Matt Dunleavy Walter F. Heinecke The Impact of 1:1 Laptop ...mathenrich.pbworks.com/w/file/fetch/52433674/Impact.pdf · on Middle School Math and Science Standardized Test Scores

Matt DunleavyWalter F. Heinecke

The Impact of 1:1 Laptop Useon Middle School Mathand Science Standardized Test Scores

ABSTRACT. Researchers and evaluators have been attempting to doc-ument the impact of ubiquitous or 1:1 computing on students, teachers,schools, and communities. However, the most recent reviews of researchon 1:1 computing initiatives reflect a deurlh of rigorous studies and em-phasize the need for well-designed, scientifically based research to mea-sure the impact of 1:1 learning on student achievemenL This studyinvesligates the eflecf of I: I laptop lo student ratios on math and scienceachievement in ut-risk middle school students. The researchers used apretest-posttest eontrol-group design. The findings are based on be-iween-groLips analysis of covariance (ANCOVA) of longitudinal datacomparing standardized achievement test scores. The researchers com-pared the test scores of students randomly assigned to 1:1 laptop class-rooms with the lest scores of students in classrooms without I: I laptopsin the same middle school. Students were exposed lo ihe trcutment fortwo years and the authors used the sludenls as tlie unit ol anulysis.Pre-existing aehievement scores for each student were included as a

MATT DLJNLEAVY is Assislani Professor in Iiislruclional Technology, School ofTeacher Education & Leadership, Room C171. Radford University, P.O. Box 6959,Radford. VA 24142 (E-mail: [email protected]).WALTER F. HEINECKE is Associate Professor. Depaitnicnt of Educational Leader-ship. Foundations & Policy. Curry School of Education, University of Virginia, 288Riifliier Hall. 405 Emniett Street, Suuth Charlottesville, VA 22903 (E-mail: [email protected]).

Computers in the Schools, Vol 24(3/4} 2007Available online at htlp://cits.haworihpress.com

© 2007 by The Haworth Press, Inc. All rights reserved.doi:10.1300/J025v24n03 02 7

8 Computers in the Schools

covariale to statistically equate groups previous to analysis. Resultsshowed significanl post-inlcrvenlion program elTects tor science achieve-ment. Furlherniore. there was a gender effect in science achievement,with boys significantly outpei forming girls in the same 1:1 laptop class-room. In contrast, no significant program effects for math achievementwere obtained. The results suggest that 1:1 laptop instruction can in-crease sttident achievement under certain conditions. This study has im-plications for policymakers, instructional designers., and educators whoare currently implementing a 1:1 laptop program or considering such animplementation. The authors suggest the need lor further research tohelp determine the efficacy of 1:1 laptop inslruction and the implemen-lalion conditions necessary for increased student achievement in thiscontext. doi:10.I300/J025v24n03_02 [Ailicle copies available for a fee fromThe Haworth Document Delivery Sendee: l-800-HAWORTH. E-mail address:<docJetiveiy@lta\\onhpress.com> Weh.site: <httj}://w\vw.HawotihPress.com> ©2007 hy The Haworth Press. Inc. All rights reserved. /

KEYWORDS, Ubiquitous computing. 1:1 laptops, science achieve-ment. ANCOVA

Beginning in 1985 witb tbe Apple Classrooms of TomorrowT^i (ACOT)(Apple Computer, 1995) project, tbe last 20 years have seen a steady in-crease in the number, scope, and sopbistication of 1:1 computer to stu-dent ratio or ubiquitous cotnputing initiatives tbat now stretcb fromMelbourne to Maine, ranging from programs witb fewer tban 100 com-puters to over 36,000. In 2000, tbere were approximately 1,000 Ameri-can scbools using a 1:1 tiiodel totaling over 150,000 laptops (Johnstone,2003).

Advocates bave bailed 1:1 programs as baving tbe promise to trans-form education as we know it (Brown, 2003; Papert, 1980, 1993; Stager,1995), wbile otbeis see tbis promise as simply another "oversold" fadtbat is at best a drain on the perpetually limited education budget and atworst a distraction tbat is actually detrimental to tbe education of ourchildren (Cuban, 2001: Oppenheitncr. 2003).

