Developing New Indices to MeasureDigital Technology Access andFamiliaritySami Kitmitto, American Institutes for ResearchGeorge W. Bohrnstedt, American Institutes for ResearchB. Jasmine Park, American Institutes for ResearchJonas Bertling, Educational Testing ServiceDebby Almonte, Educational Testing ServiceOctober 2018Commissioned by the NAEP Validity Studies (NVS) PanelThe NVS Panel was formed by the American Institutes for Research undercontract with the National Center for Education Statistics. Points of view oropinions expressed in this paper do not necessarily represent the officialpositions of the U.S. Department of Education or the American Institutes forResearch.
The NAEP Validity Studies (NVS) Panel was formed in 1995 to provide atechnical review of NAEP plans and products and to identify technical concerns andpromising techniques worthy of further study and research. The members of thepanel have been charged with writing focused studies and issue papers on the mostsalient of the identified issues.Panel Members:Peter BehuniakUniversity of ConnecticutIna V.S. MullisBoston CollegeGeorge W. BohrnstedtAmerican Institutes for ResearchScott NortonCouncil of Chief State School OfficersJames R. ChromyResearch Triangle InstituteJames PellegrinoUniversity of Illinois at ChicagoPhil DaroUniversity of California, BerkeleyGary PhillipsAmerican Institutes for ResearchRichard P. DuránUniversity of California, Santa BarbaraLorrie ShepardUniversity of Colorado BoulderDavid GrissmerUniversity of VirginiaDavid ThissenUniversity of North Carolina at Chapel HillLarry HedgesNorthwestern UniversityGerald TindalUniversity of OregonGerunda HughesHoward UniversitySheila ValenciaUniversity of Washington, SeattleProject Director:Frances B. StancavageAmerican Institutes for ResearchProject Officer:Grady WilburnNational Center for Education StatisticsFor Information:NAEP Validity Studies (NVS)American Institutes for Research2800 Campus Drive, Suite 200San Mateo, CA 94403Phone: 650/376-6363
CONTENTSExecutive Summary . 1Introduction . 3Background . 3Student Access to Technology . 4Student Familiarity With Technology . 5Digital Technology Versus the Use of Paper and Pencil for Test Taking . 7The Use of Tablets Versus Computers for Test Taking . 8Summary . 8Data . 9Methodology . 10Survey Development. 10Answering the Research Questions. 12Results . 15Research question 1. Do the access, familiarity, and self-efficacy items cluster together in ways that suggestthat reliable indices of each can be constructed? . 15Research question 2. Are access, familiarity, and self-efficacy differentially distributed across gender,race/ethnicity and/or socioeconomic status? . 19Research question 3. What is the relationship between access, familiarity, and self-efficacy, and performanceon NAEP? . 25Research question 4. Is there differential validity of the indices in predicting NAEP performance acrossmodes of administration? . 27Research question 5. Do the observed relationships between indices and NAEP performance change whencontrolling for SES and other student characteristics? . 28Summary, Discussion, and Conclusion . 29Summary . 29Discussion. 31Conclusion . 34References . 35Appendix A. Data. 37Appendix B. Student Questionnaires for This Study . 38Appendix C. Access Item Percentages . 50Appendix D. Exploratory and Confirmatory Factor Analysis Results—Common Items . 56Access Domain . 56Familiarity Domain . 58Self-Efficacy Domain. 65Appendix E. Confirmatory Factor Analysis Results—Full Set of Items . 66Appendix F. Regression Results for Digitally Based Assessment (DBA) and Paper-Based Assessment (PBA)Samples . 71
Developing New Indices to Measure Digital Technology Access and FamiliarityExecutive SummaryThe National Assessment of Educational Progress (NAEP) is in the process oftransitioning from being a paper-based assessment (PBA) to a digitally basedassessment (DBA). An important issue is the degree to which all children are readyfor the move and whether any of NAEP’s reporting subpopulations are beingdisadvantaged by the transition. If technology access and familiarity are correlatedwith NAEP DBA performance and if there is differential access to digitaltechnology, this could lead to results that differ from PBA, which has been used toassess trends since 1990 for mathematics and 1992 for reading.To investigate these issues, we developed a new set of survey items measuring accessto, familiarity with, and self-efficacy for digital technology. A common set of itemsmeasuring access to and familiarity with digital technology and a measure of selfefficacy in dealing with digital technology were developed for Grades 4, 8 and 12.Additional items dealing with more advanced uses of digital technology as well as ameasure of familiarity with digital concepts were developed for the Grade 8 and 12samples. The item set measuring familiarity with digital concepts also included itemswith some fictitious digital concepts that allowed the study to assess the degree towhich students were overclaiming knowledge of digital concepts.The items were administered as a special study as part of the 2015 NAEP usingsamples of schools from the operational PBA