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Understanding the influence of text complexity and question type on reading outcomes

  • Mercedes Spencer
  • Allison F. Gilmour
  • Amanda C. Miller
  • Angela M. Emerson
  • Neena M. Saha
  • Laurie E. Cutting
Article

Abstract

In the current study, we examined how student characteristics and cognitive skills, differing levels of text complexity (cohesion, decoding, vocabulary, and syntax), and reading comprehension question types (literal, inferential, critical analysis, and reading strategy) affected different types of reading outcomes (multiple-choice reading comprehension questions, free recall, and oral reading fluency) in a sample of 181 native English-speaking adolescents (9 to 14.83 years). Results from item response theory one-parameter models and multilevel models suggested that different cognitive skills predicted performance across the three reading outcomes. After controlling for student characteristics and cognitive skills, text complexity negatively impacted reading outcomes, particularly oral reading fluency and free recall. Critical analysis and inferential questions emerged as the most difficult types of comprehension questions. The implications of these findings are discussed.

Keywords

Item response theory Reading comprehension Oral reading fluency Assessment Multilevel models 

Notes

Acknowledgements

This research was supported by Grant Numbers R01 HD 044073, U54 HD 083211, and R01 HD 044073-14S1 from the National Institute of Child Health and Human Development and Grant Number UL1 TR000445 from the National Center for Advancing Translational Sciences.

References

  1. Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge: MIT Press.Google Scholar
  2. Amendum, S. J., Conradi, K., & Hiebert, E. (2017). Does text complexity matter in the elementary grades? A research synthesis of text difficulty and elementary students’ reading fluency and comprehension. Educational Psychology Review.  https://doi.org/10.1007/s10648-017-9398-2.CrossRefGoogle Scholar
  3. Arrington, C. N., Kulesz, P. A., Francis, D. J., Fletcher, J. M., & Barnes, M. A. (2014). The contribution of attentional control and working memory to reading comprehension and decoding. Scientific Studies of Reading, 18, 325–346.  https://doi.org/10.1080/10888438.2014.902461.CrossRefGoogle Scholar
  4. Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89.  https://doi.org/10.1016/s0079-7421(08)60452-1.CrossRefGoogle Scholar
  5. Barnes, M. A., Dennis, M., & Haefele-Kalvaitis, J. (1996). The effects of knowledge availability and knowledge accessibility on coherence and elaborative inferencing in children from fifteen years of age. Journal of Experimental Child Psychology, 61, 216–241.CrossRefGoogle Scholar
  6. Barth, A. E., Catts, H. W., & Anthony, J. L. (2009). The component skills underlying reading fluency in adolescent readers: A latent variable analysis. Reading and Writing: An Interdisciplinary Journal, 22, 567–590.  https://doi.org/10.1007/s11145-008-9125-y.CrossRefGoogle Scholar
  7. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2015). lme4: Linear Mixed-Effects Models using ‘Eigen’ and S4. R package version 1.1-8.Google Scholar
  8. Benjamin, R. G., & Schwanenflugel, P. J. (2010). Text complexity and oral reading prosody in young readers. Reading Research Quarterly, 45, 388–404.CrossRefGoogle Scholar
  9. Best, R. M., Floyd, R. G., & McNamara, D. S. (2008). Differential competencies contributing to children’s comprehension of narrative and expository texts. Reading Psychology, 29, 137–164.  https://doi.org/10.1080/02702710801963951.CrossRefGoogle Scholar
  10. Bowey, J. A. (1995). Socioeconomic status differences in preschool phonological sensitivity and first-grade reading achievement. Journal of Educational Psychology, 87, 476–487.  https://doi.org/10.1037/0022-0663.87.3.476.CrossRefGoogle Scholar
