The Effect of Time of The Effect of Time of Day on Student Day on Student

LearningLearning

Kevin RiceKevin Rice

ED 703.22 ED 703.22

Spring 2008Spring 2008

Table of ContentsTable of Contents

IntroductionIntroduction– Statement of problemStatement of problem– Review of related Review of related

literatureliterature– Statement of hypothesisStatement of hypothesis

MethodMethod– Participants (N) Participants (N) – InstrumentsInstruments– Experimental designExperimental design– ProcedureProcedure

ResultsResults

DiscussionDiscussion

ImplicationsImplications

IntroductionIntroduction

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

Statement of the problemStatement of the problem

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

Review of Related LiteratureReview of Related Literature

Student PreferenceStudent Preference

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

Ron Banks and Beth Atkinson feel Ron Banks and Beth Atkinson feel teachers should attempt to “match teachers should attempt to “match each individual student time-of-day each individual student time-of-day preferences with his or her more preferences with his or her more difficult subjects (2004). difficult subjects (2004).

Also, Pytel believes, “As students Also, Pytel believes, “As students learn which time is best for them, learn which time is best for them, they can utilize that time for optimal they can utilize that time for optimal gain (2006).gain (2006).

MorningMorning

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

Biggers stated, “The morning-active Biggers stated, “The morning-active students had higher academic students had higher academic achievement than those alert later in achievement than those alert later in the day” (1980).the day” (1980).

Zager & Bowers discovered, “Pupils Zager & Bowers discovered, “Pupils performed better in the morning” performed better in the morning” (1983)(1983)

AfternoonAfternoon

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

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

HypothesisHypothesis

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

ParticipantsParticipants

The participants for this action based research The participants for this action based research project is my current class at P.S. 198 in project is my current class at P.S. 198 in Brooklyn. These are fourth graders (ages ranging Brooklyn. These are fourth graders (ages ranging from 9-12). from 9-12). Twenty-six fourth grade students:Twenty-six fourth grade students:14 boys14 boys12 girls12 girlsOne twelve year oldOne twelve year oldThirteen 10 year oldsThirteen 10 year oldsTwelve 9 year oldsTwelve 9 year oldsAll are African-American and most are of All are African-American and most are of Caribbean decent.Caribbean decent.One boy and one girl are ELL students.One boy and one girl are ELL students.

InstrumentsInstruments

Rita Dunn’s Learning Styles Rita Dunn’s Learning Styles Inventory (LSI)Inventory (LSI)

Everyday Mathematics unit 8 Everyday Mathematics unit 8 assessment testassessment test

Experimental DesignExperimental Design

Quasi-Experimental:Quasi-Experimental:

Individuals are not randomly Individuals are not randomly assigned.assigned.

Nonequivalent Control Group Nonequivalent Control Group Design:Design:

Two groups are pretested (0), Two groups are pretested (0), exposed to a treatment (X), and exposed to a treatment (X), and Posttested (O).Posttested (O).

Threats to Internal and Threats to Internal and External ValidityExternal Validity

Threats to Internal ValidityThreats to Internal Validity

RegressionRegression Extremely high and/or low scores regress to Extremely high and/or low scores regress to

the mean on retestingthe mean on retesting Selection interactionsSelection interactions Participants have different maturation ratesParticipants have different maturation rates I also found Testing/Pre-test Sensitization I also found Testing/Pre-test Sensitization

may cause a problem. Pretesting could may cause a problem. Pretesting could have affected posttest.have affected posttest.

Threats to External ValidityThreats to External Validity Pretest-X InteractionPretest-X Interaction Pretest-TreatmentPretest-Treatment Participants react differently to Participants react differently to

treatment because they have been treatment because they have been pretestedpretested

Selection-Treatment InteractionSelection-Treatment Interaction Non-random/volunteerism of Non-random/volunteerism of

participantsparticipants

ProcedureProcedure

The symbolic Design:The symbolic Design:O XO X11 O OO XO X22 O O

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

ResultsResults

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

Test ScoresTest Scores

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Test Scores

A B C D E F G H I J

Students

Pretest

Posttest

Test Score IncreaseTest Score IncreaseName Name IncreaseIncrease

AA 10%10%

BB 20%20%

CC 10%10%

DD 10%10%

EE 20%20%

FF 20%20%

GG 5%5%

HH 10%10%

II 20%20%

JJ 10%10%

CorrelationCorrelation

Every student took Rita Dunn’s Learning Every student took Rita Dunn’s Learning Styles Inventory (the questions pertaining Styles Inventory (the questions pertaining to time preference.)to time preference.)

I took their questionnaire score and I took their questionnaire score and correlated that with the percent of correlated that with the percent of increase or decrease of their posttest increase or decrease of their posttest score.score.

The higher scores on the questionnaire The higher scores on the questionnaire indicated they preferred the afternoon and indicated they preferred the afternoon and the lower scores meant morning. the lower scores meant morning.

26 data pairs (x,y):26 data pairs (x,y):( 27.0 , 10.0 ); ( 33.0 , 20.0 ); ( 29.0 , 10.0 ); ( 27.0 , 10.0 ); ( 33.0 , 20.0 ); ( 29.0 , 10.0 ); ( 30.0 , 10.0 ); ( 26.0 , 20.0 ); ( 32.0 , 20.0 ); ( 30.0 , 10.0 ); ( 26.0 , 20.0 ); ( 32.0 , 20.0 ); ( 31.0 , 5.00 ); ( 32.0 , 10.0 ); ( 29.0 , 20.0 ); ( 31.0 , 5.00 ); ( 32.0 , 10.0 ); ( 29.0 , 20.0 ); ( 33.0 , 10.0 ); ( 10.0 , -10.0 ); ( 13.0 , 30.0 ); ( 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 , -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 ); ( 12.0 , -10.0 ); ( 10.0 , -5.00 ); ( 14.0 , -15.0 ); ( 15.0 , -5.00 ); ( 13.0 , -10.0 ); ( 14.0 , -15.0 ); ( 15.0 , -5.00 ); ( 13.0 , -10.0 ); ( 10.0 , -5.00 ); ( 12.0 , 0.00 ); ( 13.0 , 0.00 ); ( 10.0 , -5.00 ); ( 12.0 , 0.00 ); ( 13.0 , 0.00 ); ( 15.0 , 0.00 ); ( 11.0 , 0.00 ); ( 15.0 , 0.00 ); ( 11.0 , 0.00 );

y = y = aa + + bbx where: x where: aa= -17.1 ( a = 4.5 ) = -17.1 ( a = 4.5 ) bb= 0.991 ( b = 0.17 ) = 0.991 ( b = 0.17 ) degrees of freedom = 24degrees of freedom = 24r = 0.670 (p = 0.000) r = 0.670 (p = 0.000)

Scatter PlotScatter Plot

Correlation

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0 5 10 15 20 25 30 35

LSI score

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Series1

DiscussionDiscussion

There seems to be a correlation There seems to be a correlation between students’ preferred time of between students’ preferred time of day to learn and increased test scores day to learn and increased test scores as Rita Dunn’s studies suggest:as Rita Dunn’s studies suggest:

““Students matched with their time Students matched with their time preference in reading and mathematics preference in reading and mathematics scored significantly higher than when scored significantly higher than when mismatched” (1987)mismatched” (1987)

ImplicationsImplications

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