict success". I've struggled with that as I pore over our databases. I've come to realize there are different views/levels of success." Mike Sharkey 2010.[3]\n\n
- http://mashable.com/2011/07/14/google-plus-growth-early-adopters/\nOnly 4-5 Learning Products have been identified as &#x201C;Learning Analytics&#x201D;.\n\nhttp://www.learningsolutionsmag.com/articles/1026/adding-learning-analytics-to-your-open-online-cloud-course-or-mooc-part-5\n\n
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- When was the last time you got &#x201C;insight&#x201D; from your reports in your LMS? Changed your behasvior? Did something different?\n
- Quite frankly we don&#x2019;t have much of it.\n\nStarted, finished, complete isn&#x2019;t a lot.\nEvena simple score isn&#x2019;t a lot.\n
- Quite frankly we don&#x2019;t have much of it.\n\nStarted, finished, complete isn&#x2019;t a lot.\nEvena simple score isn&#x2019;t a lot.\n
- Tin Can brings data. Lots of it.\n\nFrom many sources.\n\nAnecdote from mLearnCon - LMS vendor said that it&#x2019;s &#x201C;too much data&#x201D;... What would they do with it? Too many events. Too many statements.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n
- The LMS was a bit stingy in what it stored and recorded... Many of us really don&#x2019;t stress our systems too much.\n\nThe LRS, with it&#x2019;s JSON data and NoSQL database is made to accept massive amounts of transactions.\n