  11. Buck, J., & Torgesen, J. (2003). The relationship between performance on a measure of oral reading fluency and performance on the Florida Comprehensive Assessment Test. Tallahassee, FL: Florida Center for Reading Research.Google Scholar
  12. Cain, K., & Oakhill, J. V. (1999). Inference making ability and its relation to comprehension failure in young children. Reading and Writing: An Interdisciplinary Journal, 11, 489–503.  https://doi.org/10.1023/a:1008084120205.CrossRefGoogle Scholar
  13. Cain, K., Oakhill, J., & Bryant, P. (2004). Children’s reading comprehension ability: Concurrent prediction by working memory, verbal ability, and component skills. Journal of Educational Psychology, 96, 31–42.  https://doi.org/10.1037/0022-0663.96.1.31.CrossRefGoogle Scholar
  14. Canty, A. & Ripley, B. (2015). boot: Bootstrap functions. R package version 1.3-17.Google Scholar
  15. Carlisle, J. F. (2003). Morphology matters in learning to read: A commentary. Reading Psychology, 24, 291–322.  https://doi.org/10.1080/02702710390227369.CrossRefGoogle Scholar
  16. Catts, H. W., Fey, M. E., Zhang, X., & Tomblin, J. B. (2001). Estimating the risk of future reading difficulties in kindergarten children: A research-based model and its clinical implementation. Language, Speech, and Hearing Services in Schools, 32, 38–50.  https://doi.org/10.1044/0161-1461(2001/004).CrossRefGoogle Scholar
  17. Coleman, C., Lindstrom, J., Nelson, W., Lindstrom, W., & Gregg, K. N. (2010). Passageless comprehension on the Nelson–Denny reading test: Well above chance for university students. Journal of Learning Disabilities, 43, 244–249.  https://doi.org/10.1177/0022219409345017.CrossRefGoogle Scholar
  18. Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204–256.  https://doi.org/10.1037/0033-295x.108.1.204.CrossRefGoogle Scholar
  19. Common Core State Standards Initiative. (2010). Common Core State Standards for English language arts & literacy in history/social studies, science, and technical subjects. Washington, DC: CCSSO & National Governors Association.Google Scholar
  20. Cunningham, J. W., & Mesmer, H. A. (2014). Quantitative measurement of text difficulty: What’s the use? The Elementary School Journal, 115(2), 255–269.  https://doi.org/10.1086/678292.CrossRefGoogle Scholar
  21. Cutting, L., Saha, N., & Hasselbring, T. (2017). U.S. Patent Application No. 62509856. Washington, DC: U.S. Patent and Trademark Office.Google Scholar
  22. Cutting, L. E., & Scarborough, H. S. (2006). Prediction of reading comprehension: Relative contributions of word recognition, language proficiency, and other cognitive skills can depend on how comprehension is measured. Scientific Studies of Reading, 10, 277–299.  https://doi.org/10.1207/s1532799xssr1003_5.CrossRefGoogle Scholar
  23. Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19, 450–466.  https://doi.org/10.1016/s0022-5371(80)90312-6.CrossRefGoogle Scholar
  24. Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis–Kaplan executive function system (D-KEFS). San Antonio, TX: Pearson.Google Scholar
  25. Denckla, M. B. (1989). Executive function, the overlap zone between attention deficit hyperactivity disorder and learning disabilities. International Pediatrics, 4, 155–160.Google Scholar
  26. Deno, S. L. (1985). Curriculum-based measurement: The emerging alternative. Exceptional Children, 52, 219–232.  https://doi.org/10.1177/001440298505200303.CrossRefGoogle Scholar
  27. Deno, S. L. (1989). Curriculum-based measurement and alternative special education services: A fundamental and direct relationship. In M. R. Shinn (Ed.), Curriculum-based measurement: Assessing special children (pp. 1–17). New York: Guilford Press.Google Scholar
  28. Deno, S. L. (2003). Developments in curriculum-based measurement. The Journal of Special Education, 37, 184–192.CrossRefGoogle Scholar
