KU Center for Research on Learning  CAST  NASDSE
www.centerononlinelearning.org
Learning Analytics Symposium: iNACOL Virtual
School Symposium
Wednesday, October 24, 2012
12:30 PM – 5:00 PM
Hyatt Regency New Orleans, Lyric Room, 2nd Floor
Long Term Outcomes:
The Center is charged with 1) identifying the trends and issues in online education with respect to
students with disabilities, 2) developing and testing designs and practices that promise to make online
education more effective and accessible, and 3) conducting research that impacts the future of online
education for this population. Within the context of Universal Design for Learning, the Center expects
that its research and design efforts will improve outcomes for students with disabilities, and, by
extension, improve ways to address the variability inherent in all learners in online learning
environments.
Learning Analytics Symposium Goals:

Participants will explore and understand the ways in which online learning can personalize
instruction for diverse students (disability, ELL, ethnicity/culture, socioeconomic status, etc.) via
progress monitoring, data collection (individual, class, school) and analysis.

Participants will explore and discuss the ways in which digital management systems can monitor
student access, engagement and achievement, including the role of formative assessments to guide
modifications at the point of instruction and progress dashboards for real-time monitoring of
student achievement.

Participants will explore and identify online system data related to the context of online
instruction—virtual and blended; in class or at home, via fixed or mobile devices, and other
variables—that may significantly impact student learning outcomes.
The Symposium is designed to be a dialogue among Center researchers and staff, state and local
education personnel, representatives from Office of Special Education Programs and national education
organizations, all with an interest in online learning, efficacy and equity. The role of analytics derived
from academic achievement data, both at the individual student and aggregate levels, is newly-evolving,
and the Center would like to use the Symposium to review its preliminary findings and future directions
with stakeholders who have a shared interest in the type of data –based decision making offered by
online learning.
Through this, and other, dialogue opportunities the Center on Online Learning and Students with
Disabilities expects to produce valid, accurate and implementable research findings.
Learning Analytics Symposium Agenda
12:30PM – 12:45PM – Lunch

Lunch will be served in the room
12:45 PM - 1:00 PM – Greetings & Introductions

Introductions:
o Center on Online Learning and Students with Disabilities
 Jamie Basham (Kansas University) & Skip Stahl (CAST)
o Center on Emerging Technologies
 Todd Rose (CAST) & Sami Daley (CAST)
o Participants
1:00PM – 1:30PM – Overview and Expectations


Overview of our goals for the day
Introduction to today’s topic
1:30PM – 2:30PM –Group Discussions

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Learner variability
System design
Contextual variability
2:30PM – 3:00PM – Report out
3:00PM – 3:15PM – Break

Afternoon snack will be served
3:15PM – 3:45PM – Invited Presentation

Knovation
3:45PM – 4:15PM – Reflection on presentation
4:15PM – 4:45PM – Discussion reporting
4:45PM – 5:00PM – Wrap up
Initial Question Sets
A. Learner Variables
 What student information can be used to personalize instruction for diverse learners
(disability, ELL, ethnicity/culture, socioeconomic status, etc.) in online learning systems?
 What student usage “signals” could be correlated with student information to facilitate
personalization in online learning systems?
 What supports and scaffolds possible in online learning systems are essential to ensure the
success of diverse learners, and which aspects of their use should be tracked?
B. System Design Variables
 What design features of online learning systems are essential for addressing the needs of
diverse learners?
 What student usage or student customization data related to the use of these features is the
most important to track?
 Which type of data collection and analysis —individual or aggregate (class, school, district,
etc.) will prove most useful for monitoring the progress of diverse learners?
C. Contextual Variables
 What contextual variables relative to online learning impact the achievement/success of
diverse students?
 What specific information about the context of online learning is important to acquire?
 What correlations might emerge when the context of online learning is an inherent part of the
data collection process?
The Center is a partnership involving the University of Kansas Center for Research on Learning (KUCRL), the
Center for Applied Special Technology (CAST), and the National Association of State Directors of Special
Education (NASDSE). The Center is funded by the Office of Special Education Programs (OSEP) in the U.S.
Department of Education.
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