This document summarizes a case study on the use of analytics for the Organic.Edunet learning portal. The portal provides educational resources on organic agriculture and went online in January 2010. The study examined how usage statistics changed after a series of training events were held. It found that traditional text searches remained most popular, more users visited but spent less time on each visit, and more bounced off the site after the events. However, many variables could be influencing portal usage. Further sophisticated analysis of existing statistics and additional data like user ratings was recommended.

1. Applying Analytics for a Learning Portal: the Organic.Edunet Case Study Vassilis Protonotarios, Nikos Palavitsinis , Nikos Manouselis Greek Research & Technology Network 1 st International Conference on Learning Analytics and Knowledge 2011

2. pre-intro Overwhelmed by LAK 2011 We used Google Analytics for this paper Originally deployed for reporting purposes METADATA : This presentation has 18 more slides (9 of them with pictures/figures)

3. about Organic.Edunet Completed eContentPlus project (10/2007 – 10/2010) funded with 2.5M € Main objective : Make learning content on Organic Agriculture and Agro-ecology available online, for a range of stakeholders. And : Develop educational scenarios to be used within schools & universities

4. Organic.Edunet Portal Went online on January 2010 (13 months) www.organic-edunet.eu 30.700 visits 146.100 page views 21.400 unique visitors 150 countries 10.900 resources 1.800 registered users 22.100 120.000 14.300 130 same 1.000 3 months ago

6. open days Validation events organized in all countries of the project partners, where users from institutions outside the project worked with the portal Predefined program for each “Open Day” & structured portal exercises which also allowed for unstructured interaction with the portal

7. research question How do the usage statistics both on the portal level but also on the individual user level, change, after a series of training events on the portal is organized? Do the users take full advantage of the portal functionalities we developed?

8. methodology Statistics that concern the Portal as a whole Visits per day, page views per day Visitors per day, origin of visits Bounces per day & most popular pages Statistics that concern each individual user Average time on portal, average time on page Pages per visit, depth of visit, user loyalty

9. methodology Study these statistics in three distinct periods Pre-Open Day, During & Post-Open Day Two groups of Open Days where organized one during April-May 2010 and another during August-September 2010 160 participants in 13 Open Days

10. timeline March 2010 May 2010 August 2010 September 2010 January 2010 November 2010 During-OD Post-OD

11. portal statistics

12. visit sources

13. popular pages 2 2 2 4 4 Tag search 17 14 14 9 6 Semantic Search 5 9 7 14 12 Browse 6 5 7 5 15 Educational Scenarios 3 27 18 30 30 How to S earch 5 9 73 49 61 51 Text-based S earch 81 1 36 118 138 102 Homepage Post-OD2 OD2 Post-OD1 OD1 Pre-OD Visits per day

14. depth of visit A deep visitor would open more pages in one visit than the average pages per visit of the portal for the same period of reference

15. visitor loyalty A loyal visitor is defined as the one coming back to the Organic.Edunet Portal more than once per week

16. some conclusions Traditional text-based search prevails over other means of searching, More users keep coming to the portal, spending less time on it, viewing less pages More users keep coming to the portal but also bouncing off of it

17. let’s take one step back TAKEN FROM: http://www.adventuresoutwest.com/climber-cartoon-web-style.jpg What? Go back down?

18. lots of variables to consider Language of the resources available? Seasonality (schools & universities) “ Black box” of each Open Day Cultural differences? Affiliation strategy of the project & press releases

19. open issues Deployment of a different approach on analytics that will allow in-depth statistics to be recorded? Sophisticated analysis of existing statistics? Also examine user ratings, comments, bookmarks in relation to these statistics How far can we go?

20. Thank you! 1 st International Conference on Learning Analytics and Knowledge 2011 [email_address] 30/5 – 3/6 www.jtelsummerschool.eu PhD students: 18/3/2011 PhD advisors: 31/3/2011