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Do the Data Support our Assumptions? Charles D. Dziuban Patsy D. Moskal University of Central Florida.

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Presentation on theme: "Do the Data Support our Assumptions? Charles D. Dziuban Patsy D. Moskal University of Central Florida."— Presentation transcript:

1 Do the Data Support our Assumptions? Charles D. Dziuban Patsy D. Moskal University of Central Florida

2 UCF terminology for courses utilizing web instruction “Web” Courses: delivered entirely over the Web, with no regular class meetings “Mixed-mode” Courses: some face-to-face instruction is replaced with web instruction so that on-campus time is reduced “Enhanced” Courses: delivered entirely in face-to-face mode, but with web enhancements

3 Distributed Learning Impact Evaluation StudentsFaculty Reactive behavior patterns Success Satisfaction Demographic profiles Retention Strategies for success Online programs Writing project model Large online classes Higher order evaluation models Student evaluation of instruction Theater Information fluency Alumni

4 Student Results

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

6 Students’ positive perceptions about blended learning Convenience Reduced Logistic Demands Increased Learning Flexibility Technology Enhanced Learning Reduced Opportunity Costs for Education

7 Students’ less positive perceptions about blended learning Reduced Face-to-Face Time Technology Problems Reduced Instructor Assistance Overwhelming Increased Workload Increased Opportunity Costs for Education

8 Student Generations

9 Some characteristics of the generations Matures (prior to 1946) Dedicated to a job they take on Respectful of authority Place duty before pleasure Baby boomers ( ) Live to work Generally optimistic Influence on policy & products Generation X ( ) Work to live Clear & consistent expectations Value contributing to the whole Millennials ( ) Live in the moment Expect immediacy of technology Earn money for immediate consumption

10 Students who were very satisfied by generation 55% 38% 26% Boomer n=328 Generation-X n=815 Millennial n=346 Percent

11 Better able to integrate technology into their learning by generation Percent 67% 48% 34% Boomer n=328 Generation-X n=815 Millennial n=346

12 Students who changed approach to learning because of Web by generation Percent 51% 37% 23% Boomer n=328 Generation-X n=815 Millennial n=346

13 College Level Academic Skills Test (CLAST) English scores n= 1,268n= 8,861n= 6,

14 Student Behavior Types

15 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

16 Resources Personality Emotional maturity Sophistication level Level of intellect Educational level Character development

17 A description of Long behavior types 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

18 A description of Long behavior traits 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

19 Distribution of Long Types and Traits for Fully Online Students AI 21% PI 18% AD 54% PD 7% 51% 75% 26% 30% (N=1,533)

20 Distribution of Long Types and Traits for Mixed-Mode Students AI 17% PI 23% AD 52% PD 8% 54% 76% 23% 32% (N=472)

21 Distribution of Long Types and Traits for Composition I Students AI 20% PI 23% AD 44% PD 14% 50% 53% 38% 40% (N=1,054)

22 Long Types and Traits for Web, Mixed- Mode, and General Education Students Web (N=1,533) Mixed-mode (N=472) Comp I (N=1,054) Aggressive Dependent 54%52%44% Passive Dependent 7%8%14% Compulsive74%76%53% Impulsive26%23%38% Types Traits

23 Long type by generation Baby Boomer Percent Gen-X Millennial Aggressive Independent n=312 Passive Independent n=256 Aggressive Dependent n=794 Passive Dependent n=108 23% 22% 17% 16% 20% 55% 54% 53% 4% 8% 10%

24 Students who were very satisfied by generation and Long type Baby Boomer Percent Gen-X Millennial Aggressive Independent n=118 Passive Independent n=88 Aggressive Dependent n=336 Passive Dependent n=33 53% 37% 24% 41% 37% 22% 79% 61% 40% 54% 33% 19%

25 Student Ratings

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

27 A comparison of excellent ratings by college unadjusted and adjusted for instructors satisfying Rule 1 CollegeUnadjusted %Adjusted % Arts & Sciences Business Education Engineering H&PA (N=441,758) (N=147,544)

28 A comparison of excellent ratings by course modality--unadjusted and adjusted for instructors satisfying Rule 1 F2F E M W ITV Course ModalityUnadjusted % Adjusted % N=709,285 N=235,745

29 Research Initiative for Teaching Effectiveness For more information contact: Dr. Chuck Dziuban (407) Dr. Patsy Moskal (407)


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