administration and the DBA start-upadministration. The study examined five major research questions:1. Do the access, familiarity, and self-efficacy items cluster together in ways thatsuggest that reliable indices of each can be constructed?2. Are access, familiarity, and self-efficacy differentially distributed across gender,race/ethnicity, and/or socioeconomic status (SES)?3. What is the relationship between access, familiarity, and self-efficacy andperformance on NAEP?4. Is there differential validity of the indices in predicting NAEP performanceacross modes of administration?5. Do the observed relationships between indices and NAEP performance changewhen controlling for SES and other student characteristics?The first research question was examined using exploratory and confirmatory factoranalyses. The results from these analyses indicated that both the access andfamiliarity domains are multidimensional. For the access domain, two factors wereidentified that were interpreted as “access at home” and “access at school.” For thefamiliarity domain, three factors were identified, “familiarity through instruction,”“familiarity through computer use,” and “familiarity through tablet use,” and twoadditional factors at Grades 8 and 12, “familiarity with digital concepts” and“overclaiming of familiarity with digital concepts.” The factor analyses indicated thata single factor described the “self-efficacy with digital technology” items. Indiceswere built for each of the factors observed and the reliabilities for each computed.The reliability estimates for the indices were in the acceptable range for all the factors1
Developing New Indices to Measure Digital Technology Access and Familiarityat all grades except for those associated with the “access at home” and “access atschool” factors, both of which were based on only a few items.Means were computed for the indices by grade level to examine whether access,familiarity, and self-efficacy differentially distributed across gender, race/ethnicity,and SES. We did not find substantial differences (statistically significant and greaterthan 0.2 standard deviations) between male and female students. Nor did we findevidence that Black and Hispanic students were disadvantaged because of a lack ofaccess to digital technology either at home or at school. Although not anticipated,disadvantaged students were much more likely to indicate familiarity with digitaltechnology through the use of tablets, and to a lesser extent through the use ofcomputers, than their more advantaged counterparts. However, we did find thatdisadvantaged subpopulations generally reported lower digital self-efficacy and lessfamiliarity with digital concepts than nondisadvantaged students.Regression analyses were used to examine the third and main research question—therelationship between access, familiarity, and self-efficacy and performance on NAEP.The expectation was that relationships between the indices of access and familiaritywith digital technology and NAEP scores would be positive. Although some indiceswere positively related (especially strongly related were familiarity with digitalconcepts and self-efficacy), others were negatively related (access at school,familiarity through computer use, familiarity through tablet use) and the relationshipof access to NAEP scores was in all cases but one not statistically significant.Regression analyses also were used to examine the fourth research question—whether there was differential validity for the indices in predicting NAEPperformance across modes of administration. We did not observe that associationsbetween the digital technology access, familiarity, and self-efficacy indices and NAEPscores varied much across the DBA and PBA samples. In most cases, differenceswere not statistically significant and, when differences were observed, they oftenwere in the opposite direction from that which was hypothesized.Finally, in examining research question 5, we did not observe any significantdifferences between the DBA and PBA samples in the estimated associationsbetween the indices and NAEP achievement when controlling for potentiallyimportant sociodemographic characteristics of students.In summary, the hypothesis that student access and familiarity with digital technologywould be related to student performance was not substantiated in this study. Indeed,some of the relationships went in the opposite direction from that hypothesized; this wasespecially true for the use of tablets in school. One possibility is that digital technology(especially tablets) is being used as an alternative opportunity to learn for low-performingstudents in some schools and, if so, giving a child work on a tablet could be associatedwith low prior achievement. If it is the case that laptops, and especially tablets, are beingused for teaching low-performing students, prior achievement would be an omittedvariable in our analysis. Not only would prior achievement be linked positively toclassroom tablet (or laptop) use, but also negatively to NAEP performance. This, in turn,could lead to a negative observed relationship between an index such as tablet familiarityand NAEP performance. The study has been repeated as part of the 2017 NAEPassessment, which will allow an examination of the replicability of the 2015 results.2
