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A Qualitative Study Using Quantitative Data

A Qualitative Study Using Quantitative Data. Colleen Bye Keith White Ian Sorensen. Outcomes Assessment—Phase 1. Common Departmental Final Part multiple-choice/part free response Very subjective grading Large database from IRI Received periodically Analysis in Excel

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A Qualitative Study Using Quantitative Data

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  1. A Qualitative Study Using Quantitative Data Colleen Bye Keith White Ian Sorensen

  2. Outcomes Assessment—Phase 1 • Common Departmental Final • Part multiple-choice/part free response • Very subjective grading • Large database from IRI • Received periodically • Analysis in Excel • One/few people involved

  3. Outcomes Assessment—Phase 2 • Too dependent on IRI • Developed department measure • Submitted by each faculty member for every course every semester • Single page • < 10 minutes to fill out • Primary objectives: • Own our assessment • Encourage reflection

  4. Sample Form

  5. Department Data • Semester-by-semester snapshots • Pass/Success/Retention rates • Compare • Semesters • Courses • Other • Departmental Final • Last 3 years moved to multiple choice for standardization

  6. Sample Department Data

  7. Next Steps • Data incomplete • Longitudinal data • Sequence data • Instructor data • Scary!!! • IRB approved • Professionally

  8. Outcomes Assessment—Phase 3 • Created by colleague Ian Sorensen • PCP • passed original class and continued and passed next class in first attempt • Department average = 29% • PC-P • only considers students that passed original class and continued onto next class and passed • Department average = 61%

  9. Definitions Example • 30 enrolled in original class (e.g. Pre-Algebra) • 24 passed original class (e.g. Pre-Algebra) • 20 continued to next class (e.g. Beginning Algebra) • 18 passed next class (e.g. Beginning Algebra) • 18/30 = 60% PCP • 18/20 = 90% PC-P (change in denominator)

  10. Selection Process • ~26 full-time faculty • ~80 adjunct faculty • Subjective • Large n (> ~250) • Above average PCP • Above average PC-P

  11. Department Instructors

  12. Instructor Stats

  13. Qualitative Study Design • Process • Interviews • Identifying Themes • Observations • Preliminary/Ongoing

  14. Biographical Data • What is your educational background? • How long have you been teaching? Developmental math? • Did/do you teach K – 12? • Who was most influential in your development as a math teacher?

  15. General Philosophy • What is your philosophy of teaching? • What are your objectives in teaching developmental math?

  16. Philosophical Specifics • From data collected, a good percentage of your students have been successful in subsequent math courses. Why do you think that is the case? • What personal strengths do you find especially helpful in your teaching? • What do you think are the most important factors for a student to be successful working through the developmental math series?

  17. Practical Specifics • How do you structure a class? • Which element/activities would you say contribute most to the success of your students?

  18. Paul Axelrod’s Characteristics of Effective Teaching • Accessibility and Approachability • Fairness • Open-mindedness • Subject mastery and delivery • Enthusiasm • Humor • Knowledge and Inspiration Imparted Axelrod, Paul (2008). Student Perspective on Good Teaching: What History Reveals. Academic Matters: The Journal of Higher Education, February 2008, 24 – 27.

  19. Literature-Recommended Strategies

  20. Interview Sample Data

  21. Connections • All had minimum 10 years teaching • All mentioned the importance of creating a safe atmosphere where students could ask questions • Almost all emphasized need to build student confidence • Most characterized themselves as patient • 6 out of 7 started class with homework questions • None used power point to deliver lecture

  22. Incongruities • Homework – 4 paper and book / 3 online homework • 2 stopped at Bachelor Degrees (both in math) • Only 2 held Master’s Degree in Mathematics • Group Work – 3 had groups / 4 did not • Structure – 3 stated they were a traditional lecturer • Attendance – 3 required / 4 did not

  23. Observations • Had teachers select time to come in and observe class • Looked for themes identified in interview • Found specific techniques

  24. Knowledge is Power

  25. Knowledge is Power

  26. Knowledge is Power • Qualification verified • Gradebook • Homework Average • Daily Quiz Average • Chapter Test Average • Final Exam Score • Score needed to pass • Attendance percentage • Grade with Test Corrections • Grade w/o Test Corrections • Did they sign up for next class? • Did they pass next class?

  27. Board Work Innovation • Have groups of three to four come to the board. • One person rotates to next group for next problem. • Group leaders come to the board and race. • Quadratic Equation – One uses formula other completing square.

  28. Hard at Work

  29. Music and Math

  30. Future Work • Additional instructors • Course-by-course comparisons • Course delivery comparisons • Student surveys?

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