Researchers and evaluators bave been attempting to document tbeimpact tbat 1:1 tecbnology is baving on students, teacbers, scbools, andcommunities. Several studies have documented significant increasesin more general achievement measures across the content areas, such

Matt Dunleavy and Walter F. Heinecke 9

as GPAs, end-of-course grades, and standardized norm-referenced tests(Efaw, Hampton, Martinez, & Smith, 2(X)4; Gulek & Demirtas, 2005;Light, McDermott, & Honey, 2002; Ross, Lowtber, Wilson-Relyea, &Wang, 2(X)3; Siegle & Foster, 2001). However, other .studies found mar-ginal and nonsignificant laptop effects on student achievement and atti-tudes (Gardner, Morrison, & Jarman, 1993; Gardner, Morrison, Jarnian,Reilly, & McNaily, 1994; Momson, Gardner, Reilly, & McNally, 1993;Rockman, 1999).

The general consensus from recent reviews of the research to date isthat additional detai led Information is needed to assess the impact of 1:1laptops on teaching and learning (Lemke & Martin, 2003; Penuel, 2005;Russeli, Bebell, & Higgins, 2004; Zucker, 2004). Specifically, in his re-view of research on 1:1 initiatives, Penuel (2(X)5) highlighted the dearthof scientifically based research about the efficacy of !: I laptop programs.Ba.sed upon these reviews of the literature, it is evident there is a needfor more scientifically based research to explore and document the im-pact and efficacy of 1:1 laptop programs on student learning.

The findings in this paper contribute to the research by disseminatingresults from a pretest-posttest control-group study on the effect of 1:1laptop to student ratios in math and .science achievement among at-riskmiddle .school students. This research seeks to determine whether 1:1laptop initiatives increase student achievement in science and math? Ifso, are these gains experienced by all students?

SITE AND PROGRAM CONTEXT

The school in this study was a middle school in an urban school dis-trict located in a mid-Atlantic state. This middle school serves 972 stu-dents in grades six through eight. The ethnicity percentages of the schoolstudent population are 81 % African American, 2% Asian, 3% Hispanic,and 13% White (see Table I).

TABLE 1. Demographic Information for School Site

School Name

Middle school

GradesServed

6-8

Enrollment

972

District Type

Urban

PercentagePoverty^

59.67

PercentaaeMinority

87.2

^Free and reduced lunch percentage"African American, Hispanic, Asian, Pacific islander, American Indian, Filipino

10 Computers i n tbe Scbotils

The school's history of poor academic achievement prior to 2001-2002,and low-test scores on the state's standards test (SST) assessments re-sulted in the state's notifying the school that its accreditation was atrisk. The school has also struggled with a lack of parental involvementand with grade retention rates that have usually been the highest in thedistrict.

The goals and intentions ofthe 1:1 laptop program were not related tomajor changes in the philosophy of teaching and learning at the school,but viewed as a way toincrease the efficiency of their current curricularand instructional processes in order to achieve greater success measuredby traditional indicators such as state standards test scores, SAT testscores, grades, discipline referrals, grade retention rates, and prepara-tion for future workplace skills.

The 1:1 laptop program began with a group of 100 seventh-grade stu-dents (approximately one-third of the seventh-grade class) and a teamof four teachers during the 2001 -02 school year. The students were ran-domly selected from the school population and placed within 1:1 laptopclassrooms or clas.srooms that did not have 1:1 laptops. The teacherswere volunteers. The following year, the program was expanded to in-clude a new group of 100 seventh-graders and an eighth-grade team ofteachers who inherited the previous seventh-grade participants, and fi-nally expanded to include 100 sixth-graders and a team of teachers.

As of 2005, the school's laptop program involved approximately 300students and 12 teachers across three grade levels, sixth through eighth.There was one laptop team per grade, consisting of four core teachersand approximately 100 students. The core teachers taught English, math,social studies, and science. These students were given 24-hour access totheir laptops during the school week (the students did not take them homeover the weekends). While approximately 80% ofthe households in thecity had access to a computer, the fact that the students at the schoolcould not take the laptops home for the weekend limited their use forlong-term projects and weekend homework assignments. The technol-ogy staff at the school was studying the situation to decide how best toaddress this issue during the 2005-06 school year. The laptops were Ap-ple iBooks with 128 megabyte hard drives running Operating System10.2.8. Each computer was loaded with Microsoft Office software andconfigured to use Internet Explorer as the Web browser. In addition, eachlaptop contained Glencoe/McGraw-Hill textbook resources as well asonline textbook access. While the students carried their laptops fromclass to class, the storing/charging cart was housed in each grade-levelteam leader's room.