Developing New Indices to Measure Digital Technology Access and FamiliarityIntroductionThe National Assessment of Educational Progress (NAEP) is in the process oftransitioning from being a paper-based assessment (PBA) to a digitally basedassessment (DBA). An important issue is the degree to which all children are readyfor the move and whether any of NAEP’s reporting subpopulations are beingdisadvantaged by the transition. If technology access and familiarity are correlatedwith NAEP DBA performance and if there is differential access to digitaltechnology, this could lead to results that differ from PBA, which has been used toassess trends since 1990 for mathematics and 1992 for reading.To investigate these issues, we developed a new set of survey items measuring accessto, familiarity with, and self-efficacy for digital technology. Although the primaryfocus of the study is on access to and familiarity with digital technology, we alsoadded items to measure self-efficacy for digital technology to the survey because arecent American Institutes for Research (AIR) study (Broer, Park, Bohrnstedt, &Kim, 2015) showed that digital self-efficacy was significantly related to performanceon the 2013 NAEP Technology and Engineering Literacy (TEL) pilot assessmentnet of other contextual factors.The items were administered as a special study as part of the 2015 operational NAEPadministration using samples of schools in which some schools were administeredthe PBA version of NAEP and others the DBA version. Using the responses to thenew survey items, we first explored whether students have differential access to,familiarity with, and experience with the digital devices, particularly whether there isdifferential access for disadvantaged students (e.g., those with low socioeconomicstatus [SES], minority students). Second, we used responses to the new survey, aswell as NAEP cognitive items, to understand the relationship between digitaltechnology access, familiarity, and self-efficacy with performance on NAEP in boththe PBA and DBA modes of administration.Specifically, the study examined five major research questions:1. Do the access, familiarity, and self-efficacy items cluster together in ways thatsuggest that reliable indices of each can be constructed?2. Are access, familiarity, and self-efficacy differentially distributed across gender,race/ethnicity, and/or SES?3. What is the relationship between access, familiarity, and self-efficacy andperformance on NAEP?4. Is there differential validity of the indices in predicting NAEP performanceacross modes of administration?5. Do the observed relationships between indices and NAEP performance changewhen controlling for SES and other student characteristics?BackgroundNAEP has been a paper-and-pencil assessment since its inception, but that hasbegun to change. Prior to the 2015 study reported here, there were three NAEPassessments administered by computer, beginning in 2011 with the Grades 8 and 123
Developing New Indices to Measure Digital Technology Access and Familiaritywriting assessments. There also was a small Mathematics Computer-Based Study(MCBS) in 2011, and the Technology and Engineering Literacy (TEL) assessmentwas administered by computer in 2104. For the 2015 study reported here, the NAEPresults from the operational assessments in mathematics, reading, and science werebased on PBA versions, but equivalent samples of students took the assessments ontablets, and analyses were carried by the NAEP contractor, Educational TestingService (ETS), to examine for mode effects on performance. The operational 2017NAEP assessments in mathematics, reading, and writing were all given on tablets; inaddition, a sample of students in each state took the assessment using paper andpencil to assess possible mode effects in the states. A sample of schools was drawnin which all students were again given the items developed for the study reportedhere and where some of the students took the PBA version of the operational testand others the DBA version. These data will allow the National Validity StudiesPanel (NVS Panel), in a separate report, to determine if the results found here arereplicated with the 2017 study data.Given the growth in technology in society as well as in the classroom, takingassessments online is not new. The Graduate Record Examination (GRE) and theArmed Forces Vocational Aptitude Battery (ASVAB) have had online versions oftheir tests for several years. A few states had been administering their achievementtests using a digital platform prior to 2015, but online state testing accelerated greatlywith the move to Common Core State Standards (CCSS) testing. Both of the CCSStesting consortia, the Smarter Balanced Assessment Consortium (Smarter Balanced)and the Partnership for Assessment of Readiness for College and Careers (PARCC),delivered the vast majority of their assessments on desktops or laptops in 2015 and2016, although there also was a paper-and-pencil version available for those schoolsthat did not yet have the infrastructure to