“If this information is being used as a way to urge faculty to offer a variety of times for the classes that they offer, I would strongly encourage this. It would be wonderful if there were morning AND afternoon options for required classes; or if they toggled each semester. It may sound like a lame excuse, but many students really are more alert and focused during certain parts of the day!”

Morning versus Afternoon Classes: Analysis of Attendance, Performance, and Productivity

Clinton Brownley Iris Jyoung Thomas Mutti Elizabeth Myers 25 April 2000

Introduction

• • • Why did we choose this subject?

How does the subject relate to our class and class time?

What future benefits could come of this survey?

Questions to be Explored

• • • • Does class attendance vary based on time of day?

Are there significant differences in attendance rates among colleges?

Do students perform at their best potential in the morning or in the afternoon?

Do class times significantly effect course selection?

Outcome Predictions

• • • • Attendance rates will prove greatest in afternoon classes.

H&SS students will have the highest rate of absences, CFA students will have the lowest rates.

Performance will be best in the afternoon.

Courses are selected based upon section times

Project Design

• • Initial design: paper questionnaires Flaws in initial plan: - Random sample not ensured - Confidentiality issues • Final design: web-based survey

Sampling

Target Population:

Undergraduate student population at CMU

Sampling Frame:

CMU C-Book

Sampled Population:

Undergraduates listed in C-Book paired with a corresponding random number

Sample Assembly

• • • • • 5,200 student names listed in C-Book Each name assigned a corresponding number Minitab generation of 354 random numbers ranging from 1 to 5,200 Pairing of generated numbers to appropriate name Elimination of ineligible names to arrive at sample size n = 313

Questionnaire Design

• • • • • • 9 questions total, “short and sweet” to encourage completion Questions 1 and 2 – Categorical Question 3 – Open-ended, limited Question 4 – Categorical with open-ended option Question 5 – Open-ended quantitative Questions 6 and 7 – Categorical with open ended option Questions 8 and 9 – Rating Scale

Pilot Testing

• 40 paper surveys distributed over 3-day period • • • •

Feedback:

Question 5 worded weakly; confusing Not enough options for “reasons” in questions 6 and 7 Rating scale for questions 8 and 9 too large CFA should be included in data

Response to Pilot Testing

• • • • Rewording of question 5 to reduce ambiguity Extracurricular “reason” included in questions 6 and 7; most common “other” response Reduction in size of rating scale in questions 8 and 9 Later inclusion of CFA students

Sample Contact

• • • • • Survey sent via web link in email to 313 subjects Confidentiality among subjects stressed Link initially directs subjects to Informed Consent Statement Agreement link sends subjects to the survey; disagreement link sends subjects to a comments page All surveys and comments submitted to a designated email account for collection

Non-Response Follow Up

Round 1:

Sent 5 days after initial email

Round 2:

Sent 3 days after round 1 of non-response follow up

Response Rates

Current:

52.4% (164/313)

Initial email:

10.9% (34/313)

Round 1 follow up:

29.4% (92/313)

Round 2 follow up:

49.2% (154/313)

Descriptive Statistics

 From a sample size of n = 164 – 91.5% have classes in both the morning and afternoon – 3% have classes only in the morning – 5.5% have classes only in the afternoon   Data on Morning Classes – Mean number of classes = 9.38 (s.e. = 0.472) – – Mean proportion of classes late to = 0.28 (s.e. = 0.025) Mean proportion of classes missed = 0.38 (s.e. = 0.036) Data on Afternoon Classes – Mean number of classes = 10.65 (s.e. = 0.451) – – Mean proportion of classes late to = 0.15 (s.e. = 0.018) Mean proportion of classes missed = 0.27 (s.e. = 0.030)

Responses

Of the reasons given for missing all or part of morning classes:  

55% said: Oversleeping 22% said: Lack of motivation

 

11% said: Other 10% said: Time needed for other schoolwork



2% said: Time needed for extracurricular work



A few of the ‘Other’ reasons given were: laziness, eating breakfast, illness

Of the reasons given for missing all or part of afternoon classes: 

36% said: Lack of motivation



34% said: Time needed for other schoolwork

 

12% said: Oversleeping 10% said: Other



8% said: Time needed for extracurricular work



A few of the ‘Other’ reasons given were: eating lunch, peer pressure, illness, felt attendance was not necessary

Responses (cont.)