The school district library provided numerous online resources forclassroom use to teachers and students via the Web. Among the free andcontractual onhne resources inade available to students and teachers wereUnited Streaming, ProQuest, ERIC. PBS Videodatabase, TeachingBooks.net, Facts for Learning, Gale Group, and World Book EncyclopediaOnline. In addition, the city school district provided technology trainingand classroom technology integration support on an ongoing basis atboth the district and building level. The wireless network covered ap-proximately 95% of the school and all of the 1:1 classrooms were wireless.The school also housed several servers, one of which was dedicated toteacher and student use. Except for the 1:1 laptops, the teachers and stu-dents in the control group had access to all the resources described abovevia the computer lab located in the school library. Teachers could sched-ule time in the computer lab, which contained approximately 20 Internet-ready iMac Desktop computers. These computers were loaded with thesame software as the laptops.

METHODOLOGY

The researchers used a pretest-posttest control-group design. Thefindings are based on between-groups analysis of covariance (ANCOVA)of longitudinal data comparing math and science standardized achieve-ment test scores of students randomly assigned to 1:1 laptop classrooms,versus students randomly assigned to classrooms without 1:1 laptops,within the same middle school. Students were exposed to the treatmentfor two years and the authors used the students as the unit of analysis.Pre-existing achievement scores and fifth-grade science and math StateStandardized Test (SST) scores for each student were included as a co-variate to statistically equate groups previous to analysis. The research-ers used the statistical procedure (ANCOVA) to determine if there weresignificant differences in test scores between two groups of studentswho had received different forms of instruction (1:1 laptop instructionversus instruction without 1:1 laptops). The use of a pretest or covariateallowed researchers to statistically remove any pre-existing achieve-ment differences between the two groups before comparison, in order toensure that any differences detected were due to the intervention. Theresearchers used Statistical Package for the Social Sciences (SPSS) com-puter software to run the analyses. The research design is represented inFigure 1.


Data Collection Measures

The school di strict personnel asked the researchers to analyze oneschool's achievetnent data to determine the impact of the laptop pto-gram. The school district personnel stripped all of the data of identify-ing information and replaced it with a student identification numberbefore providing the data to the researchers.

Participants

The randomization ofthe students to treatment and control classroomsprovided a sample that demographically reflected the larger school popu-lation. Table 2 provides a demographic summary of the participants.

FIGURE 1. Research design.

Lgptou Treatment

Group Pretest 5*GradeSST Semes P..s«tes( 8'" Grade SST Scores

Treatment 0 R X

Control O R 0

R = Randomization of students to treatmant and control classrooms.

TABLE 2. Demographic Profile of Participants

Factor

GenderMaleFemale

EthnicityBlackWhiteHispanicAsian

F

2232

48213

Treatment(W=54)

%

40.759.3

88.93.71.9

5.6

F

4667

981122

Control(W=113)

%

40.759.3

86.79.71.81.8

Participants (Combined){N =

F

6899

1461335

167)

%

40.759.3

87.47.81.8

3


FINDINGS

The analysis of the data from this study revealed three major find-ings: (1) There was a significant main effect of the laptop treatment onscience posttest scores after partialing out pre-existing science achieve-ment differences with a covariate; (2) there was a significant interactioneffect of treatment and gender on science posttest scores after partial-ing out pre-exisling science achievement differences with a covariate;(3) there were no significant main effects or interaction effects of thetreatment on math posttest scores after partialing out pre-existing mathachievement differences with a covariate. Due to the lack of significantdifferences on math achievement, a detailed statistical description of theanalysis will not be provided, but the significance of this finding will beexplored in the discussion. The focus of the detailed description belowis on the statistically significant differences revealed in science achieve-ment posttest scores, as a result of the treatment.

