Learning analytics - King’s College London - mootie13
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This document discusses finding the right balance of log file data when analyzing Moodle usage. It describes having too little data at first, then too much, and the need to find a better middle ground. The proposed solution involves using analytics tools to analyze geographical and tool usage trends at different levels of detail to help optimize the system without overwhelming users with data.
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Learning analytics - King’s College London - mootie13
- 1. A Goldilocks problem
- 2. A while ago, we had info…
- 4. Moodle logs
- 5. Log files
- 7. Finding a better balance
- 9. An analytics solution
- 11. Tool & action analysis
- 12. Two levels of data: a ‘dot notation’
- 13. Treemap of tools used
- 14. Drilling-down: actions within one tool
- 16. Is it just me?
- 17. Time to check data The End
- 18. A Goldilocks problem Jonathan P. San Diego Andreas Konstantinidis Stylianos Hatzipanagos Ian Barrett Ehsan Khan Philip Blake Tom Dore Mary Webb Panagiotis Fotaris Ahmed Eissa
Editor's Notes
- http://www.sxc.hu/photo/1410257
- Photo credit: http://commons.wikimedia.org/wiki/File:President_addresses_AMVETS_Convention_in_New_York_City_by_telephone._President_Kennedy,_assistants._White_House,_Oval..._-_NARA_-_194181.jpghttp://www.jfklibrary.org/Asset-Viewer/IjnZdEiNB0STI0U2nRC_Mg.aspx– it used to work, but took a lot of human input
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- Photo credit: http://www.sxc.hu/photo/1403
- Photo credit: http://www.sxc.hu/photo/1403
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- You may already be part-way on this pathIf you have been using Moodle 2, and have decided to use the ability to set conditions, then you will be aware that the system must be collecting information on who has viewed certain pages, done a particular task, or achieved a certain level in an assessment.So we are going to dig into this data and see if there is anything interesting for us, and if we can streamline the process of digging into it and find out what people want to get to.
- Photo credit: http://www.sxc.hu/photo/1410255
- Photo credit: http://www.sxc.hu/photo/1410257Our project’s goals:to provide feedback to teachers about learner activities in relation to the design and structure and contents of a moduleand also to provide feedback to students on how they are using the resources of a moduleIn order to achieve this, records of learning activities through Moodle analytics need to be translated into a form that teachers can easily interpret and that students can appreciate. Transforming logs into different forms of display such as a flowchart representing the sequence of ‘lesson pages’ visited by a student/group/cohort is possible by using available tools. So a main outcome of this project is to produce a visualisation feedback that can be easily interpreted by teachers and students.
- If the IP shows that the students are not on-campus, this could be of interest to:The instructor, in seeing patterns of jobs that study fits around, when you correlate the off-campus access with certain times. (There are privacy issues, naturally.)The university’s planners, who design the student spaces on-campus. Web developers and learning technologists: the IP address CAN distinguish between those who even on-campus connect on the wired network (KCL computers) or their own device (laptop, or tablet, or iPod). You may also be able to see that some are connecting over a phone’s connection, e.g. one we saw that starts with the digit 2 then a dot.The technical details of how we are doing thisGeoLib(containing geoipcity.inc and geoipregionvars.php), offline, we can visualize the location of the access.
- Using a ‘dot notation’We are making this information into 2 levels so that you see the first level which states that they're using a particular tool such as the forum then you see a second level which indicates that they can be read as writers within the forum; you can think of this as a kind of dot notation:forum.read or forum.writeUsage patternsYou can drill down. The first level is to say they are in the forum. The second level is to say they are viewing or posting.
- But hold on, will we be looking at the right things? A lot of people have looked at this so it must be of interest? But: academic staff will also be using the system, and this could potentially pollute your data: you think you have a lot of visitors but it's just your colleagues!Our solution: You can exclude the lecturers’ own names - or anyone's name. There’s a form you can insert these names in, and they’ll be excluded from the results. Insert them as a batch, separated by a delimiter, such as a semicolon. in that sense we are looking at the set that's left; and we can do this for students as well- if you wish to exclude a set of students from the result, due to your own unique requirements for that cohort.Filters for studentsWe filtered for James G in the Excel spreadsheet. But this can also be done through the web interface, by entering the student’s name. Or the students’ names, separated by a delimiter.We are seeking to identify the students who are in the tail of the class, due to not logging in; or not engaging in another defined way. This provides an early warning.Later, we hope we can correlate the same data with how they do in exams. To thus find out what correlates with success.OFFLINE (for now) = SECUREBy offline we mean it’s running on localhost. It could be run on the intranet. So there is no security risk in terms of that being run through another (3rd-party) website which shows the IP’s location; but we don’t know what they too glean from that information; or whether they store it.
- Photo credit: http://www.everystockphoto.com/photo.php?imageId=3018164&searchId=75d37c6cbf460947005c97e3f12906a9&npos=7We pick up a lot from our peers. We usually like to fit in.ExamplePoint out to the student that they are lurkers unlike the other students. They might not be aware of this themselves, if they think that everyone is doing what they are doing.You could point out to the teachers that their resources are being viewed; just not being commented on.
- Non-working students:Photo credit: http://www.publicdomainpictures.net/view-image.php?image=6290&picture=students-textingNewgrange:http://www.pdphoto.org/PictureDetail.php?mat=pdef&pg=5900http://www.pdphoto.org/PictureDetail.php?mat=pdef&pg=5898This system itself can do some of this for you but you may wish to go further as well. Examples of this could be the use of analytics to allow you to: Highlight anomalies: e.g. one wiki is used, but in another module, the wiki is not used. Then you can ask why.See that all the students are submitting just one day before the end of the course.Using the IP address, see if usage is coming from within the campus network; or from home. *(Using a free, open-source library )
- Photo credit: http://upload.wikimedia.org/wikipedia/commons/thumb/c/c0/Causeway-code_poet-4.jpg/1280px-Causeway-code_poet-4.jpgBackground photo credit: http://www.sxc.hu/photo/1410257
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