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Analyzing your SEEQs

Analyzing your SEEQs. A quantitative and qualitative approach. Presented by Kelley Engle HACC York April 19, 2011. Why analyze your SEEQs?. Can become an important part of a teaching portfolio A SEEQ Analysis can: Allow for self-reflection of teaching methods

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Analyzing your SEEQs

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  1. Analyzing your SEEQs A quantitative and qualitative approach Presented by Kelley Engle HACC York April 19, 2011

  2. Why analyze your SEEQs? • Can become an important part of a teaching portfolio • A SEEQ Analysis can: • Allow for self-reflection of teaching methods • Be used for hiring, tenure review and promotions • Show evidence of teaching effectiveness

  3. What is a teaching portfolio? • A collection of materials that document teaching performance • Presents a professor’s most significant teaching accomplishments • It is not an exhaustive compilation • All claims made in the portfolio should be supported by empirical evidence.

  4. What is a teaching portfolio? • An example of teaching e-portfolios: • Kelley Engle - Work in Progress • http://userpages.umbc.edu/~engke1 • Sample Teaching Portfolios • http://sunconference.utep.edu/CETaL/resources/portfolios/samples.htm#business

  5. Teaching Portfolio Resources • Texts: • Seldin, P, & Miller, J. E. (2008). The academic portfolio: a practical guide to documenting teaching, research, and service. San Francisco, CA: Jossey-Bass Inc Pub. • Seldin, P. (2004). The teaching portfolio: a practical guide to improved performance and promotion/tenure decisions. San Francisco, CA: Jossey-Bass Inc Pub.

  6. Teaching Portfolio Resources • Online: • Mues, F., & Sorcinelli, M.D. (2000). Preparing a teaching portfolio. The Center for Teaching, University of Massachusetts, Amherst, MA. • http://www.umass.edu/cft/publications/teachingportfolio.pdf • Vanderbilt University. (2011). Teaching portfolios. • http://cft.vanderbilt.edu/teaching-guides/reflecting/teaching-portfolios/

  7. SEEQ Analysis Quantitative • Collect data from current (and past) semester • Using Excel, create averages for groups based on sub-categories • Create line graphs for each sub-category • Self-reflect on teaching practices • What worked this semester and did not? • Compare with actual SEEQ data • Brainstorm for possible modifications Qualitative

  8. SEEQ Analysis: Quantitative • In order to facilitate this analysis, it is necessary to “compress” the data • An average is computed for each of the sub-categories listed on the SEEQ: • 1.       Learning • 2.       Enthusiasm • 3.       Organization • 4.       Group Interaction • 5.       Individual Rapport • 6.       Breadth • 7.       Examinations • 8.       Assignments • 9.       Workload Difficulty • 10.   Student and Course Characteristics • 11.   Overall

  9. SEEQ Analysis: Quantitative • Need to decide what scores to include for comparison: • College Wide • York All • Division (i.e., TECH All) • Discipline(i.e., CIS All) • Specific course (i.e., CIS105) • For my analysis, I have chosen to include College Wide and York All

  10. SEEQ Analysis: Quantitative • Using Excel, a matrix is created:

  11. SEEQ Analysis: Quantitative • A line chart is created

  12. SEEQ Analysis: Qualitative • There are two perspectives to analyze this chart qualitatively: • Longitudinally at my own scores • Compare with the baseline scores included for College Wide and York All.

  13. SEEQ Analysis: Longitudinal • Looking at the scores over time, perceived learning has decreased – Why? • Possible reasons: • Format and delivery changes to the course • Anomaly based on class attendance on day of SEEQ administration

  14. SEEQ Analysis: Comparison • Looking at the scores in comparison to the College Wide and York averages, perceived learning is lower • This is more difficult to analyze without feedback from other professors (particularly in same discipline)

  15. SEEQ Analysis: Brainstorming • In my average for Fall 2009, the M/W class gave low scores across the board which lowered the average • Looking at the attendance for that day, it was mostly A and high B students • What does this tell me?

  16. SEEQ Analysis: Brainstorming After looking at the MW class in more detail, I discovered the following: 1. The students who completed the SEEQ’s were expecting the highest grades (mostly A’s) 2. When looking at the attendance for the day the SEEQs were administered, the students present were mainly A/high B students. 3. They noted a marked dissatisfaction with the pace of the course stating that is was too slow.

  17. SEEQ Analysis: Brainstorming After looking at the MW class in more detail, I discovered the following: 1. The students who completed the SEEQ’s were expecting the highest grades (mostly A’s) 2. When looking at the attendance for the day the SEEQs were administered, the students present were mainly A/high B students 3. They noted a marked dissatisfaction with the pace of the course stating that is was too slow

  18. SEEQ Analysis: Brainstorming • My assessment of these evaluations is that A/high B students are frustrated with the course either because it is not challenging enough or the pace is too slow. •  How to best accommodate these students?

  19. SEEQ Analysis: Brainstorming • An inordinate amount of time is spent during class “hand-holding” students with no or limited PC skills • The majority of these “hand-held” students end up dropping and/or failing the class • This has been a recurring issue each semester

  20. SEEQ Analysis: Possible Solutions • A pre-requisite of CIS100 would alleviate this problem • Would require a placement test to allow students to test out • A pre-requisite needs to occur at the college-wide level

  21. SEEQ Analysis: Possible Solutions • For this spring semester, I have developed a 2-pronged remediation for this problem:  1. Develop and administer a CIS105 Readiness Questionnaire at the beginning of the semester 2. Each students initial CIS105 Readiness score will be compared with their final grade in the class. This will help in adjusting the heuristic for advising students in future semesters

  22. SEEQ Analysis: Follow-Up • Questionnaire was administered for Spring 2011 • None of the students surveyed met the heuristic of 5 “No” questions • May need to remove heuristic from questionnaire in order to reduce bias   • May need to reduce heuristic for recommending dropping the course

  23. SEEQ Analysis: Follow-Up • The final results of this analysis needs to be compiled and organized • This could be done through the use of an e-portfolio. • For more information on e-portfolios click here.

  24. End of Presentation Thank you for coming Questions? Comments?

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