iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: http://pubmed.ncbi.nlm.nih.gov/37131926/
Targeted school-based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K-6: A systematic review - PubMed Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021 Apr 6;17(2):e1152.
doi: 10.1002/cl2.1152. eCollection 2021 Jun.

Targeted school-based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K-6: A systematic review

Jens Dietrichson  1 , Trine Filges  1 , Julie K Seerup  1 , Rasmus H Klokker  1 , Bjørn C A Viinholt  1 , Martin Bøg  2 , Misja Eiberg  1
Affiliations
Review

Targeted school-based interventions for improving reading and mathematics for students with or at risk of academic difficulties in Grades K-6: A systematic review

Jens Dietrichson et al. Campbell Syst Rev. .

Abstract

Background: Low levels of numeracy and literacy skills are associated with a range of negative outcomes later in life, such as reduced earnings and health. Obtaining information about effective interventions for children with or at risk of academic difficulties is therefore important.

Objectives: The main objective was to assess the effectiveness of interventions targeting students with or at risk of academic difficulties in kindergarten to Grade 6.

Search methods: We searched electronic databases from 1980 to July 2018. We searched multiple international electronic databases (in total 15), seven national repositories, and performed a search of the grey literature using governmental sites, academic clearinghouses and repositories for reports and working papers, and trial registries (10 sources). We hand searched recent volumes of six journals and contacted international experts. Lastly, we used included studies and 23 previously published reviews for citation tracking.

Selection criteria: Studies had to meet the following criteria to be included: Population: The population eligible for the review included students attending regular schools in kindergarten to Grade 6, who were having academic difficulties, or were at risk of such difficulties. Intervention: We included interventions that sought to improve academic skills, were conducted in schools during the regular school year, and were targeted (selected or indicated). Comparison: Included studies used an intervention-control group design or a comparison group design. We included randomised controlled trials (RCT); quasi-randomised controlled trials (QRCT); and quasi-experimental studies (QES). Outcomes: Included studies used standardised tests in reading or mathematics. Setting: Studies carried out in regular schools in an OECD country were included.

Data collection and analysis: Descriptive and numerical characteristics of included studies were coded by members of the review team. A review author independently checked coding. We used an extended version of the Cochrane Risk of Bias tool to assess risk of bias. We used random-effects meta-analysis and robust-variance estimation procedures to synthesise effect sizes. We conducted separate meta-analyses for tests performed within three months of the end of interventions (short-term effects) and longer follow-up periods. For short-term effects, we performed subgroup and moderator analyses focused on instructional methods and content domains. We assessed sensitivity of the results to effect size measurement, outliers, clustered assignment of treatment, risk of bias, missing moderator information, control group progression, and publication bias.

Results: We found in total 24,414 potentially relevant records, screened 4247 of them in full text, and included 607 studies that met the inclusion criteria. We included 205 studies of a wide range of intervention types in at least one meta-analysis (202 intervention-control studies and 3 comparison designs). The reasons for excluding studies from the analysis were that they had too high risk of bias (257), compared two alternative interventions (104 studies), lacked necessary information (24 studies), or used overlapping samples (17 studies). The total number of student observations in the analysed studies was 226,745. There were 93% RCTs among the 327 interventions we included in the meta-analysis of intervention-control contrasts and 86% were from the United States. The target group consisted of, on average, 45% girls, 65% minority students, and 69% low-income students. The mean Grade was 2.4. Most studies included in the meta-analysis had a moderate to high risk of bias.The overall average effect sizes (ES) for short-term and follow-up outcomes were positive and statistically significant (ES = 0.30, 95% confidence interval [CI] = [0.25, 0.34] and ES = 0.27, 95% CI = [0.17, 0.36]), respectively). The effect sizes correspond to around one third to one half of the achievement gap between fourth Grade students with high and low socioeconomic status in the United States and to a 58% chance that a randomly selected score of an intervention group student is greater than the score of a randomly selected control group student.All measures indicated substantial heterogeneity across short-term effect sizes. Follow-up outcomes pertain almost exclusively to studies examining small-group instruction by adults and effects on reading measures. The follow-up effect sizes were considerably less heterogeneous than the short-term effect sizes, although there was still statistically significant heterogeneity.Two instructional methods, peer-assisted instruction and small-group instruction by adults, had large and statistically significant average effect sizes that were robust across specifications in the subgroup analysis of short-term effects (ES around 0.35-0.45). In meta-regressions that adjusted for methods, content domains, and other study characteristics, they had significantly larger effect sizes than computer-assisted instruction, coaching of personnel, incentives, and progress monitoring. Peer-assisted instruction also had significantly larger effect sizes than medium-group instruction. Besides peer-assisted instruction and small-group instruction, no other methods were consistently significant across the analyses that tried to isolate the association between a specific method and effect sizes. However, most analyses showed statistically significant heterogeneity also within categories of instructional methods.We found little evidence that effect sizes were larger in some content domains than others. Fractions had significantly higher associations with effect sizes than all other math domains, but there were only six studies of interventions targeting fractions. We found no evidence of adverse effects in the sense that no method or domain had robustly negative associations with effect sizes.The meta-regressions revealed few other significant moderators. Interventions in higher Grades tend to have somewhat lower effect sizes, whereas there were no significant differences between QES and RCTs, general tests and tests of subdomains, and math tests and reading tests.