Analysis Results

The first statistical analysis conducted was a one-way between-sub-ject analysis of covariance (ANCOVA) to determine the main effect of1:1 laptops on science achievement group means after adjusting for pre-existing differences. The independent variable, laptop access, includedtwo levels: Laptop (1;1 laptop instruction) and No Laptop (regular in-struction without 1:1 laptops). The dependent variable was the eighth-grade science SST and the covariate was the fifth-grade science SST,both administered by the state. Preliminary analysis assessing the homo-gcneity-of-slopes a.ssumption revealed that the relationship between thecovariate and the dependent variable did not differ significantly as afunction of the independent variable, F( I, 159) = .773,/? = .381, partial1]' = .005. The homogeneity-of-slopes analysis ensures that the datameet the assumption that the covariate is linearly related to the depen-dent variable-in this case, that the pretest SST scores were related to theposttest SST scores. If the interaction is significant, the assumption isnot met and the ANCOVA will be meaningless. In this case, the interac-tion was not significant and therefore an ANCOVA was conducted. TheANCOVA was significant: F (I, 160) = 4.831, /? = .029, partial TI' =.029. While the ANCOVA was significant at the p < .03 level, 1:1 lap-top instruction accounted for just 2.99c of the variance in eighth-gradescience achievement (partial T) ). Another index for the magnitude oftheeffectisCohen'sJ, which in this case is .24-a relatively small effect


size according to the guidelines provided by Cohen (1988). The impli-cations of this are detailed in the discussion section.

The means of the eighth-grade science test adjusted for pre-existingdifferences reflected the significant differences between treatment andcontrol groups. The students in classrooms with 1:1 laptop instructionhad the larger adjusted mean (M = 430.13) and the students in classroomswithout 1:1 laptops instruction had the smaller adjusted mean (M =419.07) (see Table 3, Table 4, and Figure 2).

The second statistical analysis conducted was a one-way between-subjects analysis of covariance (ANCOVA) to determine the main ef-fect of 1:1 laptops on science achievement group means and interactioneffects on gender, after adjusting for pre-existing differences. The inde-pendent variables were laptop and gender. The dependent variable wasthe eighth-grade science SST and the covariate was the ftfth-grade sci-ence SST, both administered by the state. Preliminary analysis assessingthe homogeneity-of-slopes assumption revealed that the relationshipbetween the covariate and the dependent variable did not differ signifi-cantly as a function of the independent variable: F (\, 158) = .615, p =.412 partial r\' = .004. Once again, the interaction was not significant,the assumption for homogeneity-of-slopes was met and an ANCOVA

TABLE 3. Eighth-Grade Science Posttest Means and Standard Deviations forLaptop Main Effect

No laptopLaptop

Pretest Mean(Std Deviation)

390.91 (38.85)387.92 (40.57)

Posttest Mean{Std Deviation)

420.30(46.26)427.52(44.18)

Adjusted PosttestMean (Std Error)

419.07(2.84)430.13(4.15)

TABLE 4. Analysis of Covariance of Treatment

SS df MS F

N

11152

PFifth-grade science SST (covariate) 191,907.52 1 191.907.52 214.67 .000'Treatment 4,319.70 1 4.319.70 4.83 .029*Corrected model 193,754.43 2 96,877.21 108.37 .000'Error 143,036.65 160 893.98Corrected totai 336,791.08 162

•p < .01"p < .05

Matt Dunleavy and Walter F. Heinecke t5

was conducted. The ANCOVA main effect was significant: F (1,158) =7.329, p = .008, partial j] = .044. In addition there was a significant inter-action effect between the 1:1 laptop instruction and gender: F(]\ 158) =5.643, p = .019, partial TI' = .034. While the ANCOVA was significant,the strength of the relationship between 1:1 laptop instruction and eighth-grade science achievement was relatively weak, as revealed by the par-tial Ti', with laptop instruction accounting for 4.4% of the variance in thedependent variable and 3.4% of the variance in the interaction effectwith gender.

