[Portfolio] Wednesday's (1/8/14) Webinar on Sakai and Learning Analytics

[Josh Baron]

Colleagues,

For those interested, I will be giving an informal talk tomorrow 
(Wednesday, January 8, 2014) on the Open Academic Analytics Initiative 
(OAAI) which was an initiative, supported by EDUCAUSE NGLC and the Bill 
and Melinda Gate Foundation, to develop and deploy an open source 
early-alert system using Sakai, with the goal of accurately predicting, 
early in the semester, which students are not likely to complete a course. 
 I will be presenting the work that was done on this project, our research 
results and some of the latest work that Marist and others are now engaged 
on related to learning analytics.

As one of the partners on this grant, Asahi Net International is helping 
host the event as part of its "Office Hours" initiative (THANKS!) but all 
are welcome to join.  More details and registration information is below.

I realize that this is a bit last minute notice (my fault) so if you 
cannot attend but are interested please let me know off list as we can 
work to schedule a second session if needed.

Thanks, Josh
p.s. I will be posting a note tomorrow morning regarding the Sakai T&L 
call which I would like to plan to have as well.


-----------------------------
Joshua Baron
Senior Academic Technology Officer
Marist College
Poughkeepsie, New York  12601
(845) 575-3623 (work)
Twitter: JoshBaron
----- Forwarded by Josh Baron/ADM/Marist on 01/07/2014 05:33 PM -----

From:   Jim Mezzanotte <jmezzanotte at anisakai.com>
To:     josh.baron at marist.edu, 
Date:   01/03/2014 07:31 AM
Subject:        Our Next Office Hours



















 

Please join us for our next Office Hours!

The topic for this session is Learning Analytics and Sakai. Our guest 
speaker will be Josh Baron, Senior Academic Technology Officer at ANI 
client Marist College and the Principal Investigator for the Open Academic 
Analytics Initiative (OAAI). This initiative has developed and deployed an 
open source early-alert system using Sakai, with the goal of accurately 
predicting, early in the semester, which students are not likely to 
complete a course. The webinar will focus on:
How a predictive model was developed using event log and gradebook data
Outcomes from multi-institutional pilots
Impact of intervention strategies on student success
Overview of current and future work with Sakai and learning analytics
You’ll be able to ask questions during the session, but we also encourage 
you to submit questions ahead of time to: jmezzanotte at anisakai.com

This session will be held Wednesday, January 8, 10 am to 11 am PST / 1 pm 
to 2 pm EST.

Register at: http://www2.anisakai.com/e/25612/19MvEGZ/58hss/48840211

After registering, you'll receive a confirmation email containing 
information about joining the webinar. System requirements:

PC-based attendees--Windows 7, Vista, XP or 2003 Server
Mac-based attendees--Mac OS X 10.5 or later
Mobile attendees--iPhone, iPad, Android phone/tablet







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