Authors’ conclusions: Our results indicate that interventions targeting students with or at risk of academic difficulties from kindergarten to Grade 6 have on average positive and statistically significant short-term and follow-up effects on standardised tests in reading and mathematics. Peer-assisted instruction and small-group instruction are likely to be effective components of such interventions.We believe the relatively large effect sizes together with the substantial unexplained heterogeneity imply that schools can reduce the achievement gap between students with or at risk of academic difficulties and not-at-risk students by implementing targeted interventions, and that more research into the design of effective interventions is needed.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Flowchart of the search and screening process
Figure 2
Figure 2
Number of intervention‐control studies included in the meta‐analysis by publication year
Figure 3
Figure 3
Number of intervention‐control studies included in the meta‐analysis by mean grade
Figure 4
Figure 4
Summary of risk of bias items for effect sizes included in the meta‐analysis
Figure 5
Figure 5
Distribution of short‐term effect sizes
Figure 6
Figure 6
Subgroup analyses: Weighted average effect sizes and 95% confidence intervals by instructional method
Figure 7
Figure 7
Subgroup analyses: Weighted average effect sizes and 95% confidence intervals by reading domain
Figure 8
Figure 8
Subgroup analyses: Weighted average effect sizes and 95% confidence intervals by math domain
Figure 9
Figure 9
Subgroup analyses: Weighted average effect sizes and 95% confidence intervals other content domains
Figure 10
Figure 10
Sensitivity analyses: Overall short‐term average effect size
Figure 11
Figure 11
Sensitivity analyses: Overall follow‐up average effect size
Figure 12
Figure 12
Sensitivity analyses: Peer‐assisted instruction
Figure 13
Figure 13
Sensitivity analyses: Small‐group instruction
Figure 14
Figure 14
Funnel plots of study‐level short‐term effect sizes (upper left corner), follow‐up effect sizes (upper right corner), peer‐assisted instruction effect sizes (lower left corner), and small‐group instruction effect sizes (lower right corner)
See this image and copyright information in PMC

Update of

  • PROTOCOL

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

INCLUDED STUDIES

    1. Al Otaiba, S. , Schatschneider, C. , & Silverman, E. (2005). Tutor‐assisted intensive learning strategies in kindergarten: How much is enough? Exceptionality, 13(4), 195–208.
    1. Al‐Hazza, T. C. (2002). An examination of the effects of the America Reads tutoring program and tutor training on the attitude and academic achievement of urban at‐risk minority students (Doctoral dissertation). Available from ProQuest Dissertations and Theses (UMI No. 3068649).
    1. Allor, J. , & McCathren, R. (2004). The efficacy of an early literacy tutoring program implemented by college students. Learning Disabilities Research and Practice, 19(2), 116–129.
    1. Allor, J. H. , Fuchs, D. , & Mathes, P. G. (2001). Do students with and without lexical retrieval weaknesses respond differently to instruction? Journal of Learning Disabilities, 34(3), 264–275. - PubMed
    1. Amendum, S. J. , Vernon‐Feagans, L. , & Ginsberg, M. C. (2011). The effectiveness of a technologically facilitated classroom‐based early reading intervention: The Targeted Reading Intervention. Elementary School Journal, 112(1), 107–131.

COMPARISON DESIGNS NOT INCLUDED IN THE META‐ANALYSIS

    1. Abbott, S. P. , & Berninger, V. W. (1999). It's never too late to remediate: Teaching word recognition to students with reading disabilities in grades 4–7. Annals of dyslexia, 49(1), 221–250.
    1. Anthony, J. L. (2016). For which children of economic disadvantage and in which instructional contexts does Earobics Step 1 improve kindergarteners’ literacy? Journal of Research on Educational Effectiveness, 9(1), 54–76.
    1. Baker, D. L. , Park, Y. , Baker, S. K. , Basaraba, D. L. , Kame'enui, E. J. , & Beck, C. T. (2012). Effects of a paired bilingual reading program and an English‐only program on the reading performance of English learners in Grades 1–3. Journal of School Psychology, 50(6), 737–758. - PubMed
    1. Baroody, A. J. , Eiland, M. D. , Purpura, D. J. , & Reid, E. E. (2013). Can computer‐assisted discovery learning foster first graders’ fluency with the most basic addition combinations? American Educational Research Journal, 50(3), 533–573.
    1. Berninger, V. W. , Abbott, R. D. , Brooksher, R. , Lemos, Z. , Ogier, S. , Zook, D. , & Mostafapour, E. (2000). A connectionist approach to making the predictability of English orthography explicit to at‐risk beginning readers: Evidence for alternative, effective strategies. Developmental Neuropsychology, 17(2), 241–271. - PubMed