The means of the eighth-grade science test adjusted for pre-existingdifferences reflected the significant differences between treatment andcontrol groups as well as the interaction effects. The male students inclassrooms with 1:1 laptop instruction had the largest adjusted mean {M =442.59), while the male students in classrooms without 1:1 laptops in-struction had the smallest adjusted mean (M = 416.70). Female studentsin classrooms with 1:1 laptop instruction had a slightly larger adjustedmean (M = 422.37) than female students in classrooms without 1:1 lap-tops instruction (M = 420.68). These differences suggest that 1:1 laptopinstruction was more effective in increasing science achievement for malestudents than it is for female students. The markedly different Cohen's ieffect sizes reinforce this finding. The magnitude of the interaction ef-fect for male students was much stronger {d= .55) than it was for femalestudents (d = .04). The implications of this are detailed in the discussionsection. This strong interaction effect can be clearly seen in Figure 2 (seeTable 5, Table 6, and Figure 3).

FIGURE 2. Estimated marginal means science posttest main effect.

Tmimm


TABLE 5. Eigbtb-Grade Science Posttest Means and Standard Deviations

No laptopMaleFemale

LaptopMale

Female

Pretest Mean(Std Deviation)

396.41 (44.02)387.13(34.71)

388.90 (47.68)387.31 (36.23)

Posttest Mean(Std Deviation)

424.76 (46.78)417.26(46.02)

440.85 (53.20)419.19(35.92)

Adjusted PosttestMean (Std Error)

416.70(4.43)

420.68 (3.64)

442.59 (6.60)422.37 (5.22)

N

4566

2032

TABLE 6. Analysis of Covariance of Treatment by Gender

Fifth-grade scienceSOL (covariate)

Treatment

Gender

Treatment" gender

Corrected model

Error

Corrected total

SS

190,078.04

6,382.28

2,205.47

4,914.04

199,204.77

137,586.36

336,791.08

df

1

1

1

1

4

158

162

MS

190,078.04

6,382.28

2,205.47

4,914.04

49,801.19

870.80

F

218.28

7.33

2.53

5.64

57.19

P

.000*

.008*

.114

.019"

.000"

•p < ,01"p < .05

In addition to tbe statistically significant interaction effect between1:1 laptop uses and gender on the science posttest, gender interactionpatterns tbat were not statistically significant were also observed inEnglish and writing posttests. Once again, these differences suggest tbat1:1 laptop instruction is more effective in increasing English and writ-ing acbievement for male students than it is for female students. Wbilenot statistically significant, this pattern merits discussion and warrantsfurtber researcb. Figures 3 and 4 clearly exbibit an interaction similar totbe one observed in the science posttest (see Figures 4 and 5).

Why is this pattern occurring? If it were an anomaly, wby would it bemanifest in several content areas across multiple classrooms over a two-year period? Wbat does it suggest, if anything, about gender differencesin tecbnology-ricb classrooms? Does it reflect a gender-based difference


FIGURE 3. Estimated marginal means science posttest interaction effect.

FIGURE 4. Estimated marginal means English posttest.

FIGURE 5. Estimated marginal means writing posttest.


in tecbnology interest and aptitude? What import does this have on howwe educate our female students as more technology enters the class-room, assuming this pattern generalizes to other sites?

LIMITATIONS

The findings from this study have several implications. Before dis-cussing these implications, it is instructive to detail the limitations ofthis study. Despite the fact that the students were randomly assigned tothe treatment and control classrooms, teacher effect on student achieve-ment was not controlled. This introduces a confounding variable, whichneeds to be acknowledged. The effect of the teacher and researchers' at-tempts to control for this confounding variable are perennial concernsfor educational researchers. A second limitation of this study was therelatively small sample size of males (A = 20) in the laptop treatmentgroup for tbe second ANCOVA analysis with gender in the model. Thislimitation is especially significant considering the treatment-gender in-teraction effect observed in the analysis.

DISCUSSION

While acknowledging the limitafions, this study contributes to theongoing dialogue concerning 1:1 laptop use and impact and has impli-cations for policymakers, administrators, and classroom teachers in threespecific areas. First, the results draw attention to the need to focus on dif-ferences of the impact of technology in different content areas. The ap-plication of technology to different content areas may have differentialeffects. Second, the study draws our attention to the need to examine theimplementation of technological innovations. The implementation may bemore thorough in some content areas over others because of availability ofcontent-specific applications, experience and buy-in of teachers, and otherfactors. Third, the results call attention to variations in the impact oftechnology due to gender.

