This document summarizes the results of a survey given to teaching faculty at CSUEB regarding their preferences between semester and quarter academic calendar systems. The survey had a 54% response rate with 161 responses. Descriptive statistics show that 40-54% of faculty prefer quarters, 29-42% prefer semesters, and 12-23% have no preference. Additionally, 26-39% think quarters benefit students more, 33-46% think semesters benefit students more, and 23-34% have no preference. Hypothesis tests found significant differences in preferences between faculty ranks and between those who only taught quarters versus both quarters and semesters.
Data and assessment powerpoint presentation 2015Erica Zigelman
Presented for Datag in Albany, NY. This presentation is all about multiple types of data you may obtain within your classroom and how to assess your students.
Why Social Data Deserves More of Your BudgetFalcon Social
Get the webinar playback here: http://fal.cn/Ku_O
Learn how social intelligence can help you predict customer needs, and maximise customer lifetime value.
Data and assessment powerpoint presentation 2015Erica Zigelman
Presented for Datag in Albany, NY. This presentation is all about multiple types of data you may obtain within your classroom and how to assess your students.
Why Social Data Deserves More of Your BudgetFalcon Social
Get the webinar playback here: http://fal.cn/Ku_O
Learn how social intelligence can help you predict customer needs, and maximise customer lifetime value.
Using intelligent tutoring systems, virtual laboratories, simulations, and frequent opportunities for assessment and feedback, The Open Learning Initiative (OLI) builds open learning environments that support continuous improvement in teaching and learning.
One of the most powerful features of web-based learning environments is that we can embed assessment into, virtually all, instructional activities. As students interact with OLI environments, we collect real-time data of student work. We use this data to create four positive feedback loops:
• feedback to students
• feedback to instructors
• feedback to course designers
• feedback to learning science researchers
In this JumpStart Session, we demonstrate how OLI uses the web to deliver online instruction that instantiates course designs based on research and how the learning environments, in turn, support ongoing research. We will discuss the Community College Open Learning Initiative (CC-OLI) and how faculty and colleges across the country can participate in CC-OLI and the connection between CC-OLI and Washington State’s Open Course Library project.
Using intelligent tutoring systems, virtual laboratories, simulations, and frequent opportunities for assessment and feedback, The Open Learning Initiative (OLI) builds open learning environments that support continuous improvement in teaching and learning.
One of the most powerful features of web-based learning environments is that we can embed assessment into, virtually all, instructional activities. As students interact with OLI environments, we collect real-time data of student work. We use this data to create four positive feedback loops:
• feedback to students
• feedback to instructors
• feedback to course designers
• feedback to learning science researchers
In this JumpStart Session, we demonstrate how OLI uses the web to deliver online instruction that instantiates course designs based on research and how the learning environments, in turn, support ongoing research. We will discuss the Community College Open Learning Initiative (CC-OLI) and how faculty and colleges across the country can participate in CC-OLI and the connection between CC-OLI and Washington State’s Open Course Library project.
SCS 200 Research Investigation Progress Check 1 Guidelines and.docxbagotjesusa
SCS 200 Research Investigation Progress Check 1 Guidelines and Rubric
Overview: Throughout Theme: Exploring Social Science Issues, you have been guided through work on Project One (a research investigation), which you will
continue to work on in Theme: Performing the Research Investigation and Theme: Tailoring the Message to an Audience and will formally submit to your
instructor at the end of Week 5. This assignment provides you with an important opportunity to get valuable instructor feedback on the progress you are making
and to ensure you are on the right track for your later submission.
Prompt: Throughout Theme: Exploring Social Science Issues, you have explored social science issues for further investigation and examined social science
principles that relate to issues of interest to you. Specifically, in this assignment, you will submit the Project One elements listed below for review by your
instructor.
In Theme: Exploring Social Science Issues, learning block 2-2 (page 4), you began working
on the following section of the prompt:
I. Introduction
A. Describe the issue in the social sciences that you have selected to
investigate. Why is this issue significant?
In Theme: Exploring Social Science Issues, learning block 2-3 (page 2), you completed the
following work:
II. Body
A. Identify the social science principles that apply to your issue. In other
words, which principles of social science apply to the issue you selected?