  29. Eason, S. H., Goldberg, L. F., Young, K. M., Geist, M. C., & Cutting, L. E. (2012). Reader–text interactions: How differential text and question types influence cognitive skills needed for reading comprehension. Journal of Educational Psychology, 104, 515–528.  https://doi.org/10.1037/a0027182.CrossRefGoogle Scholar
  30. Eason, S. H., Sabatini, J., Goldberg, L., Bruce, K., & Cutting, L. E. (2013). Examining the relationship between word reading efficiency and oral reading rate in predicting comprehension among different types of readers. Scientific Studies of Reading, 17, 199–223.  https://doi.org/10.1080/10888438.2011.652722.CrossRefGoogle Scholar
  31. Edwards-Hewitt, T., & Gray, J. J. (1995). Comparison of measures of socioeconomic status between ethnic groups. Psychological Reports, 77, 699–702.  https://doi.org/10.2466/pr0.1995.77.2.699.CrossRefGoogle Scholar
  32. Elbro, C., & Buch-Iversen, I. (2013). Activation of background knowledge for inference making: Effects on reading comprehension. Scientific Studies of Reading, 17, 435–452.  https://doi.org/10.1080/10888438.2013.774005.CrossRefGoogle Scholar
  33. Engen, L., & Høien, T. (2002). Phonological skills and reading comprehension. Reading and Writing, 15, 613–631.  https://doi.org/10.1023/a:1020958105218.CrossRefGoogle Scholar
  34. Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. (1999). Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. Journal of Experimental Psychology: General, 128, 309–331.  https://doi.org/10.1037/0096-3445.128.3.309.CrossRefGoogle Scholar
  35. English, L., Barnes, M. A., Fletcher, J. M., Dennis, M., & Raghubar, K. P. (2010). Effects of reading goals on reading comprehension, reading rate, and allocation of working memory in children and adolescents with spina bifida meningomyelocele. Journal of the International Neuropsychological Society, 16, 517–525.  https://doi.org/10.1017/s1355617710000123.CrossRefGoogle Scholar
  36. Fitzgerald, J., Elmore, J., Hiebert, E. H., Koons, H. H., Bowen, K., Sanford-Moore, E. E., et al. (2016). Examining text complexity in the early grades. Phi Delta Kappan, 97(8), 60–65.  https://doi.org/10.1177/0031721716647023.CrossRefGoogle Scholar
  37. Frantz, R. S., Starr, L. E., & Bailey, A. L. (2015). Syntactic complexity as an aspect of text complexity. Educational Researcher, 44(7), 387–393.  https://doi.org/10.3102/0013189x15603980.CrossRefGoogle Scholar
  38. Freebody, P., & Anderson, R. C. (1983). Effects of vocabulary difficulty, text cohesion, and schema availability on reading comprehension. Reading Research Quarterly, 18, 277–294.  https://doi.org/10.2307/747389.CrossRefGoogle Scholar
  39. Fuchs, L. S., Fuchs, D., Hosp, M. K., & Jenkins, J. R. (2001). Oral reading fluency as an indicator of reading competence: A theoretical, empirical, and historical analysis. Scientific Studies of Reading, 5, 239–256.  https://doi.org/10.1207/s1532799xssr0503_3.CrossRefGoogle Scholar
  40. Fuchs, L. S., Fuchs, D., & Kazdan, S. (1999). Effects of peer-assisted learning strategies on high school students with serious reading problems. Remedial and Special Education, 20, 309–318.  https://doi.org/10.1177/074193259902000507.CrossRefGoogle Scholar
  41. Fuchs, L. S., Fuchs, D., & Maxwell, L. (1988). The validity of informal reading comprehension measures. Remedial and Special Education, 9, 20–28.  https://doi.org/10.1177/074193258800900206.CrossRefGoogle Scholar
  42. García, J. R., & Cain, K. (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, 74–111.  https://doi.org/10.3102/0034654313499616.CrossRefGoogle Scholar
  43. Geiger, J. F., & Millis, K. K. (2004). Assessing the impact of reading goals and text structures on comprehension. Reading Psychology, 25, 93–110.  https://doi.org/10.1080/02702710490435637.CrossRefGoogle Scholar
