Discussion 2
1 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
RS6539 Quantitative Qualitative Mixed-Methods Analysis
A Model of the project/research is always useful to give a descriptive view of what the project
is about. This was created in Microsoft Visio.
Community College Survey Data: The
Impact of Quantity and Quality on
Informed Decision- Making
Dataset Survey or Collector
RESPONDENTS
Business Research
Report
Business Research
Poster
Business Research Executive Summary
Business Research
PowerPoint Slide Deck
Statistical Engine
2 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
Once data has been accumulated and processed, the descriptive findings take root. It is this kind of
reporting analysis that ensure the research produces, yep, you guessed it again: Data-Driven,
Informed Decision-Making (DDIDM);
Composite 36-Item Reliability Analysis SIT Model Domain Questions/Variables: AP = Academic
Preparation; WE – Work Ethics; IS – Institutional Support
Stu
Mean
Stu
SD
Fac
Mean
Fac
SD
Academic Preparation Variables: Q1-12
1 Writing Assignments 3.217 0.742 3.290 0.797
2 Reading the textbook 3.328 0.723 3.452 0.619
3 Students getting feedback on assignments and tests 3.678 0.535 3.581 0.529
4 Having instructors as advisors 3.544 0.637 3.194 0.827
5 Using email to give help with class material 3.206 0.830 2.790 0.792
6 Instructors who challenge and encourage students 3.617 0.610 3.742 0.477
7 Designing labs with real-world exercises 3.589 0.596 3.581 0.560
8 Having online study guides to help students learn 3.111 0.865 2.677 0.919
9 Tests that actually cover the material taught 3.800 0.415 3.694 0.516
10 Giving students help during office hours 3.583 0.597 3.597 0.527
11 Giving students feedback about progress in a course 3.656 0.563 3.645 0.546
12 Designing a syllabus that is a learning guide 3.544 0.646 3.226 0.818
Work Ethics Variables: Q1-12 (13-24)
1(13) Showing up for class on time 3.689 0.562 3.710 0.458
2(14) Students take initiative to make up work due to absences 3.794 0.445 3.839 0.371
3(15) Attending class regularly 3.778 0.467 3.855 0.355
4(16) Appearance 3.344 0.765 2.903 0.900
5(17) Being a team player in group projects 3.600 0.565 3.452 0.563
6(18) Helping other students succeed 3.339 0.756 3.065 0.744
7(19) Students improving their organizational skills 3.644 0.556 3.500 0.536
8(20) Treating people with respect 3.794 0.419 3.565 0.562
9(21) Instructors giving students feedback on their work ethics 3.578 0.651 3.532 0.593
10(22) Hearing from business/community leaders about work ethics 3.133 0.868 3.048 0.858
11(23) Being an effective manager of time 3.650 0.534 3.645 0.515
12(24) Earning an A by unethical methods 2.356 1.319 1.581 1.095
Institutional Support Variables: Q1-12 (25-36)
1(25) Having problems resolved satisfactorily 3.561 0.581 3.403 0.527
2(26) Perceiving faculty/staff/admin as accessible and helpful 3.611 0.583 3.565 0.532
3(27) Feeling safe on campus to study 3.700 0.527 3.645 0.482
4(28) Getting help in finding meaningful employment 3.581 0.677 3.290 0.776
5(29) Permission to call any individual associated with the college 3.372 0.740 2.758 0.803
6(30) Online registration is available when needed 3.467 0.646 3.306 0.737
7(31) Being in classrooms that are clean 3.589 0.547 3.468 0.564
8(32) Understanding the mission of the college 3.335 0.742 2.710 0.930
9(33) Student organizations that enrich the learning experience 3.361 0.768 3.226 0.663
10(34) Feedback to administrators on how to improve the college 3.408 0.700 3.258 0.676
11(35) Having community services published on the web site 3.228 0.797 2.839 0.793
12(36) Resources for student support are reliably accessible 3.556 0.591 3.484 0.593
Notes:
1. (N = 265)
2. Scale: (1) Not Important, (2) Somewhat Important, (3) Important, and (4) Very Important
3. Cronbach’s Reliability Coefficient for Internal Consistency: .931
4. Kaiser-Meyer-Olkin Measure of Sampling Adequacy: KMO = .908
5. Bartlett’s Test of Sphericity: a. Approx. Chi-Square, 4358.660; b. df = 630; c. Sig. = .000
6. Correlation Matrix table identified 48.23% loading coefficients as ≥ 0.3000 (625/1296).
7. Principal Component Analysis was not processed in the composite scale; this action is reserved for further study.
3 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
Perceptual Benchmark Data: Students Compared to Faculty (Comparative Significance)
Item Students Faculty Stu
Tot
N
Fac
Tot
N
Sig.