B. Explain how the principles you identified apply to your issue. In other
words, how are the social science principles you identified relevant to your
issue?
Please note that the numbering included above directly aligns with the numbering of these elements as they are presented in the Project One Guidelines and
Rubric document.
https://snhu.mindedgeonline.com/content.php?cid=92549
https://snhu.mindedgeonline.com/content.php?cid=92549
Rubric
Guidelines for Submission: Submit your progress check assignment as a Microsoft Word document with double spacing, 12-point Times New Roman font, and
one-inch margins. Your submission should be at least 1 page in length. Any citations should be formatted according to APA style.
Critical Elements Proficient (100%) Needs Improvement (80%) Not Evident (0%) Value
Introduction: Issue Describes selected issue in social
sciences and its significance,
reflecting an initial understanding of
the issue and the social sciences
Describes selected issue in social
sciences and its significance, but with
gaps in detail or clarity
Does not describe selected issue in
social sciences or its significance
30
Body: Identify Principles Identifies social science principles that
apply to issue, citing sources
Identifies social science principles that
apply to issue, but with gaps in
accuracy or citation
Does not identify social science
principles that apply to issue
30
Body: Explain Principles Explains how identified principles
apply to issue, .
Week 6 DQ1. What is your research questionIs there a differen.docxcockekeshia
Week 6 DQ
1. What is your research question?
Is there a difference between the math utility of a male and a female?
2. What is the null hypothesis for your question?
Hn There is no difference in the math utility between male and female.
Alternative hypotheses can also be created in the case the null hypothesis is proven incorrect. Two alternative hypotheses are:
Ha1 Feales have a higher math utility.
Ha2 Males have a higher math utility.
3. What research design would align with this question?
According to Frankfort-Nachmias and Leon-Guerrero (2015) a descriptive research design would be best for this type of study.
4. What comparison of means test was used to answer the question (be sure to defend the use of the test using the article you found in your search)?
The independent-samples T test was used to analyze the means for this data.
5. What dependent variable was used and how is it measured?
The dependent variable is the student’s math utility. It is measured from -3.51 to 1.31(University high school longitudinal study dataset. (2009).
6. What independent variable is used and how is it measured?
Either male (1) of female (2) (University high school longitudinal study dataset. (2009).
7. If you found significance, what is the strength of the effect?
The significance was 0.0000. This is much better than the standard of .05 significance as outlined by Frankfort-Nachmias and Leon-Guerrero (2015).
8. Identify your research question and explain your results for a lay audience, what is the answer to your research question?
My research question was “Is there a difference between the math utility of a male and a female?” Based on the analysis of the means (or average) through testing using the independent-samples T test there was no measurable difference between the math utility of male or females. This leads us to accept the null hypothesis of “There is no difference in the math utility between male and female” as true.
Group Statistics
T1 Student's sex
N
Mean
Std. Deviation
Std. Error Mean
T1 Scale of student's mathematics utility
Male
9453
.0140
1.01962
.01049
Female
9349
-.0481
.97291
.01006
Independent Samples Test
Levene's Test for Equality of Variances
t-test for Equality of Means
F
Sig.
t
df
Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the Difference
Lower
Upper
T1 Scale of student's mathematics utility
Equal variances assumed
17.400
.000
4.276
18800
.000
.06216
.01454
.03367
.09066
Equal variances not assumed
4.277
18775.932
.000
.06216
.01453
.03367
.09065
University high school longitudinal study dataset. (2009).
References
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications.
University high school longitudinal study dataset. (2009). Retrieved from class.waldenu.edu
The t Test for Related Samples
The t Test for Related Samples
Program Transcript
MAT.
Community Teaching Plan Teaching Experience Paper 1Unsatisf.docxdonnajames55
Community Teaching Plan: Teaching Experience Paper
1
Unsatisfactory
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Less than Satisfactory
75.00%
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Satisfactory
83.00%
4
Good
94.00%
5
Excellent
100.00%
80.0 %Content
30.0 %Comprehensive Summary of Teaching Plan With Epidemiological Rationale for Topic
Summary of community teaching plan is not identified or missing.