support computer-based assessments.Thus, the NAEP transition to a DBA is very much in step with the way that largescale testing of elementary and secondary students is moving in this country.Although there are important concerns about mode effects and maintaining trend inNAEP scores, the National Center for Education Statistics (NCES) is addressingthese issues in other lines of research. An additional validity issue, addressed by thisstudy, is the extent to which the change in mode might impact students with lessexposure to digital technology, particularly NAEP’s reporting subgroups. In theremainder of this section, we summarize what we know from the literature aboutstudent access to and familiarity with digital technology in the United States, andhow these factors might relate to performance assessments.Student Access to TechnologyIn the standard contextual questionnaires administered with NAEP, students were askedabout home access to a computer and an Internet connection (two separate questions).Looking at variation by race/ethnicity in the 2015 mathematics and reading assessmentsat Grade 8, 92 percent of White students reported having access to a computer at homecompared with 83 percent and 82 percent for Black and Hispanic students, respectively.When examining Internet access at home, the pattern of results is the same, although thedifference is smaller—96 percent of White students in Grade 8 reported having accesscompared with 95 percent of Black students and 93 percent of Hispanic students.4
Developing New Indices to Measure Digital Technology Access and FamiliarityAt Grade 4, 88 percent of White students indicated that they had a computer athome compared with 76 percent of Black students and 77 percent of Hispanicstudents. For Internet access, the comparable figures are 89 percent for Whites, 75percent for Blacks, and 74 percent for Hispanics. Comparing these numbers with theGrade 8 results suggests there is a larger “digital divide” at Grade 4 than at Grade 8.As NAEP does not ask students about income, it was not possible to examine itsrelationship to computer access at home. However, the Teenage Research Unlimited(TRU) study (described in more detail below) found that use of technology in thehome varied as a function of household income. For example, 21 percent of thosefrom households with incomes less than 25,000 per year reported using a tablet athome compared with 49 percent who reported household incomes of 50,000 peryear or greater. Access to the Internet at home was broken out by whether studentswere in Title I or non-Title I schools. For students in Grades 3–5, 94 percent at nonTitle I schools reported having Internet access at home compared with 87 percentfor those in Title I schools. In Grades 6–8, the comparable figures were 96 percentand 90 percent, respectively, while in Grades 9–12, they were 95 percent and 91percent, respectively. That is, although there were differences in Internet access byTitle I school status, the vast majority of all students reported having Internet access.The report did not break out results by race/ethnicity.The 2015 Project Tomorrow study, based on more than 430,000 K–12 studentresponses collected in 2014 in over 8,000 schools (Project Tomorrow, 2015) indicatesthat 23 percent of those in Grades 6–8 and 58 percent of those in Grades 9–12 reportedusing their own devices in school. Thirty-four percent of those in Grades 6–8 and 32percent of those in Grades 9–12 said they use school-issued laptops. The figures forschool-issued tablets are 21 percent (Grades 6–8) and 14 percent (Grades 9–12).Although lower SES families may have high access to the Internet, the quality ofaccess may vary considerably according to a study carried out by the Joan GanzCooney Center at Sesame Workshop of 1,991 families living below the medianincome level (Rideout & Katz, 2016). In the words of the study’s authors: “Many[lower income] families face limitations in the form of service cutoffs, slow service,older technology, or difficulty using equipment because too many people are sharingdevices”(p. 10). For example, nearly a third of these families rely solely on mobileaccess. And among these, roughly a quarter reported having service cutoff, nearly 30percent said that they have hit limits on the amount of service available given theirservice plans, and about 20 percent indicated that there were challenges using theInternet because of the number of persons in the family sharing the mobile device.Student Familiarity With TechnologyCompared with access to technology, there appear to be significantly fewer studiesthat have examined student familiarity with technology indirectly, and none that haveexamined it directly, including its relationship to taking a test on a digital device.The TRU study, mentioned briefly above, is a national online survey of 1,000 sixth,seventh, and eighth graders (i.e., middle school students), which was carried out byVerizon in the fall of 2012 (Sarmiento & Glauber, 2012). The study does not purport5