Rating of overall performance in morning classes compared to afternoon classes:



Importance of class start time is assembling academic schedule:



13% Time is most important factor



4% Performance is best in the AM



11% Performance is better in AM than PM



37% Performance same in AM and PM classes



29% Performance better in PM than AM



19% Performance best in PM



33% Time is more important factor



9% Don’t care



32% Which class they get is more important



13% Which class they get is most important

Statistical Analysis

Now let’s see if the data provides statistically significant results To assess the difference between classes entirely or partially missed in the AM and PM we performed 2 sample T tests.

Comparison of mean proportion of AM classes Late to and PM classes Late to: T = 2.81

p = 0.003

95% C.I. (0.04, 0.22) From this we see that there is a statistically significant difference in the proportion of classes students are late to in the morning and the afternoon.

Statistical Analysis (cont.)

Comparison of mean proportion of AM classes Missed and PM classes Missed: T = 1.91

p = 0. 028 95% C.I. (0.01, 0.19) From this we see that there is a statistically significant difference in the proportion of classes students miss in the morning and the afternoon.

Statistical Analysis (cont.)

Here are the mean proportions of morning and afternoon classes late to broken down by college  Morning Lateness  Afternoon Lateness  CFA (n = 10): 0.25, s.e. = 0.066

 CIT (n = 43): 0.26, s.e. = 0.041

 HSS (n = 66): 0.32, s.e. = 0.049

 MCS (n = 21): 0.14, s.e. = 0.033

 SCS(n = 14): 0.22, s.e. = 0.053

 SIA(n = 10): 0.29, s.e. = 0.118

 CFA: 0.09, s.e. = 0.033

 CIT: 0.16, s.e. = 0.032

 HSS: 0.16, s.e. = 0.050

 MCS: 0.09, s.e. = 0.069

 SCS: 0.18, s.e. = 0.053

 SIA: 0.09, s.e. = 0.030

Statistical Analysis (cont.)

Here are the mean proportions of morning and afternoon classes missed broken down by college  Morning missed  Afternoon missed  CFA (n = 10): 0.23, s.e. = 0.067

 CIT (n = 43): 0.37, s.e. = 0.076

 HSS (n = 66): 0.38, s.e. = 0.065

 MCS (n = 21): 0.35, s.e. = 0.060

 SCS(n = 14): 0.42, s.e. = 0.129

 SIA(n = 10): 0.28, s.e. = 0.097

 CFA: 0.10, s.e. = 0.030

 CIT: 0.20, s.e. = 0.033

 HSS: 0.29, s.e. = 0.042

 MCS: 0.35, s.e. = 0.156

 SCS: 0.35, s.e. = 0.141  SIA: 0.14, s.e. = 0.053

Statistical Analysis (cont.)

A 2 sample T test was performed on the proportions of lateness and absence in HSS and CFA (AM and PM proportions averaged for each college) Comparison of mean proportion of HSS classes Late to and CFA classes Late to: T = 0.55

p = 0.28

95% C.I. (-0.18, 0.32) From this we see that there is not a statistically significant difference in the proportion of classes that HSS students are late to and CFA students are late to.

Statistical Analysis (cont.)

Comparison of mean proportion of HSS classes Missed and CFA classes Missed: T = 1.31

p = 0.10

95% C.I. (-0.09, 0.43) From this we see that there is a statistically significant difference in the proportion of classes that CFA students miss and HSS students miss.

Performance Response

 Based on the self report question relating to performance :  15% of students feel that their performance is either best or better in the morning  37% of students feel that there is no difference in their performance in the morning and afternoon.

 48% of students feel that their performance is either best or better in the afternoon

Time influence on scheduling Response

 Based on the self report question relating to time’s influence on scheduling:  46% report that the time of class is the most or a more important factor in scheduling classes  9% report that neither time of class or which class they register for is important  45% report that the actual class they schedule for is the most or a more important factor than the time of the class.

Conclusions

• • • • Attendance rates do vary based on time of day. Not only are attendance rates higher in the afternoon, but students are late to classes less.

Proportionately HSS and CFA students are late to and miss the same ratio of classes. More students rate their performance in the afternoon as superior to their performance in the morning.

Time does not influence scheduling. There is an equal number of students that consider time when scheduling as those that consider the actual class itself.

Comments Received

• • • • More choices should have been included in questions 6 and 7, with an option of selecting more than one response.

Number of classes needs to be considered.

Respondent encouraged the inclusion of grade inquiry for AM and PM classes. Respondents generally interested in subject.

“What could we have done differently?”

• • Stratification of sample Subject selection (elimination of ineligible respondents before selecting sample)

Problems Encountered

• • Inaccessibility of Professors for separate survey to further support data gathered from students Rewording of question 5 still confused a small percentage of respondents (4 comments received regarding confusion)

Questions

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