  44. Goswami, U., Gombert, J. E., & de Barrera, L. F. (1998). Children’s orthographic representations and linguistic transparency: Nonsense word reading in English, French, and Spanish. Applied Psycholinguistics, 19, 19–52.CrossRefGoogle Scholar
  45. Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36, 193–202.  https://doi.org/10.3758/bf03195564.CrossRefGoogle Scholar
  46. Hackman, D. A., & Farah, M. J. (2009). Socioeconomic status and the developing brain. Trends in Cognitive Sciences, 13, 65–73.  https://doi.org/10.1016/j.tics.2008.11.003.CrossRefGoogle Scholar
  47. Hall, C. S. (2016). Inference instruction for struggling readers: A synthesis of intervention research. Educational Psychology Review, 28, 1–22.  https://doi.org/10.1007/s10648-014-9295-x.CrossRefGoogle Scholar
  48. Halliday, M. A. K., & Hasan, R. (2014). Cohesion in English. New York, NY: Routledge.Google Scholar
  49. Hansen, C. L. (1978). Story retelling used with average and learning disabled readers as a measure of reading comprehension. Learning Disability Quarterly, 1, 62–69.  https://doi.org/10.2307/1510938.CrossRefGoogle Scholar
  50. Hiebert, E. H., & Mesmer, H. A. E. (2013). Upping the ante of text complexity in the Common Core State Standards examining its potential impact on young readers. Educational Researcher, 42, 44–51.  https://doi.org/10.3102/0013189x12459802.CrossRefGoogle Scholar
  51. Hollingshead, A. B. (1975). Four factor index of social status. Unpublished manuscript, Yale University, New Haven, CT.Google Scholar
  52. Homack, S., Lee, D., & Riccio, C. A. (2005). Test review: Delis–Kaplan executive function system. Journal of Clinical and Experimental Neuropsychology, 22, 599–609.  https://doi.org/10.1080/13803390490918444.CrossRefGoogle Scholar
  53. Hoover, W. A., & Gough, P. B. (1990). The simple view of reading. Reading and Writing: An Interdisciplinary Journal, 2, 127–160.  https://doi.org/10.1007/bf00401799.CrossRefGoogle Scholar
  54. Hosp, M. K., & Fuchs, L. S. (2005). Using CBM as an indicator of decoding, word reading, and comprehension: Do the relations change with grade? School Psychology Review, 34, 9–26.Google Scholar
  55. Keenan, J. M., & Betjemann, R. S. (2006). Comprehending the gray oral reading test without reading it: Why comprehension tests should not include passage-independent items. Scientific Studies of Reading, 10, 363–380.  https://doi.org/10.1207/s1532799xssr1004_2.CrossRefGoogle Scholar
  56. Keenan, J. M., Betjemann, R. S., & Olson, R. K. (2008). Reading comprehension tests vary in the skills they assess: Differential dependence on decoding and oral comprehension. Scientific Studies of Reading, 12, 281–300.  https://doi.org/10.1080/10888430802132279.CrossRefGoogle Scholar
  57. Keenan, J. M., & Meenan, C. E. (2014). Test differences in diagnosing reading comprehension deficits. Journal of Learning Disabilities, 47, 125–135.  https://doi.org/10.1177/0022219412439326.CrossRefGoogle Scholar
  58. Kintsch, W. (1988). The role of knowledge in discourse comprehension: a construction-integration model. Psychological Review, 95, 163–182.  https://doi.org/10.1037/0033-295x.95.2.163.CrossRefGoogle Scholar
  59. Kintsch, W. (1994). Text comprehension, memory, and learning. American Psychologist, 49, 294–303.  https://doi.org/10.1037/0003-066x.49.4.294.CrossRefGoogle Scholar
  60. Klecker, B. M. (2006). The gender gap in NAEP fourth-, eighth-, and twelfth-grade reading scores across years. Reading Improvement, 43, 50–56.Google Scholar
  61. Kulesz, P. A., Francis, D. J., Barnes, M., & Fletcher, J. M. (2016). The influence of properties of the test and their interactions with reader characteristics on reading comprehension: An explanatory item response study. Journal of Educational Psychology.  https://doi.org/10.1037/edu0000126.CrossRefGoogle Scholar