Summary of community teaching plan is incomplete.
Summary of community teaching plan is offered but some elements are vague.
Focus of community teaching is clear with a detailed summary of each component. Rationale is not provided.
Focus of community teaching is clear, consistent with Functional Health Patterns (FHP) assessment findings and supported by explanation of epidemiological rationale.
50.0 %Evaluation of Teaching Experience With Discussion of Community Response to Teaching Provided. Areas of Strength and Areas of Improvement Described
Evaluation of teaching experience is omitted or incomplete.
Evaluation of teaching experience is unclear and/or discussion of community response to teaching is missing.
Evaluation of teaching experience is provided with a brief discussion of community response to teaching.
A detailed evaluation of teaching experience with discussion of community response to teaching and areas of strength/improvement is provided.
Comprehensive evaluation of teaching experience with discussion of community response provided along with a detailed description of barriers and strategies to overcome barriers is provided.
15.0 %Organization and Effectiveness
5.0 %Thesis Development and Purpose
Paper lacks any discernible overall purpose or organizing claim.
Thesis is insufficiently developed and/or vague; purpose is not clear.
Thesis is apparent and appropriate to purpose.
Thesis is clear and forecasts the development of the paper. It is descriptive and reflective of the arguments and appropriate to the purpose.
Thesis is comprehensive; contained within the thesis is the essence of the paper. Thesis statement makes the purpose of the paper clear.
5.0 %Paragraph Development and Transitions
Paragraphs and transitions consistently lack unity and coherence. No apparent connections between paragraphs are established. Transitions are inappropriate to purpose and scope. Organization is disjointed.
Some paragraphs and transitions may lack logical progression of ideas, unity, coherence, and/or cohesiveness. Some degree of organization is evident.
Paragraphs are generally competent, but ideas may show some inconsistency in organization and/or in their relationships to each other.
A logical progression of ideas between paragraphs is apparent. Paragraphs exhibit a unity, coherence, and cohesiveness. Topic sentences and concluding remarks are appropriate to purpose.
There is a sophisticated construction of paragraphs and transitions. Ideas progress and relate to each other. Paragraph and transition construction guide the reader. Paragraph structure is seamless.
5.0 %Mechanics of Writing (includes spelling.
Traditional Student Evaluations of Teaching (SETs) are feedback forms returned by students at the close of a course. Institutions intend that data from these forms be used to improve the quality of teaching and as an assessment of quality of teaching for deciding faculty promotion and tenure decisions. Although it is recognized that students can offer valuable information on the appropriateness of teaching quality, it has also been recognized that these traditional SETs are likely to have negative effects on the quality of teaching. These negative criticisms are quite extensive and range from "dumbing down" of courses to restrictions on academic freedom. One patently obvious criticism is that the information given by one group of students at the end of a course cannot be used to improve the teaching on that course. Similarly, it can only be useful to future students to the extent that future groups of students are similar to the feedback group and to the extent that the course and teaching remain similar. However, courses and teaching methods hopefully evolve and the constituent subgroups of a student cohort can change considerably from one year to the next.
This paper introduces an alternative method of allowing students to assess the quality of teaching that circumvents many of the problems associated with traditional SETs. In particular it allows feedback to be used for optimizing teaching quality during the course for the whole class, for individuals or for identified subgroups of students within the whole group. The feedback is quick and cheap to process - as it requires only eight ratings from each course member.
The paper outlines the method and the theory behind it. These three objectives - kills, understanding and attitudes - are emphasized to a determined amount in the teaching and assessment of the course. Feedback forms used during the course give data on the lecturer’s and students’ expectations for change in these objectives. This data allows for calculations of the alignment between the lecture’s and the students’ expectations for change. The theory is that academic success is maximized when students and their lecture are working towards the same changes. The theory is re-validated with each course by correlations of alignments with results, which show that in-course alignment predicts postcourse academic success. This paper describes how the data are also used during the course to determine the changes that will best align in-course student/lecture expectations. The educational importance of this alignment method is that it offers a cheap, efficient and effective alternative to the widespread problematic use of traditional SETs for quality control of teaching in tertiary institutions.
