{"id":70,"date":"2012-01-15T05:01:29","date_gmt":"2012-01-15T05:01:29","guid":{"rendered":"https:\/\/harwoodben.com\/?p=70"},"modified":"2014-02-13T23:59:51","modified_gmt":"2014-02-13T23:59:51","slug":"notes-form-eli-webinar-learning-analytics","status":"publish","type":"post","link":"https:\/\/harwoodben.com\/?p=70","title":{"rendered":"ELI Webinar: Learning Analytics"},"content":{"rendered":"

It was very nice to tune into ELI’s webinar<\/a> on Learning Analytics. Here are some notes I took… I haven’t had a chance to wordsmith it. It’s been almost two weeks and I should just share and revisit the editing when I have time. Ok, poor form this time. But this gives me good cause to improve! \ud83d\ude42<\/p>\n

The focus was around building a predictive model. Second goal. Moodog – allow students to compare their progress with each other ((important for buy-in and justification of sharing personal info about each other.)) How original is the blog post? “original” is key. It allows for qualitative and quantitative analysis of work in high-volume classes. More real time\/implement changes in real time during the semester.<\/p>\n

The Actors > instructors, administrators (assessment folks), or even students themeselves…. Predictive functions = intervention? Continuous monitoring, keep track without constant vigilance. \u00a0\u00a0different from AA > preexisting tools . strategies > immediate classroom, data visualization, user-accessible.<\/p>\n

Resources:
\nPublication Simon recommended – I printed this out:
\nLearning Disposition and Transferable Competencies
\nhttp:\/\/projects.kmi.open.ac.uk\/hyperdiscourse\/docs\/SBS-RDC-review.pdf<\/a><\/p>\n

LAK 12 Conference site
\nhttp:\/\/lak12.sites.olt.ubc.ca\/<\/a><\/p>\n

Building a predictive model<\/p>\n

A. \u00a0\u00a0\u00a0\u00a0Mike Sharkey
\n###Debate is online monitoring- etc.<\/p>\n

Lots of data is great\u2026 but foundation to extract the information you need? Have to figure that out. Turn into valuable info, then put in front of someone who can do something about it.<\/p>\n

Capture all.\u00a0 See what you can do after.. complex shifting landscape of pointing whatever data output .. need skilled people who need to know which field need what kind of info. Working well at U Saskatcheawan\u2026
\nParallel processing of data. Get all the data, then write jobs afterwards to extract the jobs you did. Ie. Did student post something right after x, did they take this class afte rr this.. that\u2019s complex and tricky. Instead\u2026. Throw all data in there into a Hadoop Data center and make sense of it on the backend. 40 node dual..<\/p>\n

Hadoop, open source large data mining parallel processing dtat. HADOOP<\/p>\n

\u201cCan we predict if they will pass or fail this course?\u201d 1- fail to 10-super pass flying colors. Feed this score to academic counselors.<\/p>\n

So far, the method is:
\nBuilt different models
\nStrongest predictive coefficients. \u2013 identify recurring \u201ccooefficients\u201d and map to outcomes such as a 4 means, they are failing, advise the advisor.<\/p>\n

Hadoop.apache.org
\nLAK conference lak12.sites.olt.ubc.ca<\/p>\n

Will a predictive model be broadly applicable across all course design? Mike says, if you have a uniform curriculum, then yes, centralize curriculum yes. Haven\u2019t tested yet, but it\u2019s very encouraging. Humanities\/STEM\/ any differences.. haven\u2019t looked yet, just treating everything uniformly.
\nInfomatica and Tableau\u2026 microstrategy as business intelligence reporting tool. Tableau is key on data visualization, storyboarding. Tableau helps drill down and paint the right picture. It\u2019s a specialist tool., not an enterprise wide tool. Ben, check out Tableau. Mike is a \u00a0big fan but for small enterprise only. Would be great for us in smaller context. Mike is open for other questions.<\/p>\n