  62. LaBerge, D., & Samuels, S. J. (1974). Toward a theory of automatic information processing in reading. Cognitive Psychology, 6, 293–323.  https://doi.org/10.1016/0010-0285(74)90015-2.CrossRefGoogle Scholar
  63. Loosli, S. V., Buschkuehl, M., Perrig, W. J., & Jaeggi, S. M. (2012). Working memory training improves reading processes in typically developing children. Child Neuropsychology, 18, 62–78.  https://doi.org/10.1080/09297049.2011.575772.CrossRefGoogle Scholar
  64. Lorch, R. F., Lorch, E. P., & Inman, W. E. (1993). Effects of signaling topic structure on text recall. Journal of Educational Psychology, 85, 281–290.  https://doi.org/10.1037/0022-0663.85.2.281.CrossRefGoogle Scholar
  65. Lyon, G. R. (1998). Why reading is not a natural process. Educational Leadership, 55(6), 14–18.Google Scholar
  66. Mahony, D., Singson, M., & Mann, V. (2000). Reading ability and sensitivity to morphological relations. Reading and Writing: An Interdisciplinary Journal, 12, 191–218.  https://doi.org/10.1023/a:1008136012492.CrossRefGoogle Scholar
  67. McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1–43.CrossRefGoogle Scholar
  68. Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49, 270–291.  https://doi.org/10.1037/a0028228.CrossRefGoogle Scholar
  69. Mesmer, H. A., Cunningham, J. W., & Hiebert, E. H. (2012). Toward a theoretical model of text complexity for the early grades: Learning from the past, anticipating the future. Reading Research Quarterly, 47, 235–258.  https://doi.org/10.1002/rrq.019.CrossRefGoogle Scholar
  70. Meyers, J. L., & Beretvas, N. (2006). The impact of inappropriate modeling of cross-classified data structures. Multivariate Behavioral Research, 41, 473–497.  https://doi.org/10.1207/s15327906mbr4104_3.CrossRefGoogle Scholar
  71. Miller, A. C., Davis, N., Gilbert, J. K., Cho, S. J., Toste, J. R., Street, J., et al. (2014). Novel approaches to examine passage, student, and questions effects on reading comprehension. Learning Disabilities Research and Practice, 29, 25–35.  https://doi.org/10.1111/ldrp.12027.CrossRefGoogle Scholar
  72. Miller, A. C., & Keenan, J. M. (2009). How word reading skill impacts text memory: The centrality deficit and how domain knowledge can compensate. Annals of Dyslexia, 59, 99–113.  https://doi.org/10.1007/s11881-009-0025-x.CrossRefGoogle Scholar
  73. Moravcsik, J. E., & Kintsch, W. (1993). Writing quality, reading skills, and domain knowledge as factors in text comprehension. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 47, 360–374.CrossRefGoogle Scholar
  74. Nation, K., & Snowling, M. J. (1998). Semantic processing and the development of word-recognition skills: Evidence from children with reading comprehension difficulties. Journal of Memory and Language, 39, 85–101.  https://doi.org/10.1006/jmla.1998.2564.CrossRefGoogle Scholar
  75. National Center for Education Statistics. (2009). The nation’s report card: Reading 2009 (NCES 2010–458). Washington, D.C.: U.S. Department of Education, Institute of Education Sciences.Google Scholar
  76. National Center for Education Statistics. (2013). National assessment of educational progress (NAEP), 2013 mathematics and reading assessments. Washington, D.C.: U.S. Department of Education, Institute of Education Sciences.Google Scholar
  77. National Center for Education Statistics. (2015). NAEP 2015 reading: A report card for the nation and the states. Washington, D.C.: U.S. Department of Education, Institute of Education Sciences.Google Scholar
  78. National Institute of Child Health and Human Development. (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 (NIH Publication No. 00-4769). Washington, DC: Government Printing Office.Google Scholar
  79. National Reading Panel (US), National Institute of Child Health, & Human Development (US). (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. National Institutes of Health: National Institute of Child Health and Human Development.Google Scholar
