The Effect of Time of Day on Student Learning

1. The Effect of Time of Day on Student Learning Kevin Rice ED 703.22 Spring 2008

2. Introduction Statement of problem Review of related literature Statement of hypothesis Method Participants (N) Instruments Experimental design Procedure Results Discussion Implications Table of Contents

3. Introduction • In 1974 Dunn, Dunn, and Price developed a self-report questionnaire so students could identify their own learning styles called the Learning Styles Inventory. The inventory is made up of true/false questions many of which are similar in nature to allow checking for a student’s consistency in answering. Twenty of the one hundred four questions included in the inventory question time of day preferences.

4. Statement of the problem It is assumed by many teachers that students are most attentive and alert in the morning. It is also widely believed that students perform best in the morning, and that is why most standardized tests are in the morning and many teachers instruct reading at that time.

5. Review of Related LiteratureStudent Preference Rita Dunn, Kenneth Dunn, Louis Primavera, Richard Sinatra, and Joan Virostko found “Students matched with their time preference in reading and mathematics scored significantly higher than when mismatched” (1987)

6. Ron Banks and Beth Atkinson feel teachers should attempt to “match each individual student time-of-day preferences with his or her more difficult subjects (2004). Also, Pytel believes, “As students learn which time is best for them, they can utilize that time for optimal gain (2006).

7. Morning Sjosten-Bell’s results showed, “Higher scores in the morning, followed by the mid-morning, then the afternoon” (2005)

8. Biggers stated, “The morning-active students had higher academic achievement than those alert later in the day” (1980). Zager & Bowers discovered, “Pupils performed better in the morning” (1983)

9. Afternoon Barron, Henderson, & Spurgeon discovered, “Overall increase in the mean scores for the mastery of reading skills for below grade level students who were instructed in the afternoon as compared with those in the morning” (1994).

10. Klein stated, “Fifth graders’ attention levels were especially high in the afternoon” (2001).

11. Hypothesis Teaching elementary school mathematics to twenty-six fourth graders at P.S. 198 in Brooklyn, New York is more effective when instructing students at their preferred time of day.

12. Participants The participants for this action based research project is my current class at P.S. 198 in Brooklyn. These are fourth graders (ages ranging from 9-12). Twenty-six fourth grade students: 14 boys 12 girls One twelve year old Thirteen 10 year olds Twelve 9 year olds All are African-American and most are of Caribbean decent. One boy and one girl are ELL students.

13. Instruments • Rita Dunn’s Learning Styles Inventory (LSI) • Everyday Mathematics unit 8 assessment test

14. Experimental Design • Quasi-Experimental: Individuals are not randomly assigned. • Nonequivalent Control Group Design: Two groups are pretested (0), exposed to a treatment (X), and Posttested (O).

15. Threats to Internal and External Validity Threats to Internal Validity Regression • Extremely high and/or low scores regress to the mean on retesting • Selection interactions • Participants have different maturation rates • I also found Testing/Pre-test Sensitization may cause a problem. Pretesting could have affected posttest.

16. Threats to External Validity • Pretest-X Interaction • Pretest-Treatment • Participants react differently to treatment because they have been pretested • Selection-Treatment Interaction • Non-random/volunteerism of participants

17. Procedure The symbolic Design: O X1 O O X2 O The Everyday Math Unit 8 test was administered to twenty-six students in my fourth grade class (pretest) Twenty-six students of my fourth grade class were then given Rita Dunn’s Learning Styles Inventory to determine their preferred time of day to learn. The Everyday Math Unit 8 test was re-administered to 26 students in my fourth grade class to determine if preferred time of day to learn correlates with improved test scores. (posttest)

18. Results I found the students whose preferred time of the day for learning was the afternoon tests scores increased when given the test again, but this time in the afternoon.

19. Test Scores

20. Test Score Increase

21. Correlation • Every student took Rita Dunn’s Learning Styles Inventory (the questions pertaining to time preference.) • I took their questionnaire score and correlated that with the percent of increase or decrease of their posttest score. • The higher scores on the questionnaire indicated they preferred the afternoon and the lower scores meant morning.

22. 26 data pairs (x,y):( 27.0 , 10.0 ); ( 33.0 , 20.0 ); ( 29.0 , 10.0 ); ( 30.0 , 10.0 ); ( 26.0 , 20.0 ); ( 32.0 , 20.0 ); ( 31.0 , 5.00 ); ( 32.0 , 10.0 ); ( 29.0 , 20.0 ); ( 33.0 , 10.0 ); ( 10.0 , -10.0 ); ( 13.0 , 30.0 ); ( 14.0 , -25.0 ); ( 12.0 , -5.00 ); ( 10.0 , -10.0 ); ( 14.0 , -15.0 ); ( 12.0 , -10.0 ); ( 10.0 , -5.00 ); ( 14.0 , -15.0 ); ( 15.0 , -5.00 ); ( 13.0 , -10.0 ); ( 10.0 , -5.00 ); ( 12.0 , 0.00 ); ( 13.0 , 0.00 ); ( 15.0 , 0.00 ); ( 11.0 , 0.00 ); • y = a + bx where: a= -17.1 ( a = 4.5 ) b= 0.991 ( b = 0.17 ) degrees of freedom = 24r = 0.670 (p = 0.000)

23. Scatter Plot

24. Discussion • There seems to be a correlation between students’ preferred time of day to learn and increased test scores as Rita Dunn’s studies suggest: “Students matched with their time preference in reading and mathematics scored significantly higher than when mismatched” (1987)

25. Implications • Further experimentation is necessary, however if students have a preferred time of the day to learn, teachers’ instruction should adjust accordingly.