Source: https://ebookschoice.com/skills-understanding-and-attitudes/
TESTA at UNSW, Sean Brawley, TESTA Summit 16 Sept 2013Tansy Jessop
TESTA is Faculty of Arts and Social Sciences. Efficiency in Assessment and Feedback. Data-driven approach to fast-tracking quality assurance to make responsive changes to assessment.
TESTA at UNSW, Sean Brawley, TESTA Summit 16 Sept 2013
STAT 3510 Presentation
1. STAT 3510 Final Project
CSUEB Fall Teaching Faculty and Academic Calendars
2. Motivation for our project
Due to the fact that CSUEB is changing from a quarter system to a semester system,
we wanted to get a real world sampling of the teaching faculties thoughts on
which is a better academic calendar. We thought it would be easier to get a true
Simple Random Sample from this population.
We asked them which system they individually prefer and which system they
thought benefitted students more.
They were given three choices: semesters, quarters, and no preference.
3. Methods/Procedure
Our sampling frame was the fall teaching faculty at CSUEB, a total of 804.
We used an online random name generator to sample 300 of them.
We sent out an 8 question survey to their CSUEB e-mail account. Two
separate e-mails were sent out over the course of two weeks.
We received 163 responses back for a response rate of 54.3%, we discarded
two of the responses due to completely unusable data, so our final sample size
was 161 respondents.
4. Descriptive Statistics
What Academic Calendar do Teaching Faculty Prefer
1. Semester System
The 95% confidence interval for teaching faculty who prefer semester system is (0.288, 0.420)
Thus, we are 95 % confident that between 28.8% and 42% teaching faculty prefer semester system.
2. Quarter System
The 95% confidence interval for teaching faculty who prefer quarter system is (0.403, 0.541)
Therefore, we are 95% confident that between 40.3% and 54.1% teaching faculty prefer quarter system.
3. No preference
The 95% confidence interval for teaching faculty who have no preference of systems is (0.121, 0.227)
Therefore, we are 95% confident that between 12.1% and 22.7% teaching faculty have no preference on specific system either
5. Descriptive Statistics
Which Benefits Students : Quarter? Semester? No Preference?
1. Semester System
The 95 % C. I for teaching faculty who said that the semester system benefits students more is (0.325,0.457)
Therefore, we are 95% confident that between 32.5 % and 45.7% teaching faculty say that semester system benefits students
more.
2. Quarter System
The 95 % C. I for teaching faculty who said that the quarter system benefits students more is (0.258,0.386)
Thus, we are 95 % confident that between 25.8% and 38.6% of the teaching faculty say that quarter system benefits students
more.
3. No Preference
The 95 % C. I for teaching faculty who had no preference for which system benefits students more is (0.230,0.340)
Thus, we are 95% confident that between 23% and 34% teaching faculty have no preference which system will benefit students.
6. Hypothesis(Likelihood of response by college)
Ho:
When looked at by college, there is no significant statistical difference in the
probability of getting a response.
Ha:
There is at least one college that is more or less likely to respond to our survey.
7. College Count of potential Response
#s
Count of actual
responses
response
percentage
Business and
Economics
36 18 0.5
Education and Allied
Studies
35 19 0.542857143
Letters, Arts and
Social Sciences
127 78 0.614173228
Science 102 49 0.480392157
Grand Total 300 164 0.546666667
Table of Values
8. Results
Average response rate is about 53% with a sample standard deviation of about 6%.
It is 95% confident that response rates will be within 44% and 62%.
All of the response rates recorded are within this range so don’t reject Ho.
In other words each college is equally likely to respond to the college or, despite
Statistics teachers being counted under Math and thus Science they are no more likely
to help out Statistic students than any other teacher.
9. Hypothesis (College Within CSUEB)
Ho: The college within CSUEB that teaching
faculty works in makes no difference as to
what academic calendar they prefer.
Ha: The college within CSUEB that teaching
faculty works in makes a difference as to
what academic calendar they prefer.
H0: The college within CSUEB that teaching
faculty works in makes no difference as to
what academic calendar they think is more
beneficial to the students.
