The Individualized Student Instruction (ISI) intervention was designed to help teachers increase their use of differentiated core reading instruction, to optimize student growth by providing appropriate amounts of code- and meaning-focused instruction. Based on the results from original studies on ISI, it is still unclear if differentiated instruction can mitigate the influence of individual differences, and if this is similar for all students. Using integrative data analytic techniques, we combined data from six randomized control trials on the ISI intervention conducted in kindergarten and first grade and obtained a dataset with a total sample of 3,144 students in Grades K and 1. We then fit conditional multilevel quantile regression models to examine differential effects on word reading and vocabulary outcomes and the moderating effect of pre-intervention skills. The model coefficients did not indicate a treatment effect of the ISI intervention on either vocabulary or word reading skills. We discuss these results in the light of the importance of data sharing and registered reports to uncover what works for which students under which conditions.
Al OtaibaS.ConnorC. M.FolsomJ. S.GreulichL.MeadowsJ.LiZ. (2011). Assessment data–informed guidance to individualize kindergarten reading instruction: Findings from a cluster-randomized control field trial. The Elementary School Journal, 111(4), 535–560. https://doi.org/10.1086/659031
2.
Al OtaibaS.ConnorC. M.FolsomJ. S.WanzekJ.GreulichL.SchatschneiderC.WagnerR. K. (2014). To wait in tier 1 or intervene immediately: A randomized experiment examining first-grade response to intervention in reading. Exceptional Children, 81(1), 11–27. https://doi.org/10.1177/0014402914532234
3.
Al OtaibaS.FolsomJ. S.WanzekJ.GreulichL.WaescheJ.SchatschneiderC.ConnorC. M. (2016). Professional development to differentiate kindergarten tier 1 instruction: Can already effective teachers improve student outcomes by differentiating tier 1 instruction?Reading & Writing Quarterly, 32(5), 454–476. https://doi.org/10.1080/10573569.2015.1021060
4.
Al OtaibaS.FuchsD. (2002). Characteristics of children who are unresponsive to early literacy intervention: A review of the literature. Remedial and Special Education, 23(5), 300–316. https://doi.org/10.1177/07419325020230050501
5.
BarchardK. A.FreemanA. J.OchoaE.StephensA. K. (2020). Comparing the accuracy and speed of four data-checking methods. Behavior Research Methods, 52(1), 97–115. https://doi.org/10.3758/s13428-019-01207-3
6.
BaumannJ. F. (2009). Intensity in vocabulary instruction and effects on reading comprehension. Topics in Language Disorders, 29(4), 312–328. https://doi.org/10.1097/TLD.0b013e3181c29e22
7.
BenjaminiY.HochbergY. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
8.
BuurenS. v.Groothuis-OudshoornK. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. https://doi.org/10.18637/jss.v045.i03
9.
CattsH. W. (2018). The simple view of reading: Advancements and false impressions. Remedial and Special Education, 39(5), 317–323. https://doi.org/10.1177/0741932518767563
10.
CattsH. W.AdlofS. M.WeismerS. E. (2006). Language deficits in poor comprehenders: A case for the simple view of reading.
11.
ColenbranderD.KohnenS.Smith-LockK.NickelsL. (2016). Individual differences in the vocabulary skills of children with poor reading comprehension. Learning and Individual Differences, 50, 210–220. https://doi.org/10.1016/j.lindif.2016.07.021
12.
ConnorC. M.JakobsonsL.CroweE. C.MeadowsJ. G. (2009). Instruction, student engagement, and reading skill growth in reading first classrooms. The Elementary School Journal, 109(3), 221–250. https://doi.org/10.1086/592305
13.
ConnorC. M.MorrisonF. J.FishmanB.CroweE. C.Al OtaibaS.SchatschneiderC. (2013). A longitudinal cluster-randomized controlled study on the accumulating effects of individualized literacy instruction on students’ reading from first through third grade. Psychological Science, 24(8), 1408–1419. https://doi.org/10.1177/0956797612472204
14.