OVERLAPPING SAMPLES

    1. Baker, S. K. , Smolkowski, K. , Chaparro, E. A. , Smith, J. L. , & Fien, H. (2015). Using regression discontinuity to test the impact of a tier 2 reading intervention in first grade. Journal of Research on Educational Effectiveness, 8(2), 218–244.
    1. Chaparro, E. A. , Smolkowski, K. , Baker, S. K. , Fien, H. , & Smith, J. L. M. (2012). An examination of treatment effects of a first grade literacy intervention using a regression discontinuity design (Evaluative Report). Society for Research on Educational Effectiveness. Retrieved from ERIC database (ED530445).
    1. Fien, H. , Smith, J. L. M. , Smolkowski, K. , Baker, S. K. , Nelson, N. J. , & Chaparro, E. (2015). An examination of the efficacy of a multitiered intervention on early reading outcomes for first grade students at risk for reading difficulties. Journal of Learning Disabilities, 48(6), 602–621. - PubMed
    1. Fives, A. (2016). Modeling the interaction of academic self‐beliefs, frequency of reading at home, emotional support, and reading achievement: An RCT study of at‐risk early readers in first grade and second grade. Reading Psychology, 37(3), 339–370.
    1. Foster, M. (2014). Structure of mathematics achievement and response to intervention in children with mild disabilities (Doctoral dissertation). Available from ProQuest Dissertations and Theses (UMI No. 3637676).

LACK INFORMATION

    1. Babinski, L. M. , Amendum, S. J. , Knotek, S. E. , Sánchez, M. , & Malone, P. (2018). Improving young English learners’ language and literacy skills through teacher professional development: A randomized controlled trial. American Educational Research Journal, 55(1), 117–143.
    1. Baenen, N. , Bernholc, A. , Dulaney, C. , & Banks, K. (1997). Reading Recovery: Long‐term progress after three cohorts. Journal of Education for Students Placed at Risk, 2(2), 161–181.
    1. Boardman, A. G. , Vaughn, S. , Buckley, P. , Reutebuch, C. , Roberts, G. , & Klingner, J. (2016). Collaborative strategic reading for students with learning disabilities in upper elementary classrooms. Exceptional Children, 82(4), 409–427.
    1. Bramlett, R. K. (1992). Cooperative learning: A field study with implications for school psychologists. Paper presented at the Annual Convention of the American Psychological Association, Washington DC. Retrieved from ERIC database (ED351654).
    1. Carlo, M. S. , August, D. , McLaughlin, B. , Snow, C. E. , Dressler, C. , Lippman, D. N. , Lively, T. J. , & White, C. E. (2004). Closing the gap: Addressing the vocabulary needs of English‐language learners in bilingual and mainstream classrooms. Reading Research Quarterly, 39(2), 188–215.

TOO HIGH RISK OF BIAS

    1. Aagaard, L. J. , Roach, R. G. , Wall, T. , & Stamm, V. (2016). An evaluation of a math response to intervention training program in the primary grades. Paper presented at the 2016 annual meeting of the American Educational Research Association, Washington DC. Retrieved from the AERA Online Paper Repository.
    1. Adams, W. (2011). Comparative study of reading first schools reading achievement to non‐reading first schools (Doctoral dissertation). Available from ProQuest Dissertations and Theses (UMI No. 3462040).
    1. Algozzine, B. , Marr, M. B. , Kavel, R. L. , & Dugan, K. K. (2009). Using peer coaches to build oral reading fluency. Journal of Education for Students Placed at Risk, 14(3), 256–270.
    1. Allen, K. (2017). An Evaluation Study of Fifth‐Grade Independent Reading and Reading Achievement (Doctoral dissertation). Dissertation Abstracts International Section A: Humanities and Social Sciences, 4‐A(E).
    1. Allinder, R. M. , Bolling, R. M. , Oats, R. G. , & Gagnon, W. A. (2000). Effects of teacher self‐monitoring on implementation of curriculum‐based measurement and mathematics computation achievement of students with disabilities. Remedial and Special Education, 21(4), 219–226.

ADDITIONAL REFERENCES

    1. Abadie, A. (2005). Semiparametric difference‐in‐differences estimators. Review of Economic Studies, 72(1), 1–19.
    1. Ackerman, P. T. , Dykman, R. A. , Holloway, C. , Paal, N. P. , & Gocio, M. Y. (1991). A trial of piracetam in two subgroups of students with dyslexia enrolled in summer tutoring. Journal of Learning Disabilities, 24(9), 542–549. - PubMed
    1. Alexander, K. L. , Entwisle, D. R. , & Olson, L. S. (2001). Schools, achievement, and inequality: A seasonal perspective. Education Evaluation and Policy Analysis, 23(2), 171–191.
    1. Alfieri, L. , Brooks, P. J. , Aldrich, N. J. , & Tenenbaum, H. R. (2011). Does discovery‐based instruction enhance learning? Journal of Educational Psychology, 103(1), 1–18.
    1. Al Otaiba, S. , Connor, C. M. , Sidler Folsom, J. , Greulich, L. , Meadows, J. , & Li, Z. (2011). Assessment data‐informed guidance to individualize kindergarten reading instruction: Findings from a cluster‐randomized control field trial. Elementary School Journal, 111(4), 535–560. - PMC - PubMed

LinkOut - more resources