Your Task

Your job is to analyze and present the data from pre- and post-semester First Year Seminar (FYS) surveys for stakeholders. There are three key groups that have an interest in effectively applying this data in their work.

For this task, you will work in groups. Each group will choose one of the groups of stakeholders outlined below, answering, at minimum, the following questions. You are also encouraged to think of other relevant questions and analyses to present to your stakeholders.

Freshman Advisors

  1. Which groups of students appear most at risk for dropping out?
  2. Study the beginning and end-of-semester mindsets of students who are retained and not retained. Which mindsets appear to be most critical to student success?
  3. Are there any relationships between the declared major and beginning-of-semester mindsets?

Best on your analysis, provide a concise list of recommendations for freshman advisors to help them in best caring for students during their first semester at USAO.

[This task includes primarily descriptive statistics, though you will have the opportunity to utilize other methods.]

Administrators

  • In what ways are different groups of students impacted by their experience in FYS?
  • What groups of students are most at risk for retention?
  • What differences (if any) in student outcomes do you observe between the different the sections offered?
  • What differences (if any) in student outcomes do you observe between the different the types of instructors teaching FYS (adjunct, staff, or faculty)?
  • What differences (if any) in student outcomes do you observe between the different the different formats of FYS (online or in-person)?

If time permits, use logistic regression to study what factors predict retention most strongly.

Based on your analysis, what considerations should administrators be aware of when determining:
1) format (online vs. in-person) of FYS, and 2) staffing (choosing instructors) for FYS

[This task includes primarily descriptive statistics, though you will have the opportunity to utilize other methods.]

FYS Instructors

  • What is the relationship between the various mindsets studied? Does this relationship remain the same across gender?
  • In what ways (if any) do student mindsets change?
  • To what extent are the mindsets studied correlated with GPA and retention?
  • To what extent does beginning and end of semester mindsets predict retention?
  • To what extent do changes in mindsets predict retention?

Based on your analysis, provide recommendations for instructors teaching FYS in future terms. What mindset(s) should instructor focus on fostering in their classes? What other considerations should they be aware of?

[This task requires both correlational and predictive statistical methods, though you have the opportunity to utilize other methods.]

The data

The data for this project comes from pre- and post-semester surveys given to students in First Year Seminar (FYS) in the Fall of 2024.

Your data is provided in four files, described in the following subsections:

  • “data_institution.csv” - institutional data was provided from USAO’s institutional records.
  • “data_pre.csv” - Pre-semester survey results (with the above institutional data added for those taking this survey)
  • “data_post.csv” - Post-semester survey results (with the above institutional data added for those taking this survey)
  • “data_wide.csv” - Longitudinal data across matching participants from both surveys (with the above institutional data added for those taking this survey)
  • “data_long.csv” - The responses from pre- and post-semester surveys joined by row (long data).

Note: The data you are using is randomly generated (fake data), but generated to provide some of the same relationship underlying the original data.

Institutional Data

The following institutional data was provided from USAO’s institutional records.

  • major_1 - major (as of the beginning of the second year of college)
  • major_2 - second major, if declared (as of the beginning of the second year of college)
  • minor_1 - minor, if declared (as of the beginning of the second year of college)
  • GPA_Career - Career after first year of college
  • Fall_Year_2_Enrolled - whether the student enrolled in the second year of college

Pre-semester Survey

Growth Mindset Scale

The Growth Mindset Scale (GMS) measures how much people believe that they can get smarter if they work at it.

GMS1, GMS2, and GMS3 correspond to questions 1-3 of the GMS. The mean of these three items represents a composite measure of growth mindset.

Stress Mindset Measure

The Stress Mindset Measure (SMMS) measures “the extent to which an individual adopts a mindset that the effects of stress are enhancing or debilitating”

Items SMM1-6 correspond to questions 1-6, respectively. Questions 7-8 Were not included.

Please note that reverse scoring of the negatively worded items (1,3,5) has already been applied to the results provided. Thus, a mean of these 6 items, as provided, represents a composite measure of stress mindset.

NEOS Scale

The Next Element Outcomes Scale (NEOS) measures one’s self-efficacy for effective functioning across three dimensions: maintaining open (emotions), resourceful (thinking), and persistent (action).

The following questions are rated from 0 (No way I can) to 10 (Definitely sure I can).

  1. Stay motivated when things seem impossible.
  2. Trust in the goodness of others.
  3. Bounce back quickly when I am stressed out.
  4. Accept my failures as a necessary part of problem-solving.
  5. Stay focused on my goals when things keep getting in my way.
  6. Ask others for help when I need it.
  7. Find more than one way to solve a problem.
  8. Understand both my strengths and weaknesses.
  9. Finish what I start even if I don’t want to.

A mean of these nine items (as the data is provided) represents a composite measure of effective functioning across these three dimensions.

Remaining Pre-semester Questions

Four additional questions were also asked using the response scale below:

  • 1 - Strongly Disagree
  • 2 - Disagree
  • 3 - Neither agree nor disagree
  • 4 - Agree
  • 5 - Strongly Agree

Schedule: I have made my schedule for the Spring semester with the intent to be a student at USAO next semester.
Grad_4yrs: I intend to graduate from USAO in the next four years.
Gender: Women, Man, Transgender, Non-binary (Note, in the pre-semester survey, the options for this were inaccurately provided as Male, Female, Transgender.)
FYS_Section: One of 16 sections of FYS taught in Fall 2024. Of those, 8 sections were taught by faculty, 3 by adjunct, and 5 by staff. Three sections were online, as listed below.

  • Sections taught by Faculty
    • Section 1 - Instructor F1
    • Section 5 - Instructor F2
    • Section 7 - Instructor F1
    • Section 8 - Instructor F1
    • Section 9 - Instructor F3
    • Section 10 - Instructor F4
    • Section 11 - Instructor F2
    • Section 12 - Instructor F5
  • Sections taught by Adjunct
    • Section 2 - Instructor A1
    • Section 4 - Instructor A2
    • Section 6 - Instructor A1
  • Sections taught by Staff
    • Section 3 - Instructor S1
    • Section 13 - Instructor S2 (Online)
    • Section 14 - Instructor F3 (Online)
    • Section 15 - Instructor F3 (Staff)
    • Section 17 - Instructor F3 (Online)

Post-Semester Survey

In addition to all the above questions, the following questions were provided on the pre-semester survey, using the response scale below:

  • 1 - Strongly Disagree
  • 2 - Disagree
  • 3 - Neither agree nor disagree
  • 4 - Agree
  • 5 - Strongly Agree

Value1 - The in-class sessions were a valuable use of my time. (If you are enrolled in an online session, choose NA)
Value2 - The online asynchronous activities were a valuable use of my time.
Value3 - I would prefer if this course involved more in-person sessions.
Value4 - I would prefer if this course involved more online activities.

Longitudinal (Wide) Data

Based on unique identifiers, respondents with matching pre- and post-semester responses were merged to study longitudinal effects.

Grouped Pre- and Post-semester (Long) Data

The responses from pre- and post-semester surveys are joined by row (long data) for analysis of instrument validity.