Below
Avg
Avg Above
Avg
Below
Avg
Avg Above
Avg
Attendance 1.8% (7)
35.3% (138)
62.9% (246)
13.0% (18)
67.4% (93)
19.6% (27)
391 138 .000
Writing Ability 1.8% (7)
52.9% (207)
45.3% (177)
36.2% (50)
60.9% (84)
2.9% (4)
391 138 .000
Team Player 2.3% (9)
45.0% (176)
52.7% (206)
15.9% (22)
72.5% (100)
11.6% (16)
391 138 .000
Motivation to Succeed in
College
1.0% (4)
28.6% (112)
70.3% (275)
18.1% (25)
62.3% (86)
19.6% (27)
391 138 .000
Oral Presentations 13.3% (52)
62.7% (245)
24.0% (94)
26.8% (37)
66.7% (92)
6.5% (9)
391 138 .000
Producing Quality Work 0.8% (3)
43.7% (171)
55.5% (217)
25.4% (35)
70.3% (97)
4.3% (6)
391 138 .000
Computer Skills 5.1% (20)
46.5% (182)
48.3% (189)
21.0% (29)
60.9% (84)
18.1% (25)
391 138 .000
Success in High School 10.7% (42)
50.1% (196)
39.1% (153)
17.4% (24)
73.9% (102)
8.7% (12)
391 138 .000
Respect for Others 0.8% (3)
21.5% (84)
77.7% (304)
13.0% (18)
63.0% (87)
23.9% (33)
391 138 .000
Enjoy Learning New Things 0.5% (2)
26.3% (103)
73.1% (286)
15.2% (21)
64.5% (89)
20.3% (28)
391 138 .000
Reading Ability 2.3% (9)
40.4% (158)
57.3% (224)
28.3% (39)
63.8% (88)
8.0% (11)
391 138 .000
Time Management 12.0% (47)
54.0% (211)
34.0% (133)
44.9% (62)
47.8% (66)
7.2% (10)
391 138 .000
Math Skills 18.4% (72)
59.3% (232)
22.3% (87)
40.6% (56)
55.8% (77)
3.6% (5)
391 138 .000
Leadership 5.9% (23)
51.7% (202)
42.5% (166)
29.0% (40)
64.5% (89)
6.5% (9)
391 138 .000
Work Ethic 1.5% (6)
30.4% (119)
68.0% (266)
32.6% (45)
57.2% (79)
10.1% (14)
391 138 .000
4 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
Data-Driven, Informed Decision-Making (DDIDM)
Table 2: Comparison of Students and Faculty in Selected 15 Soft Skills (Δ Means) Strategic-Impact-Triad (SIT) Perceptions: Students Compared to Faculty
ITEM STUDENTS FACULTY Statistical Variance
Below
Avg Avg
Above
Avg
Below
Avg Avg
Above
Avg
Stu
Mean
Fac
Mean
Mean
Diff.