ConnorC. M.MorrisonF. J.FishmanB.GiulianiS.LuckM.UnderwoodP. S.BayraktarA.CroweE. C.SchatschneiderC. (2011). Testing the impact of child characteristics × instruction interactions on third graders’ reading comprehension by differentiating literacy instruction. Reading Research Quarterly, 46(3), 189–221. https://doi.org/10.1598/RRQ.46.3.1
ConnorC. M.MorrisonF. J.KatchL. E. (2004). Beyond the reading wars: Exploring the effect of child-instruction interactions on growth in early reading. Scientific Studies of Reading, 8(4), 305–336. https://doi.org/10.1207/s1532799xssr0804_1
17.
ConnorC. M.MorrisonF. J.PetrellaJ. N. (2004). Effective reading comprehension instruction: Examining child x instruction interactions. Journal of Educational Psychology, 96(4), 682–698. https://doi.org/10.1037/0022-0663.96.4.682
18.
ConnorC. M.MorrisonF. J.SchatschneiderC.TosteJ.LundblomE.CroweE. C.FishmanB. (2011). Effective classroom instruction: Implications of child characteristics by reading instruction interactions on first graders’ word reading achievement. Journal of Research on Educational Effectiveness, 4(3), 173–207. https://doi.org/10.1080/19345747.2010.510179
19.
ConnorC. M.PiastaS. B.FishmanB.GlasneyS.SchatschneiderC.CroweE.UnderwoodP.MorrisonF. J. (2009). Individualizing student instruction precisely: Effects of child x instruction interaction on first graders’ literacy development. Child Development, 80(2), 77–100. https://doi.org/10.1111/j.1467-8624.2008.01247.x
20.
CookB. G.MagginD. M.RobertsonR. E. (2021). Registered reports in special education: Introduction to the special series. Remedial and Special Education, 42(3), 131–139. https://doi.org/10.1177/0741932521996459
21.
CoyneM. D.CookB. G.TherrienW. J. (2016). Recommendations for replication research in special education: A framework of systematic, conceptual replications. Remedial and Special Education, 37(4), 244–253. https://doi.org/10.1177/0741932516648463
22.
CoyneM. D.McCoachD. B.WareS.AustinC. R.Loftus-RattanS. M.BakerD. L. (2019). Racing against the vocabulary gap: Matthew effects in early vocabulary instruction and intervention. Exceptional Children, 85(2), 163–179. https://doi.org/10.1177/0014402918789162
23.
CurranP. J.HussongA. M. (2009). Integrative data analysis: The simultaneous analysis of multiple data sets. Psychological Methods, 14(2), 81–100. https://doi.org/10.1037/a0015914
24.
CurranP. J.McGinleyJ. S.BauerD. J.HussongA. M.BurnsA.ChassinL.SherK.ZuckerR. (2014). A moderated nonlinear factor model for the development of commensurate measures in integrative data analysis. Multivariate Behavioral Research, 49(3), 214–231. https://doi.org/10.1080/00273171.2014.889594
25.
DaucourtM. C.SchatschneiderC.ConnorC. M.Al OtaibaS.HartS. A. (2018). Inhibition, updating working memory, and shifting predict reading disability symptoms in a hybrid model: Project KIDS. Frontiers in Psychology, 9(238), 1–16.https://doi.org/10.3389/fpsyg.2018.00238
26.
DongN.KelceyB.SpybrookJ.MaynardR. A. (2016). PowerUpR (Version 1.0.4) [Computer software]. powerupr.shinyapps.io/index/.
27.
EhriL. C.NunesS. R.StahlS. A.WillowsD. M. (2001). Systematic phonics instruction helps students learn to read: Evidence from the national reading panel’s meta-analysis. Review of Educational Research, 71(3), 393–447. https://doi.org/10.3102/00346543071003393
28.