Ha: The college within CSUEB that teaching
faculty works in makes a difference as to what
academic calendar they think is more
beneficial to the students.
10. No preference Quarter Semester Total
College of Business and
Economics
4
3.019
0.31905
8
8.609
0.04304
6
6.373
0.02179
18
College of Education and
Allied Studies
4
3.019
0.31905
6
8.609
0.79051
8
6.373
0.41556
18
College of Letter, Arts, and
Social Sciences
11
12.745
0.23901
39
36.348
0.19352
26
26.907
0.03056
76
College of Science 8
8.217
0.00575
24
23.435
0.01363
17
17.348
0.00697
49
Total 27 77 57 161
Cell contents: Count
Expected count
Contribution to Chi-Square
Pearson Chi-Square = 3.684. DF = 6, P-Value = 0.719
Chi Square Test: CSUEB College, Benefits the Teacher
11. No preference Quarter Semester Total
College of Business and
Economics
5
5.143
0.00397
6
5.814
0.00597
7
7.304
0.00027
18
College of Education and
Allied Studies
7
5.143
0.67063
4
5.814
0.56580
7
7.043
0.00027
18
College of Letters, Arts, and
Social Science
23
21.714
0.07613
21
24.547
0.51242
32
29.739
0.17188
76
College of Science 11
14.000
0.64286
21
15.826
1.69147
17
19.174
0.24648
39
Total 46 52 63 161
Chi Square Test: CSUEB College, Benefits for the Students
Cell contents: Count
Expected count
Contribution to Chi-square
Pearson Chi-square = 5.711, DF = 6, P-Value = 0.456
12. Results
There doesn’t seem to be a difference
between the college that the
teaching faculty works in and
teachers and students benefits in
academic calendar.
Therefore we fail to reject the null
hypothesis Ho in both situations.
Teaching faculty had about 20 more responses
for quarter in terms of benefits for the
teachers, and 11 more think that quarter
would benefit the students
If we had just semester and quarter, and took
out the no preference answer, maybe the
data would have changed and caused a
preference towards one or the other.
Especially, in the college and benefits students
test because there was 46 total no preference
responses
13. Hypothesis (Teaching Title)
Ho:The title and rank of the teaching
faculty at CSUEB makes no difference
as to what system they prefer
Ha: The title and rank of the teaching
faculty at CSUEB makes a difference in
what system they prefer
Ho: The title and rank of the teaching
faculty at CSUEB makes no difference
in what system they think is beneficial
to the students
Ha: The title and rank of the teaching
faculty at CSUEB makes a difference in
what system they think is beneficial to
the students
14. Teaching Title vs Personal Preference
Chi-Sq=23.046, DF=6 P-Value=0.001, Reject Null Hypothesis
Full professor Associate
professor
Assistant
Professor
Adjunct
Professor
Total
Quarter 17
12.27
1.820
9
8.50
0.030
2
10.86
7.226
48
44.37
0.297
76
Semester 4
9.20
2.943
7
6.37
0.062
17
8.14
9.634
29
33.28
0.550
57
No Preference 5
4.52
0.051
2
3.313
0.408
4
4.00
17
16.35
0.026
28
Total 26 18 23 94 161
15. Teaching Title vs Student Benefit
Chi-Sq= 23.788; DF= 6; P-Value=0.001, Reject Null Hypothesis
Full Professor Associate
Professor
Assistant
Professor
Adjunct
Professor
Total
Quarter 11
8.40
0.807
6
5.81
0.006
2
7.43
3.967
33
30.36
0.230
52
Semester 6
10.17
1.712
10
7.04
1.241
18
9.00
9.000
29
36.78
1.647
63
No Preference 9
7.43
0.332
2
5.14
1.921
3
6.57
1.941
32
26.86
0.985
46
Total 26 18 23 94 161
16. Results
From the data there is a correlation between
job title and the type of system they prefer
Since there is a preference we reject Ho
After running pairwise tests, the data shows
that full professors show a preference for
quarters over semesters, while assistant
professors show a strong preference for
semesters over quarters, the other two group
don’t show a preference.