B. \u00a0\u00a0\u00a0\u00a0 Chris Brooks
\nUniversity of Saskatchewan
\nLooking at K12 b\/c it has a lot of \u201cuntapped potential\u201d
\nThe grey areas between research and production
\nA provable science? What\u2019s your bias first?
\nCapture things at a semantic level. The event at the semantic level is meaningful. So plan to and toward it. A little different take form Mike. * Make hypothesis explicit in your team so they can decide how to best collect data. \u00a0Institutional Will \u2013 show some small targeted gains in the short run and great buy in later on. Ethical to do so? Why yes, it\u2019s about evaluation. \u00a0But.. there have been abuses. Tracking too much, you might disadvantage students in real time environment.. or instances wher data could lead a teacher deny help to those who data may show are refusing to learn or put time in.. that\u2019s a problem, too. A lot of issues could be personal data, only show part of the picture. Dead tree learning. Social learning drinks.
\nQ from Malcom \u2013 ethical issue is a tough one per Chris. Students are being told about how they\u2019re being evaluated. It doesn\u2019t say when you email me, I\u2019ll see a graph of everything you\u2019re doing\u2026 that is,, in the syllabus. \u00a0Lots of data we don\u2019t\u2019 show instructors, b\/c we know we won\u2019t get approval. The commercial tools allows instructors to see more than the research ones that they build. ie blackboard analytics, maybe.
\nAnother Q \u00a0from MB: for someone getting started, any advice on getting started, if you have access to a lot of data, do like Mike said, and clear things \/build to data with queries. IF building a tool, then you have a lot of work. Get a course grain model going to deploy on time, so what\u2019s the institutional will? Development cycle in the summer, then wait 8 months after active use.. let that be guide. Think in terms of EVENTS. Not number of clicks. Think what is to capture what it means to log on and od something, model best practice use of students to what\u2019s being done during an event (ie. Completing homework in LMS)
\nChris is a super good guy\u2026<\/p>\n

Simon B. Shum from Open University
\nDispositions and Skills
\nSimon.buckinghamsum.net
\n@sbski
\nExchange dataset, and analytics, to accelerate rate of growth of innovations.
\nGreat analogy of being under knife of someone who can work well under pressure, not just takien a classs, iesurgeon<\/p>\n

Learning dispostions – > it\u2019s possible to model them formally and informally. Students fixed in intelligence, become brittle, that is under pressure, don\u2019t know how to cope very well. \u00a0So he\u2019s got an inventory of questionnaire items. (see screenshot)<\/p>\n

7 dimensions of \u201cLearning Power\u201d Awesome slide > take a look at it. From web to visual analytic. 7 dim. Spider diagram. A mirror for learner to have a conversation with a trained expert about their learning. How to embed this type of model in online learning platforms? ** to further personalize it.<\/p>\n

\u00b7 \u00a0\u00a0\u00a0\u00a0\u00a0Cohort data for each dimension, give a layout of dimensions in a group, what would the intervention strategy be? \u00a0And then be able to drill down on a specific dynamic..
\n***** EnquiryBlogger for WordPRess
\n******LearningEmergence.NET \u00a0<< check out this site, and also Simon\u2019s work>>>><>
\nDevelop categories that u assign dimensions for your online work<\/p>\n

Discourse Learning analytics
\nSocio-cultural discourse analysis.
\nWhere\u2019s the quality learning going on??? Skim through chat logs, etc. .. different methods<\/p>\n

KMi\u2019s Coher \u2013 web deliberation platform.. mapping out connection and roles of people who faciliatate a dialogue, like a \u201cBroker\u201d between tow ideas where there\u2019s a different understanding. Very cool!<\/p>\n

Others can run analytaics on others to look at contributions<\/p>\n

Thinking of students as cohorts and not just collection of individuals.
\nReal time analytics of students online, can it be tied to dimensions. If you never ask questions, does that put you as someone who is not the curious.. what does it mean to define analytics, to dig beneath the surface, to understand more about what\u2019s going on.
\nQ from MB. = the visual analytic spider diagram is one way to represent, the enquiry blogger gives you an analytic.. in teractive blog and v isualization. To classify your blogs as collaborative working relationshiops. Allows student or educator to know to see blog posts and meaning making\u2026 now imagine, meaning making beyond a blog, but across an entire system, a learner who understands their progress in a course, but also as a learner., metacognition, metacompetencies. **** Create self directed learners who will stretch themselves because they enjoy learning. That\u2019s what were trying to push as the benchmark of LA.
\nApril 11\/12, LA design for faculty and students.<\/p>\n","protected":false},"excerpt":{"rendered":"

It was very nice to tune into ELI’s webinar on Learning Analytics. Here are some notes I took… I haven’t had a chance to wordsmith it. It’s been almost two weeks and I should just share and revisit the editing … Continue reading →<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[100],"tags":[22,24,23,20],"class_list":["post-70","post","type-post","status-publish","format-standard","hentry","category-learning-analytics-2","tag-eli","tag-hadoop","tag-lak12","tag-learning-analytics"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack-related-posts":[{"id":61,"url":"https:\/\/harwoodben.com\/?p=61","url_meta":{"origin":70,"position":0},"title":"My Introduction to Learning Analytics","author":"Ben Harwood","date":"January 17, 2012","format":false,"excerpt":"Last Friday, I attended NERLA, the first north east regional learning analytics symposium. 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