A Look at Online Teaching and Learning at UCF

1. A Look at Online Teaching and Learning at UCF Charles D. Dziuban Patsy D. Moskal University of Central Florida

2. Levels of faculty development IDL 6543 Mixed-mode course to design, develop, & deliver M or W course ADL 5000 Online course modeling delivering existing M or W course Essentials Online course for faculty who want to supplement their F2F course without reducing any class time.

3. Growth of UCF online learning environments M+E courses Wcourses Enrollment Academic Year – Summer, Fall, Spring

4. The Evaluation

5. Principles that guide our evaluation • Evaluation must be objective. • Evaluation should conform to the culture of the institution. • Uncollected data cannot be analyzed. • Data do not equal information. • Qualitative and quantitative approaches must complement each other. • We must show an institutional impact. • Our results may not be generalized beyond UCF.

6. Students Success rates Attitudes Demographic inertia Withdrawal rates Strategies for success Reactive behavior patterns Distributed Learning Impact Evaluation components Faculty Online programs Real-time surveys Writing project model Modified instructional theories Student evaluation of instruction Large online classes

7. Student Results

8. What we have found regarding online students • The majority of students enrolled in fully online (W) courses are also enrolled in face-to-face courses, • The distribution of students by ethnicity is approximately the same for all modalities, • Fully online (W) courses consistently have more females than other modalities, • On the average, students enrolled in W courses are oldest, followed by those in M sections then face-to-face.

9. Student satisfaction in fully online and mixed-mode courses 44% Fully online (N = 1,526) 41% 39% 38% Mixed-mode (N = 485) 11% 9% 9% 5% 3% 1% Very Satisfied Neutral Very Unsatisfied Satisfied Unsatisfied

10. Success rates by modalitySpring 01 through Spring 03 F2F Total N= 139,444 students M W Percent

11. A segment model depicting success in course by college, gender, and modality College of Health & Public Affairs 93.0% n=31,124 Females Males 94.3% n=20,858 90.5% n=10,266 F2F W M F2F,W M 97.4% n=2,989 93.1% n=9,226 89.8% n=9,024 94.5% n=62,403 95.7% N=1,242

12. Withdrawal rates by modalitySpring 01 through Spring 03 F2F Total N= 147,194 students M W Percent

13. Student Behavior Types

14. Research on reactive behavior patterns • Theory of William A. Long, University of Mississippi • Ambivalence brings out behavior patterns • Provides a lens for how “types” react to different teaching styles

15. Resources • Personality • Emotional maturity • Sophistication level • Level of intellect • Educational level • Character development

16. Aggressive Independent high energy action-oriented not concerned with approval speaks out freely gets into confrontational situations Passive Independent low energy not concerned with approval prefers to work alone resists pressure from authority Aggressive Dependent high energy action-oriented concerned with approval rarely expresses negative feelings performs at or above ability Passive Dependent low energy concerned with approval highly sensitive to the feelings of others very compliant A description of Long behavior types

17. Phobic exaggerated fears of things often feels anxious often sees the negative side doesn’t take risks Compulsive highly organized neat, methodical worker perfectionist strongly motivated to finish tasks Impulsive explosive quick-tempered acts without thinking frank short attention span Hysteric dramatic and emotional more social than academic artistic or creative tends to overreact A description of Long behavior traits

18. Distribution of Long types and traits for fully online students 75% PD 7% 51% AD 54% AI 21% 30% 26% PI 18% (N=1,520) (N=1,437)

19. Distribution of Long types and traits for mixed-mode students 76% PD 8% 54% AI 17% AD 52% 32% 23% PI 23% (N=472)

20. Distribution of Long types and traits for Composition I students PD 14% 53% 50% 40% 38% AI 20% AD 44% PI 23% (N=1,054)

21. Long types and traits for Web, mixed-mode, and general education students Types Traits

22. Faculty Results

23. Time to develop course as compared with a comparable face-to-face section A lot more time More work A little more time 52% 77% About the same A little less time A lot less time 43% 21% Equal to or less than 5% 2% W n=56 M N=43 Modality

24. Time in weekly course administration activities as compared with a comparable face-to-face section A lot more time 43% More work A little more time 60% About the same A little less time 38% 20% A lot less time 15% 19% Equal to or less than 2% 4% W n=55 M N=42 Modality

25. Time in weekly course delivery activities as compared with a comparable face-to-face section A lot more time A little more time About the same A little less time More work 9% 5% A lot less time 15% 13% 28% 37% Equal to or less than 30% 29% 20% 15% W n=55 M N=42 Modality

26. Amount of interaction in Web classes compared to comparable F2F sections Increased Somewhat increased 45% More interaction 62% About the same Somewhat decreased 30% Decreased 16% Equal to or less than 13% 15% 8% 2% 3% 7% W n=55 M N=40 Modality

27. Quality of interaction in Web classes compared to comparable F2F sections Increased Somewhat increased About the same 30% 35% Better interaction Somewhat decreased Decreased 37% 33% Equal to or less than 22% 19% 9% 14% 2% W n=55 M N=43 Modality

28. Faculty satisfaction with their varying course modalities 38% Very satisfied 44% 49% Satisfied Positive Neutral 58% Unsatisfied 44% 38% Very unsatisfied Neutral or negative 7% 6% 5% 5% 7% W n=55 M N=43 F2F N=64 Modality

29. Faculty willingness to teach Web courses in the future Definitely Probably Probably not Definitely not Positive 81% 69% 16% 13% Neutral or negative 2% 10% 4% 6% W n=71 M N=53 Modality

30. Relationships of faculty satisfaction with class interaction and workload (TAU-b) W M (n=53) (n=38) Amount of interaction .39** .34* Quality of interaction .43** .51** Time to develop .16 .09 Time to administer .10 .01 Time to deliver .06 .10 *p<.05; ** p<.01

31. Student Ratings

32. Student Ratings by Modality Very Modality Excellent Good Good Fair Poor F2F 42.00 29.50 19.00 7.20 2.40 (N=628,623) E 44.00 29.10 17.40 6.90 2.60 (N=6,632) M 40.60 28.60 20.60 7.70 2.40 (N=11,450) W 55.40 25.20 12.10 4.90 2.50 (N=5,435)

33. A decision rule based on student evaluation responses and the probability of faculty receiving an overall rating of Excellent If... Excellent Very Good Good Fair Poor Facilitation of learning Communication of ideas Then... The probability of an overall rating of Excellent = .93 & The probability of an overall rating of Fair or Poor =.00

34. A comparison of excellent ratings by college unadjusted and adjusted for instructors satisfying Rule 1 College Unadjusted % Adjusted % Arts & Sciences41.6 92.4 Business 34.9 90.9 Education 56.8 94.8 Engineering 36.2 91.3 H&PA 46.1 93.9 (N=441,758) (N=147,544)

35. A comparison of excellent ratings by course modality--unadjusted and adjusted for instructors satisfying Rule 1 Course Modality Unadjusted % Adjusted % F2F 42.0 92.2 E 44.0 92.3 M 40.6 92.0 W 55.4 92.7 ITV 20.9 86.7 N=709,285 N=235,745

36. Research Initiative for Teaching Effectiveness

37. The transition from online to face-to-face courses Research Initiative for Teaching Effectiveness Distributed Learning Impact Evaluation

38. Research Initiative for Teaching Effectiveness For more information contact: Dr. Chuck Dziuban (407) 823-5478 dziuban@mail.ucf.edu Dr. Patsy Moskal (407) 823-0283 pdmoskal@mail.ucf.edu http://pegasus.cc.ucf.edu/~rite