Attendance 1.8%
(7)
35.3%
(138)
62.9%
(246)
13.0%
(18)
67.4%
(93)
19.6%
(27) 2.61 2.07 0.55
Writing Ability 1.8%
(7)
52.9%
(207)
45.3%
(177)
36.2%
(50)
60.90%
(84)
2.9%
(4) 2.43 1.67 0.77
Team Player 2.3%
(9)
45.0%
(176)
52.7%
(206)
15.9%
(22)
72.5%
(100)
11.6%
(16) 2.50 1.96 0.55
Motivation to
Succeed in College
1.0%
(4)
28.6%
(112)
70.3%
(275)
18.1%
(25)
62.3%
(86)
19.6%
(27) 2.69 2.01 0.68
Oral Presentations 13.3%
(52)
62.7%
(245)
24.0%
(94)
26.8%
(37)
66.7%
(92)
6.6%
(9) 2.11 1.80 0.31
Producing
Quality Work
0.8%
(3)
43.7%
(171)
55.5%
(217)
25.4%
(35)
70.3%
(97)
4.3%
(6) 2.55 1.79 0.76
Computer Skills 5.1%
(20)
46.5%
(182)
48.3%
(189)
21.0%
(29)
60.9%
(84)
18.1%
(25) 2.43 1.97 0.46
Success in High
School
10.7%
(42)
50.1%
(196)
39.1%
(153)
17.4%
(24)
73.9%
(102)
8.7%
(12) 2.28 1.91 0.37
Respect for Others 0.8%
(3)
21.5%
(84)
77.7%
(304)
13.0%
(18)
63.0%
(87)
23.9%
(33) 2.77 2.11 0.66
Enjoy Learning
New Things
0.5%
(2)
26.3%
(103)
73.1%
(286)
15.2%
(21)
64.5%
(89)
20.3%
(28) 2.73 2.05 0.68
Reading Ability 2.3%
(9)
40.4%
(158)
57.3%
(224)
28.3%
(39)
63.8%
(88)
8.0%
(11) 2.55 1.80 0.75
Time Management 12.0%
(47)
54.0%
(211)
34.0%
(133)
44.9%
(62)
47.8%
(66)
7.2%
(10) 2.22 1.62 0.60
Math Skills 18.4%
(72)
59.3%
(232)
22.3%
(87)
40.6%
(56)
55.8%
(77)
3.6%
(5) 2.04 1.63 0.41
Leadership 5.9%
(23)
51.7%
(202)
42.5%
(166)
29.0%
(40)
64.5%
(89)
6.5%
(9) 2.37 1.78 0.59
Work Ethic 1.5%
(6)
30.4%
(119)
68.0%
(266)
32.6%
(45)
57.2%
(79)
10.1%
(14) 2.66 1.78 0.89
N = 548; * Not all respondents answered all items presented. NOTE: The rating scale is Below Avg (1), Avg (2), and Above
Avg (3). The Student Means of the ratings compared to the Faculty Mean ratings, consistently show that students rate themselves
higher in every category, with a low of 0.31 for Oral Presentations, and a high of 0.89 for Work Ethic. Translated this means
that students and faculty agree that students need improvement in Oral Presentations; by contrast, students by a margin of 0.89
perceived themselves to be in great shape in terms of a solid work ethic, where faculty tend to disagree almost an entire
percentage point in the rating scale. Source: Scott, K. (2008). Dissertation: Strategic Factors of Institutional Practice Impacting
Student Success in the Community College as Perceived by Students and Faculty: Academic Preparation, Work Ethics, and
Institutional Support; UMI Number: 3317344.
5 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
Descriptive Bar Chart and Analysis [Data-Driven, Informed Decision-Making (DDIDM)]
NOTES: (N = 649)
1. As reported in this response set, 72% indicated that they would be somewhat to very likely to
respond to “all questions” on a survey with “carefully thought-out responses”;
2. 63% reported that their completion-participation depended on the topic of the survey, as well
as the length of the survey;
3. “The thing that would motivate me would be my belief that the responses would actually
have an impact and effect change where needed. Another thing would be my belief that the
responses were truly anonymous.” (AFS121)
Rationale: Based on the data presented from the respondents (N=649), it is strongly suggested
that to improve—or to imply improvement in the quality and quantity of survey methodologies---
the design of the survey is tantamount to success in all facets. These variables include, but are not
limited to: a) carefully structured questions on the survey, applying peer review and statistical
analysis using a sample from the intended population, to include Confirmatory Factor Analysis
and/or Exploratory Factor Analysis to extract any potential duplications or variances which would
otherwise cause issues with central tendencies of the cohesion of the dataset (correlation
coefficient errors); b) conduct additional research on the 72% of respondents to assess the factors
that support indications that “they would be somewhat to very likely to respond to all questions on
(37/649) (216/649)
(248/649)
(245/649) (163/649)
5.70%
33.28%
38.21% 37.75%
25.12%
6 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
a survey with carefully thought-out responses.” The crux of this statement is to inform survey
designers of variables that may be used to improve the quality and quantity of the responses to
well-designed surveys, thus providing data-driven, informed decision making; c) 63% of the
participants indicated that the topic and length of the survey was of consideration in improving
quantity and quality of survey responses. The implication of this data is that survey designers must
be diligent to correlate survey topic to data collection to maximize interest in the survey, as well
as to promote maximum response rates by testing/retesting the length of the survey---in multiple
pilot testing to reduce variances (via Statistical Package of the Social Sciences – SPSS); and, d) to
address the issues noted by respondent AFS121. The quality and quantity of survey responses are
vital to the success of informed decision-making, and new and improved methodologies to protect
the anonymity of the respondents must be developed to ensure maximum secrecy of the responses
tendered and from whom those responses originated; moreover, for survey data to become change
agents within organizations of various sizes and types, outcomes must be reported back to the
respondent pool so that their input is measurable in terms of change within and throughout the
organization---as well, as how changes were considered but could not be accomplished due to
various circumstances in the operational outcomes of the organization (this is also viable feedback
to survey participants.)