  80. O’Connor, R. E., Bell, K. M., Harty, K. R., Larkin, L. K., Sackor, S. M., & Zigmond, N. (2002). Teaching reading to poor readers in the intermediate grades: A comparison of text difficulty. Journal of Educational Psychology, 94, 474–485.  https://doi.org/10.1037/0022-0663.94.3.474.CrossRefGoogle Scholar
  81. Oakhill, J. V., Cain, K., & Bryant, P. E. (2003). The dissociation of word reading and text comprehension: Evidence from component skills. Language and Cognitive Processes, 18, 443–468.  https://doi.org/10.1080/01690960344000008.CrossRefGoogle Scholar
  82. Ouellette, G. P. (2006). What’s meaning got to do with it: The role of vocabulary in word reading and reading comprehension. Journal of Educational Psychology, 98, 554–566.  https://doi.org/10.1037/0022-0663.98.3.554.CrossRefGoogle Scholar
  83. Ozuru, Y., Best, R., Bell, C., Witherspoon, A., & McNamara, D. S. (2007). Influence of question format and text availability on assessment of expository text comprehension. Cognition & Instruction, 25, 399–438.  https://doi.org/10.1080/07370000701632371.CrossRefGoogle Scholar
  84. Perfetti, C. A. (1985). Reading ability. New York, NY: Oxford University Press.Google Scholar
  85. Perfetti, C. A. (1999). Comprehending written language: A blueprint of the reader. In P. Hagoort & C. M. Brown (Eds.), Neurocognition of language processing (pp. 167–208). Oxford: Oxford University Press.Google Scholar
  86. Pikulski, J. J., & Chard, D. J. (2005). Fluency: Bridge between decoding and reading comprehension. The Reading Teacher, 58, 510–519.  https://doi.org/10.1598/rt.58.6.2.CrossRefGoogle Scholar
  87. Priebe, S. J., Keenan, J. M., & Miller, A. C. (2012). How prior knowledge affects word identification and comprehension. Reading and Writing: An Interdisciplinary Journal, 25, 131–149.  https://doi.org/10.1007/s11145-010-9260-0.CrossRefGoogle Scholar
  88. Quinn, J. M., Wagner, R. K., Petscher, Y., & Lopez, D. (2015). Developmental relations between vocabulary knowledge and reading comprehension: A latent change score modeling study. Child Development, 86, 159–175.  https://doi.org/10.1111/cdev.12292.CrossRefGoogle Scholar
  89. Ready, R. E., Chaudhry, M. F., Schatz, K. C., & Strazzullo, S. (2013). “Passageless” administration of the Nelson–Denny reading comprehension test: Associations with IQ and reading skills. Journal of Learning Disabilities, 46, 377–384.  https://doi.org/10.1177/0022219412468160.CrossRefGoogle Scholar
  90. Reed, D. K. (2008). A synthesis of morphology interventions and effects on reading outcomes for students in grades K–12. Learning Disabilities Research & Practice, 23, 36–49.  https://doi.org/10.1111/j.1540-5826.2007.00261.x.CrossRefGoogle Scholar
  91. Reynolds, A. J., Chan, H., & Temple, J. A. (1998). Early childhood intervention and juvenile delinquency: An exploratory analysis of the Chicago child-parent centers. Evaluation Review, 22, 341–372.  https://doi.org/10.1177/0193841x9802200302.CrossRefGoogle Scholar
  92. Reynolds, A. J., Temple, J. A., Robertson, D. L., & Mann, E. A. (2002). Age 21 cost-benefit analysis of the Title I Chicago child-parent centers. Educational Evaluation and Policy Analysis, 24, 267–303.  https://doi.org/10.3102/01623737024004267.CrossRefGoogle Scholar
  93. Riedel, B. W. (2007). The relation between DIBELS, reading comprehension, and vocabulary in urban first-grade students. Reading Research Quarterly, 42, 546–567.  https://doi.org/10.1598/rrq.42.4.5.CrossRefGoogle Scholar
  94. Saenz, L. M., & Fuchs, L. S. (2002). Examining the reading difficulty of secondary students with learning disabilities: Expository versus narrative text. Remedial and Special Education, 23(1), 31–41.  https://doi.org/10.1177/074193250202300105.CrossRefGoogle Scholar