ErringtonT. M.MathurM.SoderbergC. K.DenisA.PerfitoN.IornsE.NosekB. A. (2021). Investigating the replicability of preclinical cancer biology. eLife, 10, Article e71601. https://doi.org/10.7554/eLife.71601
FoormanB. R.KoonS.PetscherY.MitchellA.TruckenmillerA. (2015). Examining general and specific factors in the dimensionality of oral language and reading in 4th–10th grades. Journal of Educational Psychology, 107(3), 884–899. https://doi.org/10.1037/edu0000026
31.
FoormanB. R.MoatsL. C. (2004). Conditions for sustaining research-based practices in early reading instruction. Remedial and Special Education, 25(1), 51–60. https://doi.org/10.1177/07419325040250010601
32.
FoormanB. R.SchatschneiderC. (2003). Measurement of teaching practices during reading/language arts instruction and its relationship to student achievement. In VaughnS.BriggsK. L. (Eds.), Reading in the Classroom: Systems for the Observation of Teaching and Learning (pp. 1–30). Brookes.
33.
FuchsD.FuchsL. S. (2019). On the importance of moderator analysis in intervention research: An introduction to the special issue. Exceptional Children, 85(2), 126–128. https://doi.org/10.1177/0014402918811924
34.
FuchsD.KearnsD. M.FuchsL. S.EllemanA. M.GilbertJ. K.PattonS.PengP.ComptonD. L. (2019). Using moderator analysis to identify the first-grade children who benefit more and less from a reading comprehension program: A step toward aptitude-by-treatment interaction. Exceptional Children, 85(2), 229–247. https://doi.org/10.1177/0014402918802801
35.
GarcíaJ. R.CainK. (2014). Decoding and reading comprehension: A meta-analysis to identify which reader and assessment characteristics influence the strength of the relationship in English. Review of Educational Research, 84(1), 74–111. https://doi.org/10.3102/0034654313499616
GottfredsonN. C.ColeV. T.GiordanoM. L.BauerD. J.HussongA. M.EnnettS. T. (2019). Simplifying the implementation of modern scale scoring methods with an automated R package: Automated moderated nonlinear factor analysis (aMNLFA). Addictive Behaviors, 94, 65–73. https://doi.org/10.1016/j.addbeh.2018.10.031
Hagan-BurkeS.CoyneM. D.KwokO.SimmonsD. C.KimM.SimmonsL. E.SkidmoreS. T.HernandezC. L.McSparran RubyM. (2013). The effects and interactions of student, teacher, and setting variables on reading outcomes for kindergarteners receiving supplemental reading intervention. Journal of Learning Disabilities, 46(3), 260–277. https://doi.org/10.1177/0022219411420571
HartS. A.SchatschneiderC.ReynoldsT.CalvoF. (2024). A community data sharing resource: The LDbase data repository. Journal of Learning Disabilities, 57(6), 411–416. https://doi.org/10.1177/00222194241254091
42.
HartS. A.SchatschneiderC.ReynoldsT. R.CalvoF. E.BrownB. J.ArsenaultB.HallM. R. K.van DijkW.EdwardsA.SheroJ. A.SmartR.PhillipsJ. S. (2020). LDbase. http://doi.org/10.33009/ldbase.
43.
HedgesL. V. (2007). Correcting a significance test for clustering. Journal of Educational and Behavioral Statistics, 32(2), 151–179. https://doi.org/10.3102/1076998606298040
HornburgC. B.RieberM. L.McNeilN. M. (2017). An integrative data analysis of gender differences in children’s understanding of mathematical equivalence. Journal of Experimental Child Psychology, 163, 140–150. https://doi.org/10.1016/j.jecp.2017.06.002
46.
JansenM.LüdtkeO.RobitzschA. (2020). Disentangling different sources of stability and change in students’ academic self-concepts: An integrative data analysis using the STARTS model. Journal of Educational Psychology, 112, 1614–1631. https://doi.org/10.1037/edu0000448
47.
KendeouP.Van den BroekP.WhiteM. J.LynchJ. S. (2009). Predicting reading comprehension in early elementary school: The independent contributions of oral language and decoding skills. Journal of Educational Psychology, 101(4), 765–778. https://doi.org/10.1037/a0015956
48.
