This study employed group randomized trials to investigate the effects of self– and peer–monitoring on the academic vocabulary and content knowledge of students with learning disabilities and low achieving students in social studies. Fourth grade students were randomly assigned to either treatment or control groups on a class level. Results indicated that there was a significant interaction effect between the intervention and students’ pretest scores on academic vocabulary acquisition; the intervention was more effective for students with lower scores in the pretest than those with higher scores. In addition, there was a significant intervention effect on content knowledge acquisition; the effect size of the growth of the treatment group on the content knowledge test was significantly larger than that of the comparison group. Teacher interviews also revealed that teachers viewed the intervention positively. Implications for practice and suggestions for future research are discussed.
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References
1.
BeachK. D., SanchezV., FlynnL. J., & O'ConnorR.E. (2015). Teaching academic vocabulary to adolescents with learning disabilities. Teaching Exceptional Children, 48, 36–44. https://doi.org/0.1177/0040059915594783
2.
BeckI. L., McKeownM. G., & KucanL. (2002). Bring words to life: Robust vocabulary instruction. New York, NY: Guilford.
3.
BerkeleyS., MarshakL., MastropieriM. A., & ScruggsT. E. (2011). Improving student comprehension of social studies text: A self–questioning strategy for inclusive middle school classes. Remedial and Special Education, 32, 105–113.
4.
BolingerK., & WarrenW. J. (2007). Methods practiced in social studies instruction: A review of public school teachers’ strategies. International Journal of Social Education, 22, 68–84.
5.
CalhoonM. B., & FuchsL. S. (2003). The effects of peer–assisted learning strategies and curriculum–based measurement on the mathematics performance of secondary students with disabilities. Remedial and Special Education, 24, 235–245.
6.
CarrS. C., & PunzoR. P. (1993). The effects of self–monitoring of academic accuracy and productivity on the performance of students with behavioral disorders. Behavior Disorders, 18, 241–50.
7.
CohenJ. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: Erlbaum.
8.
CouhglinJ., McCoyK. M., KenzerA., MathurS. R., & ZuckerS. H. (2012). Effects of a self–monitoring strategy on independent work behavior of students with mild intellectual disabilities. Education and Training in Autism and Development disabilities, 47(2), 154–164.
9.
CoyneM. D., McCoachD. B., & KappS. (2007). Vocabulary intervention for kindergarten students: Comparing extended instruction to embedded instruction and incidental exposure. Learning Disability Quarterly, 30, 74–88.
10.
DiGangiS. A., MaagJ. W., & RutherfordR. B. (1991). Self–graphing of on–task behavior: Enhancing the reactive effects of self–monitoring of on–task behavior and academic performance. Learning Disability Quarterly, 14, 221–230.
11.
EspinC. A., BuschT. W., LembkeE. S., HamptonD. D., SeoK., & ZukowskiB. A. (2013). Curriculum–based measurement in science learning: Vocabulary–matching as an indicator of performance and progress. Assessment for Effective Intervention, 38, 203–213.
12.
FuchsD., FuchsL. S., ThompsonA., SvensonE., YenL., Al OtaibaS., et al. (2001). Peer–assisted learning strategies in reading: Extensions for kindergarten, first grade, and high school. Remedial and Special Education, 22, 15–21. https://doi.org/10.1177/074193250102200103
13.
HarrisK. R., FriedlanderB. D., SaddlerB., FrizzelleR., & GrahamS. (2005). Self–monitoring of attention versus self–monitoring of academic performance. The Journal of Special Education, 39, 145–156.
14.
JitendraA. K., HoppesM. K., & XinY. P. (2000). Enhancing main idea comprehension for students with learning problems: The role of a summarization strategy and self–monitoring instruction. The Journal of Special Education, 34, 127–139.
15.
JohnsonE. S., HumphreyM., MellardD. F., WoodsK., & SwansonH. L. (2010). Cognitive processing deficits and students with specific learning disabilities: A selective meta–analysis of the literature. Learning Disability Quarterly, 33, 3–18.
16.
JosephL. M., & EveleighE. L. (2011). A review of the effects of self–monitoring on reading performance of students with disabilities. The Journal of Special Education, 45, 43–53.
17.
KentS., WanzekJ., SwansonE. A., & VaughnS. (2015). Team–based learning for students with high–incidence disabilities in high school social studies classrooms. Learning Disabilities Research & Practice, 30, 3–14.
18.
KimW., & KohE. Y. (2015). The experiences and perceptions of special education teachers in social studies instruction for students with intellectual disabilities: A focus group study. Journal of Intellectual Disabilities, 17, 299–321.
19.
KimW., & Linan–ThompsonS. (2013). The effects of self–regulation on science vocabulary acquisition of English language learners with learning difficulties. Remedial and Special Education. 34, 225–236.
20.
KimW., Linan–ThompsonS., & MisquittaR. (2012). Critical factors in reading comprehension instruction for students with learning disabilities: A research synthesis. Learning Disabilities Research & Practice, 27, 66–78.
21.
KimY. O., & KimS. H. (2000). Effects of a hypermedia CAI reading program for elementary students with and without learning disabilities. The Journal of Special Children Education, 1, 13–32.
22.
KimW. & KimJ. Y. (2016). Definitions and interventions of children at risk for disabilities: Experiences and perceptions of general and special education teachers. Korean Journal of Special Education, 51, 1–32.
23.
KlingnerJ. K., VaughnS., & SchummJ. S. (1998). Collaborative strategic reading during social studies in heterogeneous fourth–grade classrooms. Elementary School Journal, 99, 3–21. https://doi.org/10.1086/461914
24.
Korea Institute for Curriculum and Evaluation. (2012). The nation's report card (RRE 2012–2). Kyungsung, Seoul: KICE.