In conclusion, when surveys are designed, it is highly suggested that any Preamble and
Disclaimers for surveys should include verbiage that summarizes this data to entice participants to
complete the survey at hand, and to do so with vigor and seriousness of intent. By inclusion, the
information presented in the beginning of the survey may very well be the catalyst that triggers the
open-minded and intentional of taking the necessary time to analyze each question on the survey
to produce the best set of data items possible.
7 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
Principal Component Analysis for Pilot Study Variables (Independent Analysis)
Academic Preparation Work Ethics Institutional Support
Factor Factor Factor
1 2 1 2 1 2
Q11 .730 Q6 .773 Q11 .787
Q10 .708 Q10 .770 Q10 .777
Q9 .684 Q4 .725 Q9 .775
Q7 .676 Q7 .720 Q8 .741
Q6 .655 Q9 .695 Q6 .638
Q12 .576 Q5 .659 Q12 .615 .404
Q4 .508 Q11 .627 .423 Q5 .553 .429
Q5 .452 .406 Q8 .604 Q1 .797
Q8 .427 .409 Q2 .824 Q2 .773
Q2 .780 Q3 .803 Q3 .764
Q1 .759 Q1 .711 Q4 .572
Q3 .586 Q12 (1) .408 -.456 Q7 .468 .488
1. Cronbach’s Reliability Coefficient: .821 (Q1-12);
** Q1-3: = .624 * Q4-12: = .810 ** Q4, 6-7,9-12: = .785 * Q1-3,5,8: = .674 2. Kaiser-Meyer-Olkin Measures
of Sampling Adequacy: KMO = .831 3. Bartlett’s Test of Sphericity:
Sig. = .000
1. Cronbach’s Reliability (Q1-12) Coefficient: .824 (Q1-11: 880) ** Q1-3: = .826 * Q4-11: = .870 ** Q4-7,8,9-10: = .856 * Q1-3, 11: = .807 2. Kaiser-Meyer-Olkin Measures of
Sampling Adequacy: KMO = .869 3. Bartlett’s Test of Sphericity:
Sig. = .000
1. Cronbach’s Reliability Coefficient: .901 (Q1-12)
** Q1-4: = .772 * Q5-12: = .884 ** Q6, 8-11: = .851 * Q1-5,7,12: = .835 2. Kaiser-Meyer-Olkin
Measures of Sampling Adequacy:
KMO = .907 3. Bartlett’s Test of Sphericity:
Sig. = .000
Notes: (** omitted cross-loadings for each factor)
1. Variable Q12 in the Work Ethics domain was reverse coded. Using all variables in the Work Ethics domain to
perform the Reliability Analysis resulted in Cronbach’s Alpha of .824; using only variables Q1 – Q11 in the Work
Ethics domain resulted in Cronbach’s Alpha of .880.
2. Academic Preparation: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with
Kaiser Normalization. a. Rotation converged in 3 iterations;
3. Work Ethics: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization. a. Rotation converged in 3 iterations;
4. Institutional Support: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser
Normalization. a. Rotation converged in 3 iterations;
5. Loadings on variables with values of < .4000 were not included in the analysis;
6. Bartlett’s test of Sphericity is significant at p < .05 for factor analysis to be considered appropriate (Tabachnick
& Fidell, 2007);
7. Kaiser-Meyer-Olkin (KMO) index range 0 to 1, with .6 suggested as minimum for good factor analysis
(Tabachnick & Fidell, 2007).
8. Correlation Matrix coefficient ratio for: a) Academic Preparation: 42% ≥ .3000 (60/144); b) Work Ethics: 72% ≥
.3000 (103/144); c) Institutional Support: 88.2% ≥ .3000 (127/144)
Data-Driven, Informed Decision-
Making (DDIDM)
8 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c
9 | D r . K e n n e t h E . S c o t t , R S 6 5 3 9 R e s e a r c h R e p o r t G u i d e a n d R u b r i c