SAKAI and ANALYTICS A Case for collaboration in Analytics Space 2011 Sakai conference Los Angeles 1

Analytics for ATLAS Advanced Teaching, Learning and Scholarship  Where are we today  What are the possibilities  Low hanging fruits  Where do we want to be  How do we get there 2 2

Maturity Model Predictive Modeling Time Line Maturity Growth Infancy Querying and Reporting Scorecards and Dashboards 3 Sage

Data, Data, Data  All the data are available already  Data Acquisition  Data Transformation  Data Richness 4

Life Cycle Reporting 5 Courses and Classes Grades Development goals Donor Information State Grants Federal Loans School & Personal Information Aptitude Data Admissions Financial Aid RegistrarAlumni

Need for Business Intelligence  Data  Information  Knowledge  Actionable Knowledge  Strategic Recruiting  Advising  Intervention  Student Retention 6

Consumers of Information  Students  Faculty  Technologists Traction  Direction  Exploration 7

Usage Data  Participant Logins  Participant Summary  Page Hits 8

Portfolio Activities  Portfolio Data  Types of Content  Most accessed  Participant Activity 9

 Indicative Data from SIS  Admissions Data  Alumni Data 10 Data Richness 10

External Tagging  Aggregate Data from “Services”  “Recommend” Service  Assessment Matrices 11

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Institutional Key Performance Indicators  Qualitative Program Assessment  Multiple Entry Points  Gauging Student Engagements  Rolling Course Evaluation  Quantify Teaching Credentials  Retrospective Evaluation  Advisor Evaluation 13

Continued…  Cross Institutional Analysis  Co-curricular Activities  Student Life 14

15 Pentaho BI Oracle OBIEE NYU BI Tools 15

16 Contact Information Lucy Appert Director of Educational Technology, Liberal Studies Program Madan Dorairaj, PM 16