KillewaldA.BearakJ. (2014). Is the motherhood penalty larger for low-wage women? A comment on quantile regression. American Sociological Review, 79(2), 350–357. https://doi.org/10.1177/0003122414524574
49.
KoenkerR. (2017). Quantile regression 40 years on. The IFS.
50.
KoenkerR.BassettG. (1978). Regression quantiles. Econometrica: Journal of the Econometric Society, 46, 33–50. https://doi.org/10.2307/1913643
51.
LamE. A.McMasterK. L. (2014). Predictors of responsiveness to early literacy intervention: A 10-year update. Learning Disability Quarterly, 37(3), 134–147. https://doi.org/10.1177/0731948714529772
52.
LeijtenP.RaaijmakersM.WijngaardsL.MatthysW.MentingA.Hemink-van PuttenM.Orobio de CastroB. (2018). Understanding who benefits from parenting interventions for children’s conduct problems: An integrative data analysis. Prevention Science, 19(4), 579–588. https://doi.org/10.1007/s11121-018-0864-y
53.
LoniganC. J.BurgessS. R.SchatschneiderC. (2018). Examining the simple view of reading with elementary school children: Still simple after all these years. Remedial and Special Education, 39(5), 260–273. https://doi.org/10.1177/0741932518764833
54.
LovettM. W.FrijtersJ. C.WolfM.SteinbachK. A.SevcikR. A.MorrisR. D. (2017). Early intervention for children at risk for reading disabilities: The impact of grade at intervention and individual differences on intervention outcomes. Journal of Educational Psychology, 109(7), 889–914. https://doi.org/10.1037/edu0000181
MarulisL. M.NeumanS. B. (2010). The effects of vocabulary intervention on young children’s word learning. Review of Educational Research, 80(3), 300–335. https://doi.org/10.3102/0034654310377087
57.
McGrewK. S.SchrankF. A.WoodcockR. W. (2007). Technical Manual. Woodcock-Johnson III normative update. Riverside Publishing.
58.
NationK. (2019). Children’s reading difficulties, language, and reflections on the simple view of reading. Australian Journal of Learning Difficulties, 24(1), 47–73. https://doi.org/10.1080/19404158.2019.1609272
59.
National Center for Education Statistics. (2019). The condition of education 2018. (NCES 2018-144). Government Printing Office.
60.
National Institute of Child Health and Human Development (NICHD). (2000). Report of the national reading panel: teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction: Reports of the subgroups (NIH 00-4754). U.S. Government Printing Office.
61.
OakhillJ. V.CainK. (2012). The precursors of reading ability in young readers: Evidence from a four-year longitudinal study. Scientific Studies of Reading, 16(2), 91–121. https://doi.org/10.1080/10888438.2010.529219
OuelletteG.BeersA. (2010). A not-so-simple view of reading: How oral vocabulary and visual-word recognition complicate the story. Reading and Writing, 23(2), 189–208. https://doi.org/10.1007/s11145-008-9159-1
64.
PellegriniA. (2001). Some theoretical and methodological considerations in studying literacy in social context. Handbook of Early Literacy Research, 1, 54–65.
65.
PetscherY.LoganJ. A. R. (2014). Quantile regression in the study of developmental sciences. Child Development, 85(3), 861–881. https://doi.org/10.1111/cdev.12190
66.
PorterS. R. (2015). Quantile regression: Analyzing changes in distributions instead of means. In PaulsenM. B. (Ed.), Higher education: Handbook of theory and research (pp. 335–381). Springer International Publishing.
67.
R Core Team. (2020). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. https://www.R-project.org/.
68.
RhoadsC. H. (2012). Problems with Tests of the Missingness Mechanism in Quantitative Policy Studies. Statistics, Politics, and Policy, 3(1). https://doi.org/10.1515/2151-7509.1012
69.
RobertsG. J.VaughnS.RobertsG.MiciakJ. (2019). Problem behaviors and response to reading intervention for upper elementary students with reading difficulties. Remedial and Special Education, 42, 169–181. https://doi.org/10.1177/0741932519865263
70.