Developing New Indices to Measure Digital Technology Access and Familiarityto examine familiarity, but its findings clearly are related to it. For example, the studyfound that 64 percent of students had used a laptop to complete homeworkassignments and nearly 45 percent did so on at least a weekly basis. Use and itsfrequency are logically related to familiarity. Also, nearly 40 percent of students hadused smartphones to do homework. Interestingly, the study also revealed that moreHispanics (38 percent) and African Americans (27 percent) reported using theirsmartphones for doing homework on a weekly basis or more than did Whitestudents (24 percent). The figures for tablet use for homework on a weekly basis ormore follow the same pattern—Hispanics (32 percent), Blacks (26 percent), andWhites (24 percent). Roughly half of those who reported using tablets in class saidthey bring their own devices to school. The TRU study also found that not allschools encourage the use of technology: 66 percent of students reported that theywere not allowed to use tablets in class, and 88 percent were not allowed to usesmartphones.A couple of things about the TRU survey need to be noted. First, the survey wasconducted online, which means that the sample was biased toward those who hadonline access. That is, it was not a random sample of students. Second, a quotasample based on household income was used to ensure that low-income studentswere included and that the male-female distribution was 50-50. However, it appearsthat quotas were not used for race/ethnicity. For these reasons, it is not certain howmuch weight to put on the results of the study.A second, somewhat relevant study was carried out by the Kaiser Family Foundation(Rideout, Foehr, & Roberts, 2010). It examined media use by 8- to 18-year-olds in1999, 2004, and 2009 using representative national samples. As might be expectedgiven the explosion in technology in the United States, media use in general was upfor all groups of children from 1999 to 2009. Computer and Internet use were partof the definition of media use in their study, but only one question dealt with the useof computers for schoolwork and, unfortunately, the results were not broken out byrace/ethnicity or family SES. Interestingly, the study found that total computer use(as well as all media use when it was summed together) was highest among Blacks,followed by Hispanics; White children reported the lowest amount of use. Althoughthese results suggest that minority children in 2009 were more likely to use mediathan White children overall, the study unfortunately does not tell us anything abouthow these groups used technology for schoolwork.Using a different but relevant measure of familiarity, teachers in the 2017 ProjectTomorrow study reported that 50 percent of students in Grades 6–8 and 49 percent ofthose in Grades 9–12 reported taking tests online.In summary, no studies could be found that measured familiarity with technologydirectly. The TRU study indicates that significant percentages of students usecomputers, tablets, and smartphones in doing their schoolwork and homework. Oneof the interesting findings of the Kaiser Family Foundation study was that Blackshad the highest computer use, followed by Hispanics and then Whites. Also ofinterest was the 2017 Project Tomorrow findings that about 50 percent of studentshad taken a test online in middle and high school.6
Developing New Indices to Measure Digital Technology Access and FamiliarityDigital Technology Versus the Use of Paper and Pencil forTest TakingThe jury is out on the effects of a DBA versus a PBA in assessing performance. Asreported in a recent comprehensive review of the literature by the Council of ChiefState School Officers (CCSSO; DePascale, Dadey, & Lyons, 2016), recent metaanalyses have shown mode effects to be either small or nonsignificant (Kingston,2009; Wang, Jiao, Young, Brooks, & Olson, 2007, 2008). The CCSSO report goes onto note, however, that some of the studies suggest that taking tests using digitaltechnology may disadvantage at least some students, and the differences may vary bycontent area. More specifically, they note that when differences were found, thosetaking the test using digital technology were more likely to score higher when takingan English language arts or social science test, and those taking a mathematics testdid better when taking it by paper and pencil. A study by PARCC, as discussed in anEducation Week blog (Herold, June 10, 2016), reports that of the roughly 5 millionstudents who took the 2014–15 PARCC assessment, students who took theassessments on the computer did worse, on average, than those who took it withpaper and pencil.In recent years two sets of experiments have been undertaken comparing studentperformance depending upon whether notetaking is done on a laptop versus paperand pencil. One was an introductory economics study at the U.S. Military Academyat We
To investigate these issues, we developed a new set of survey items measuring access to, familiarity with, and self-efficacy for digital technology. A common set of items measuring access to and familiarity with digital technology and a measure of self - efficacy in dealing with digital technology were developed for G rades 4, 8 and 12.
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