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Common Data Set
IR E-book
Index
Chapter 1 - Efficient IR
Chapter 2 - Data Communication
Chapter 3 - Common Data Set
Chapter 4 - Enrollment Data
Chapter 5 - Transfer Students
Chapter 6 - Qualitative Data
Chapter 7 - Student Success
Chapter 8 - NSSE Survey
Chapter 9 - Program Review
Chapter 10 - Accreditation
Chapter 11 - University Ranking
Chapter 12 - Sustainability
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Index
Chapter 1: Develop a Highly Efficient Institutional Research Office
Introduction
What is Efficiency?
Data Consistency
Data Extraction & Preparation
IR and IT Collaboration from IR’s Perspective
IR and IT Collaboration from IT’s Perspective
Data Reporting & Dissemination
Data Communication
Essential Skills for an Office
Closing Remarks
Chapter 2: Effective Data Communication Strategies
Introduction
Know Your Key Users (Strategy 1)
Keep Things Organized (Strategy 2)
Standardization and Transparency (Strategy 3)
Easy to Digest Information and Instant Help (Strategy 4)
Branding, Marketing, and the Power of Visuals (Strategy 5)
Data Dissemination
Involve Data Users (Strategy 6)
Closing Remarks
Chapter 3: Data Preparation and Usage for Common Data Set and External Surveys
Introduction
Consolidating Questions to Improve Efficiency
The Manual Procedure (Bottleneck Issue 1)
Inter-Office Communication (Bottleneck Issue 2)
Automating Data Processing and Calculation Methods
Closing Remarks
Chapter 4: Understanding Student Populations Using Enrollment Data Visualization Tools
Introduction
Decision Support System (DSS)
The Enrollment Trend Web App
Answering Transfer Enrollment Questions (Enrollment Trend App)
Answering Gender Questions (Enrollment Trend App)
Answering Race and Ethnicity Questions (Enrollment Trend App)
Answering STEM major Questions (Enrollment Trend App)
Answering Resident/Commuting Students Questions (Enrollment Trend App)
Answering Remote Learning Questions (Enrollment Trend App)
Answering Degree Pursuing Questions (Enrollment Trend App)
Enrollment by Program Web App
Unit Profile Web App
International Students Web App
The Course Web App
Closing Remarks
Answering Geographic Origin Questions (Enrollment Trend App)
Chapter 5: What Data Can Tell Us About Transfers
Introduction
Undergraduate Transfer Admission Web App
Enrollment Web App
Program Comparison - Enrollment Web App
Transfers Persistence
Transfers GPA
Degrees Awarded to Transfers
Time-to-Degree Web App
Transfers’ Student Engagement Data
Campus Experience Survey Web App
Closing Remarks
Chapter 6 - Qualitative Data & Analysis in Institutional Research
Introduction
Qualitative Data Web Apps
Qualitative Data Web Apps
Design the Qualitative Web Apps
Search Keyword Web App
Make Use of Qualitative Data
Closing Remarks
Chapter 7 - Student Success Measures
Introduction
MIRO’s Triple-A Data Strategy
Organizing Student Success Data
Closing Remarks
Making Data More Accurate (Applying Strategy 1)
Chapter 8 - NSSE 2020 at UH Manoa: From Record High Response Rate to Innovative NSSE Data Tools
Introduction
A Comprehensive NSSE Marketing Plan
Early Preparation (Timeline Phase 1)
Gear-up Month (Timeline Phase 2)
The Launch Day (Timeline Phase 3)
The Survey Open Window (Timeline Phase 4)
Response Rates Tracking Web Apps
Data Dissemination
Closing Remarks
Chapter 9 - IR Support for Academic Program Review
Introduction
From A Manual Process to a Digital Programming Software
Early Preparation (Timeline Phase 1)
Web App Filters
Web App Features and Design
Data Help Page
Closing Remarks
Chapter 10 - Institutional Research Support for Accreditation
Introduction
What is Accreditation?
Addressing Accreditation Standards
Addressing Core Commitments
Student Success Measures
NSSE
Special Programs
Qualitative Data
Earth Day Survey
Closing Remarks
Chapter 11 - Decode, Track, and Use Ranking Information
Introduction
Our View Towards the Ranking Phenomenon
Ranking Data Preparation
Cost Efficient Ways to Improve Ranking
Communicate Ranking Results
Improving Understanding about Ranking
Closing Remarks
Chapter 12 - UHM EARTH DAY SURVEY PRODUCT
Introduction
The Survey Design
2018 Earth Day Survey Findings
2020 & 2021 Earth Day Survey Findings
Making Data Useful
Closing Remarks
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