RubinD. B. (2004). Multiple imputation for nonresponse in surveys (Vol. 81). John Wiley & Sons.
71.
RubinM.DonkinC. (2024). Exploratory hypothesis tests can be more compelling than confirmatory hypothesis tests. Philosophical Psychology, 37(8), 2019–2047. https://doi.org/10.1080/09515089.2022.2113771
72.
SabatiniJ. (2015). Understanding the basic reading skills of US adults: Reading components in the PIAAC literacy survey. ETS Center for Research on Human Capital and Education.
73.
SilberzahnR.UhlmannE. L.MartinD. P.AnselmiP.AustF.AwtreyE.BahníkŠBaiF.BannardC.BonnierE.CarlssonR.CheungF.ChristensenG.ClayR.CraigM. A.Dalla RosaA.DamL.EvansM. H.Flores CervantesI.NosekB. A. (2018). Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychological Science, 1(3), 337–356. https://doi.org/10.1177/2515245917747646
74.
SimmonsD. C.TaylorA. B.OslundE. L.SimmonsL. E.CoyneM. D.LittleM. E.RawlinsonD. M.Hagan-BurkeS.KwokO.KimM. (2014). Predictors of at-risk kindergarteners’ later reading difficulty: Examining learner-by-intervention interactions. Reading and Writing, 27(3), 451–479. https://doi.org/10.1007/s11145-013-9452-5
75.
SnowC. E. (2002). Reading for understanding: Toward an R&D program in reading comprehension. Rand Corporation.
76.
SnowC. E.PorcheM. V.TaborsP. O.HarrisS. R. (2007). Is literacy enough? Pathways to academic success for adolescents. Brookes.
77.
SolariE. J.DentonC. A.PetscherY.HaringC. (2018). Examining the effects and feasibility of a teacher-implemented tier 1 and tier 2 intervention in word reading, fluency, and comprehension. Journal of Research on Educational Effectiveness, 11(2), 163–191. https://doi.org/10.1080/19345747.2017.1375582
78.
StanovichK. E. (1986). Matthew effects in reading: Some consequences of the individual differences in the acquisition of reading. Reading Research Quarterly, 21, 360–407. https://doi.org/10.1598/RRQ.21.4.1
79.
VadasyP. F.SandersE. A.AbbottR. D. (2008). Effects of supplemental early reading intervention at 2-year follow up: Reading skill growth patterns and predictors. Scientific Studies of Reading, 12(1), 51–89. https://doi.org/10.1080/10888430701746906
80.
van DijkW.NorrisC. U.OtaibaS. A.SchatschneiderC.HartS. A. (2022). Exploring individual differences in response to reading intervention: Data from Project KIDS (Kids and Individual Differences in Schools). Journal of Open Psychology Data, 10(2), 1–10.https://doi.org/10.5334/jopd.58
81.
van DijkW.SchatschneiderC.Al OtaibaS.HartS. A. (2023). Student behavior ratings and response to tier 1 reading intervention: Which students do not benefit?Journal of Research on Educational Effectiveness, 17(3), 491–512. https://doi.org/10.1080/19345747.2023.2194894
82.
van DijkW.SchatschneiderC.HartS. A. (2021). Open science in education sciences. Journal of Learning Disabilities, 54(2), 139–152. https://doi.org/10.1177/0022219420945267
83.
WanzekJ.PetscherY.Al OtaibaS.KentS. C.SchatschneiderC.HaynesM.RivasB. K.JonesF. G. (2016). Examining the average and local effects of a standardized treatment for fourth graders with reading difficulties. Journal of Research on Educational Effectiveness, 9(Suppl. 1), 45–66. https://doi.org/10.1080/19345747.2015.1116032
WolffU. (2016). Effects of a randomized reading intervention study aimed at 9-year-olds: A 5-year follow-up. Dyslexia, 22(2), 85–100. https://doi.org/10.1002/dys.1529
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