From the data there is a correlation between
job title and the type of system they believe
to be beneficial to the students
Since there is a preference we reject Ho
The data shows that overall the teaching
faculty believes that semester system is
better for the students
The results are more interesting in this
comparison because the adjunct professors
are almost equally split three ways
17. Hypothesis (system they have previously taught in)
Ho: There is no difference in the proportion
of teaching faculty that have only taught in a
quarter system compared to those who have
taught in both a quarter and semester
system when it comes to what system they
prefer.
Ha: There is a difference in the proportion of
teaching faculty that have only taught in a
quarter system compared to those who have
taught in both a quarter and semester
system when it comes to the system they
prefer
Ho: There is no difference in the proportion
of teaching faculty that have only taught in a
quarter system compared to those who have
taught in both a quarter and semester
system when it comes to what system they
thinks benefits students.
Ha: There is a difference in the proportion of
teaching faculty that have only taught in a
quarter system compared to those who have
taught in both a quarter and semester
system when it comes to the system they
think benefits students.
18. No preference Quarter Semester Total
Taught in only
quarter system
16
10.61
2.7398
30
28.80
0.0504
15
21.60
2.0147
61
Taught in both
quarter and
semester system
12
17.39
1.6713
46
47.20
0.0308
42
35.40
1.2290
100
Total 28 76 57 161
Cell contents: Count
Expected count
Contribution to Chi-Square
Pearson Chi-Square = 7.736 DF = 2, P-Value = 0.021, Reject Null Hypothesis
Chi Square Test: Previous System Taught in, Teaching Faculty Prefers
19. No preference Quarter Semester Total
Taught in only
quarter system
25
17.43
3.2892
20
19.70
0.0045
16
23.87
2.5945
61
Taught in both
quarter and
semester system
21
28.57
2.0064
32
32.30
0.0028
47
39.13
1.5287
100
Total 46 52 63 161
Cell contents: Count
Expected count
Contribution to Chi-Square
Pearson Chi-Square = 9.480 DF = 2, P-Value = 0.009, Reject Null Hypothesis
Chi Square Test: Previous System Taught in, Benefits Students
20. Results
The null hypothesis was rejected in both chi
square tests of what does teaching faculty
prefer and what benefits students when
comparing the three responses of no
preference, semesters and quarters.
After running pairwise tests on the data to
determine what differences actually exist,
the only contrast that was shown was
between the responses “no preference”
and “semesters”
Professors who have taught in both systems
show a higher preference for semesters
than expected, but a lower no preference
response than expected
Professors who have only taught in a quarter
system show a higher no response than
expected and lower preference for
semesters than expected
Even though the null hypothesis was rejected
in both cases, there is no evidence that
shows an actual difference between the
system that is preferred or the one that
benefits students
21. Conclusions
Overall, it appears that CSUEB teaching faculty prefer quarters over semesters, while between 12-
22% have no preference.
Overall, it appears that CSUEB teaching faculty think semesters have a slight edge over quarters
when it comes to what system benefits students, while between 23 - 34% have no preference.
The college within CSUEB that a professor teaches in does not appear to affect their preference or
what they think benefits students.
Assistant professors prefer semesters over quarters and also think semesters benefit students more,
we are unsure why. Full professors prefer quarters over semesters, possibly due to the high amount
of time they have spent at CSUEB, a quarter system.
22. More Conclusions
There is no evidence indicating that the previous system that teaching faculty have
been in, has any effect on what system they prefer for themselves or students.
Teaching faculty who have taught only in quarter system probably chose no preference
over semesters because they don’t have enough information on semesters.
Teaching faculty who have taught in both systems chose semesters over no preference
because they feel strongly about semesters.
The addition of the “no preference” category made some our data more difficult to
interpret.
23. Shortcomings
Our response rate was lower than we wanted, around 53%
Some colleges responded more than others. The College of Letter, Arts, and Social
Sciences, and The College of Science had a majority of the responses.
Depending on the rank of the teaching staff, it affected the response rate
If we took out the no preference, then maybe we could have seen a difference in
preference.
One of the questions was misunderstood by 20% of the respondents, it could have
been worded differently
The survey questions could have been randomized to eliminate bias. The order of