what we do

 

Data-driven decision-making entails systematically collecting and analyzing various types of data, including input, process, outcome, and satisfaction data, to guide the development, implementation, and ongoing assessment of courses, programs, and initiatives. Our office provides this support for internal decision-making in the College of Natural Sciences. External data requests should be directed to Institutional Reporting, Research, and Information Systems (IRRIS), which is the central point of contact for official campus statistics. 

 

There are four main ways we support data-driven decision-making in the College:  

 

SACS accreditation compliance, including:

 

  • Serving as a liaison between the CNS Dean's Office and the Provost's Office in all assessment matters
  • Consulting with CNS academic departments to design and execute assessment plans for undergraduate degree programs
  • Assisting CNS academic departments with the collection, analysis, and reporting of quantitative data on student learning outcomes

 

Data reporting and analysis for CNS undergraduate education degree plans and programs, including:

  • Accessing and summarizing data relevant to enrollment and curriculum management 
  • Analyzing data related to student performance in CNS courses and support/enrichment programs

Current examples include:

  • Tracking movement of students from gateway courses to advanced courses
  • Assessing relations among student pass/fail rates, placement test and other standardized test scores, and course assignments 
  • Examining the impact of first-year transition programs on student retention and grades

 

Technical assistance related to program design and evaluation, including:

  • Assisting in the design of objective and self-report measures that support the development and evaluation of curricula decisions and departmental/unit initiatives
  • Providing guidance on elements of program development and evaluation based on success metrics

Current examples include:

  • Designing assessment plans for curricular changes
  • Modeling the development and assessment of placement tests and course assignments  
  • Creating and managing surveys to measure student learning outcomes and attitudes

 

Development and support of automated processes for data retrieval and reporting for administrative functions, including:

  • Developing applications for automated electronic data collection and storage
  • Developing applications for automated electronic data retrieval and reporting

Current examples include:

  • Incorporating new data fields into current CNS web-based structures for reporting and storage
  • Implementing automatic downloads and displays of student performance data for programs and initiatives
  • Generating user friendly data access/summary tools customized for departmental administrators

  

how to reach us