25.
Korean Ministry of Education. (2011). National curriculum standards for social studies (MOE Bulletin 2011–361). Wooshin, Seoul: MOE.
26.
Korean National Institute of Special Education. (2005). Korean National Institute of Special Education–Basic Academic Achievement Test. Seoul Munhwa, Asan: KNISE.
27.
KwakK. J., OhS. W., & KimC. T. (Eds.). (2011). Korean–Wechsler Intelligence Scale for Children–IV. Seoul, Republic of Korea: Hakjisa.
28.
LeeJ. Y., & SonS. H. (2012). Characteristics of interventions for improving knowledge of students with learning disabilities or difficulties in social studies. The Journal of Special Education: Theory and Practice, 13, 111–140.
29.
MaloneL. D., & MastropieriM. A. (1992). Reading comprehension instruction: Summarization and self–monitoring training for students with learning disabilities. Exceptional Children, 58, 270–279.
30.
MarshakL., MastropieriM. A., & ScruggsT. E. (2011). Curriculum enhancements for inclusive secondary social studies classes. Exceptionality, 19, 61–74.
31.
MassC. J. M. & HoxJ. J. (2005). Sufficient sample sizes for multilevel modeling. Methodology, 1, 86–92.
32.
MastropieriM. A., & ScruggsT. E. (2010). The inclusive classroom: Strategies for effective instruction (4th ed.). Upper Saddle River, NJ: Prentice Hall.
33.
McMasterK., FuchsD., & FuchsL. (2006). Research on peer–assisted learning strategies: The promise and limitations of peer–mediated instruction. Reading & Writing Quarterly, 22, 5–25.
34.
MinH–J., & KimY–Y. (2002). Effects of a textbook comprehension–summarization strategy to the achievements of social studies and metacognition of elementary students with learning disabilities. The Journal of Special Children Education, 4, 163–183.
35.
National Center for Education Statistics. (2011). The nation's report card: US history 2010 (NCES 2011–468). Washington, DC: Institute of Education Sciences, U.S. Department of Education.
36.
National Council for the Social Studies. (2010). National curriculum standards for social studies: A framework for teaching, learning, and assessment (NCSS Bulletin 111). Silver Spring, MD: NCSS.
37.
NitkoA. J., & BrookhartS. M. (2007). Educational assessment of students (5th ed.). Upper Saddle River, NJ: Prentice Hall.
38.
OkoloC. M., & FerrettiR. P. (2013). History instruction for students with learning disabilities (2nd ed.). In SwansonH. L., HarrisK., & GrahamS. (Eds.), Handbook of learning disabilities (pp. 463–487). New York, NY: Guilford Press.
39.
PeughJ. L. (2010). A practical guide to multilevel modeling. Journal of school psychology, 48, 85–112.
40.
PinheiroJ. C., & BatesD. M. (2000). Mixed–effects models in S and S–Plus. New York, NY: Springer.
41.
PinheiroJ., BatesD., DebRoyS., SarkarD., & R Core Team (2015, December 10). nlme: Linear and nonlinear mixed effects models. R package Version 3.1–121. Retrieved from http://CRAN.R-project.org/package=nlme
42.
R Core Team (2015, December 10). R: A language and environment for statistical computing. Retrieved from https://www.R-project.org/
43.
RaudenbushS. (1997). Statistical analysis and optimal design for cluster randomized trials. Psychological Methods, 2, 173–185.
44.
RaudenbushS. W., & BrykA. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Newbury Park, CA: Sage.
45.
ReyesM. R., BrackettM. A., RiversS. E., WhiteM., & SaloveyP. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104, 700–712. https://doi.org/10.1037/a0027268
46.
ScruggsT. E., & MastropieriM. A. (2013). Science and social studies education for students with learning disabilities. In SwansonH. L., HarrisK. R., & GrahamS. (Eds.), Handbook of learning disabilities (pp. 526–544). New York, NY: Guilford Press.
47.
ScruggsT. E., MastropieriM. A., & MarshakL. (2012). Peer–mediated instruction in inclusive secondary social studies learning: Direct and indirect learning effects. Learning Disabilities Research & Practice, 27, 12–20.
48.
ScruggsT. E., MastropieriM. A., & OkoloC. M. (2008). Science and social studies for students with disabilities. Focus on Exceptional Children, 41, 1–24.
49.
ScruggsT. E., MastropieriM. A., BerkeleyS., & GraetzJ. (2010). Do special education interventions improve learning of secondary content? A meta–analysis. Remedial and Special Education, 31, 437–449.
50.
SingerJ. D., & WillettJ. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press.
51.
SlymenD. J., & HovellM. F. (1997). Cluster versus individual randomization in adolescent tobacco and alcohol studies: Illustrations for design decisions. International Journal of Epidemiology, 26, 765–771.
52.
SnijdersT. A. B. (2005). Power and sample size in multilevel linear models. In EverittB. S. & HowellD. C. (Eds.), Encyclopedia of Statistics in Behavioral Science (Vol. 3, pp. 1570–1573). Chicester: Wiley.
53.
SnijdersT., & BoskerR. (1999). Multilevel analysis. An introduction to basic and advanced multilevel modeling. Thousand Oakes, CA: Sage.
54.
SwanbornM. S. L., & de GlopperK. (1999). Incidental word learning while reading: A meta–analysis. Review of Educational Research, 69, 261–285.
55.
VaughnS., Linan–ThompsonS., KouzekananiK., BryantD. P., DicksonS., & BlozisS. A. (2003). Reading instruction grouping for students with reading difficulties. Remedial and Special Education, 24, 301–315.
56.
WalshJ. E. (1947). Concerning the effect of intraclass correlation on certain significance tests. Annals of Math Statistics, 18, 88–96.
