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Student Analytics

Can insights from breast cancer research be applied to improving student success? Explore how analytics can personalize resources to enhance students’ unique life circumstances for better academic outcomes.

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Student Analytics

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  1. Student Analytics Prescription for success Dwight Randle, Ph.D. Richland College CLARA Graduate 2016

  2. Breast Cancer in 2016* • Nearly 250,000 new cases • Over 40, 000 deaths • Caucasian women have the highest incidence • African American women have the highest mortality *Susan G. Komen for the Cure

  3. Breast Cancer Treatment • One size fits all treatment choices • Some are over treated while others are undertreated • Not all therapies work for all patients

  4. Personalize Breast Cancer Treatment • Treatment is customized the specific tumor • Genetics help target the right treatment for the right tumor

  5. Genetic Micro Arrays Columns are Patients Gene Turned On Rows are Genes Gene Turned Off No Information

  6. Cluster Analysis of Breast Tumors Breast Cancer is not a single disease. Pattern of genes turned on and off is important.

  7. Breast Cancer is 5 diseases genetically. Each respond to treatments differently. Better Survival Effective Treatments New Therapies New Leads

  8. The Question Can What We’ve Learned In Breast Cancer Be Applied To Student Success?

  9. The Modern Student School is one part of the complex and busy life of today’s student.

  10. The Modern Student Students learn that they need support too late …after the first exam.

  11. The Modern Student Students and faculty aren’t sure which support is best for each unique situation.

  12. Goal Use Analytics to Customize Resources Suited to the Student’s Unique Life Circumstance

  13. Study Design • IRB Approved, Deidentified Dataset. • 225 General Chemistry Students Surveyed in the First Week of Class. • Surveyed Socialization, Academic Preparedness & Academic Behaviors. • Supervised Cluster Analysis to Uncover Patterns that Predict Support Best Suited for each Student’s Life Circumstance.

  14. Impact of Tutoring in the Science Corner

  15. Preliminary Data Study Alone Has Friend in Class Course Grade Possible Response Red is Yes Green is No

  16. Next Steps • Correlate Interventions, Socialization, Academic Preparedness & Academic Behaviors with Course Grade • Cluster Analysis • Develop & Validate a Predictive Model • Deploy Prescriptive Trial & Validate

  17. Study Weaknesses • Currently, too few students to draw statistically relevant conclusions. • Self reporting of student behaviors • Will need several semesters to reach statistical significance

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