The significant main effect suggests that 1:1 laptop instruction some-how enhances or facilitates student science achievement. However, itbegs the question as to why a significant main effect was not observed inmath achievement. Future research must address the variation in imple-mentation across content areas. Was tbe laptop initiative more thorough-ly implemented in the science classrooms at the school being studied?

Matt Dunleavy and Walter R Heinecke 19

Were more applications readily available for science instruction withthe laptops? Do laptops have a differential impact in different contentareas? Does science instruction somehow lend itself more readily to lap-top-based instruction, thereby facilitating student comprehension andretention? Is it a case of simply more laptop-based science-focused re-sources and Web sites relative to math resources? In addition, while themain effect for science was statistically significant, the relatively smalleffect size {d = .24) suggests that future research needs to address thepractical contribution of 1:1 instruction to student achievement. In lightof constrained budgets and increased accountability, the strength of theeffect needs to be explored in order to assess the practical significanceof any study involving 1:1 computing.

The interaction effect of gender and laptop use on science achieve-ment suggests some interesting possibilities. The relationship betweengender and science learning has been asignificant issue since the 1990s(Kahle & Meese, 1994; Weinburgh, 1995), as has the relationship be-tween gender and technology in education (Acker & Oakley, 1993;Cooper & Weaver, 2003; Durndell & Lightbody, 1993; Volman, 1997;Volman & van Eck, 2001). The greater attrition of girls and women fromscience and technology fields relative to their male peers is well docu-mented (Cooper & Weaver, 2003). However, the causes for this attritionare poorly understood. The debate as to why this attrition occurs is con-tentious and politically charged as evidenced by the events surroundingHarvard's President Summers comments in January of 2005 in whichhe suggested that innate cognitive differences may be one of the reasonswhy women are underrepresented in scientific fields (Anita Borg Insti-tute, 2005). Regardless of the causes, research suggests that experiencesof girls in middle and high school have significant effects for later deci-sions in science and technology (Barron, 2004). The 1;1 access tolaptops at the school in the study did have a positive effect on sciencelearning, but not one experienced equally by girls and boys. In the cur-rent study, girls had similar physical access to computer resources butdid not show similar results in termsof science content mastery. This ismost clearly illustrated by the difference between the effect size for malestudents (t/ = .55) and the effect size for female students (d = .04) on sci-ence achievement. In this study, the use of 1:1 laptop science instructionappears to be moreeffectiveforboys than it is for girls. However, we donot understand the mechanisms behind this disparity.

Barron (2004) reminds us that access to technology does not neces-sarily equate to Huency. Barron found that, even when holding experi-ence with content and technology constant, girls used technology within


classrooms in different and less sophisticated ways than did boys insome key areas such as simulations or modeling. While we may be wit-nessing similar results in terms of giris and science, it is clear thatmerely adding technology into the mix does not mitigate gender effectsreported in the science education literature. The findings in this researchsuggest a few possible lines of inquiry: (1) Are boys more engaged withscience than girls? (2) Are boys more engaged with technology thangirls? (3) Are boys more engaged with a combination of science andtechnology than giris? (4) Do boys exhibit more time on task or taskperseverance in science classes with laptops relative to giris in the sameclass? (5) Do boys spend more time using laptops in a 1:1 laptop envi-ronment relative to girls in the same classroom? (6) Are boys socializedto the use of technology at an earlier age through computer games, re-sulting in a higher level of computer comfort and proficiency? (7) Arethe programs used in the 1:1 classroom gender-biased? These questionsand others need to be fully explored as more technology is used in theclassroom to deliver instruction. While it is important to ensure equalaccess among student subgroups to technological tools, it is even moreimportant to determine if equal access equates into equal opportunity foracademic success across student populations by race, class, and gender.

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Matt Dunleavy Walter F. Heinecke The Impact of 1:1 Laptop ...mathenrich.pbworks.com/w/file/fetch/52433674/Impact.pdf · on Middle School Math and Science Standardized Test Scores