  95. Schroeder, S. (2011). What readers have and do: Effects of students’ verbal ability and reading time components on comprehension with and without text availability. Journal of Educational Psychology, 103, 877–896.  https://doi.org/10.1037/a0023731.CrossRefGoogle Scholar
  96. Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96, 523–568.  https://doi.org/10.1037/0033-295x.96.4.523.CrossRefGoogle Scholar
  97. Sesma, H. W., Mahone, E. M., Levine, T., Eason, S. H., & Cutting, L. E. (2009). The contribution of executive skills to reading comprehension. Child Neuropsychology, 15, 232–246.  https://doi.org/10.1080/09297040802220029.CrossRefGoogle Scholar
  98. Shaywitz, S. E., & Shaywitz, B. A. (2005). Dyslexia (specific reading disability). Biological Psychiatry, 57, 1301–1309.  https://doi.org/10.1016/j.biopsych.2005.01.043.CrossRefGoogle Scholar
  99. Shinn, M. R. (Ed.). (1989). Curriculum-based measurement: Assessing special children. New York, NY: Guilford.Google Scholar
  100. Shinn, M. M., & Shinn, M. R. (2002). AIMSweb training workbook: Administration and scoring of reading curriculum-based measurement (R-CBM) for use in general outcome measurement. Eden Prairie, MN: Edformation.Google Scholar
  101. Snow, C. E., Burns, M. S., & Griffin, P. (1998). Preventing reading difficulties in young children committee on the prevention of reading difficulties in young children. Washington, DC: National Research Council.Google Scholar
  102. Snowling, M. J., & Hulme, C. (2011). Evidence-based interventions for reading and language difficulties: Creating a virtuous circle. British Journal of Educational Psychology, 81, 1–23.  https://doi.org/10.1111/j.2044-8279.2010.02014.x.CrossRefGoogle Scholar
  103. Solis, M., Ciullo, S., Vaughn, S., Pyle, N., Hassaram, B., & Leroux, A. (2012). Reading comprehension interventions for middle school students with learning disabilities: A synthesis of 30 years of research. Journal of Learning Disabilities, 45, 327–340.  https://doi.org/10.1177/0022219411402691.CrossRefGoogle Scholar
  104. Tannenbaum, K. R., Torgesen, J. K., & Wagner, R. K. (2006). Relationships between word knowledge and reading comprehension in third-grade children. Scientific Studies of Reading, 10, 381–398.  https://doi.org/10.1207/s1532799xssr1004_3.CrossRefGoogle Scholar
  105. Thurlow, R., & van den Broek, P. (1997). Automaticity and inference generation. Reading and Writing Quarterly, 13, 165–184.  https://doi.org/10.1080/1057356970130205.CrossRefGoogle Scholar
  106. Torgensen, J. K., Wagner, R. K., & Rashotte, C. A. (1999). Test of word reading efficiency (TOWRE). Austin, TX: Pro-Ed.Google Scholar
  107. Torgesen, J. K., & Hudson, R. (2006). Reading fluency: critical issues for struggling readers. In S. J. Samuels & A. Farstrup (Eds.), Reading fluency: The forgotten dimension of reading success. Newark, DE: International Reading Association.Google Scholar
  108. Tuinman, J. J. (1974). Determining the passage dependency of comprehension questions in 5 major tests. Reading Research Quarterly, 9, 206–223.CrossRefGoogle Scholar
  109. van den Broek, P., Lorch, R. F., Linderholm, T., & Gustafson, M. (2001). The effects of readers’ goals on inference generation and memory for texts. Memory and Cognition, 29, 1081–1087.  https://doi.org/10.3758/bf03206376.CrossRefGoogle Scholar
  110. van den Noortgate, W., de Boeck, P., & Meulders, M. (2003). Cross-classification multilevel logistic models in psychometrics. Journal of Educational and Behavioral Statistics, 28, 369–386.  https://doi.org/10.3102/10769986028004369.CrossRefGoogle Scholar
  111. Van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New York, NY: Academic Press.Google Scholar
  112. Von Stumm, S., & Plomin, R. (2015). Socioeconomic status and the growth of intelligence from infancy through adolescence. Intelligence, 48, 30–36.  https://doi.org/10.1016/j.intell.2014.10.002.CrossRefGoogle Scholar
  113. Waters, G. S., & Caplan, D. (1996). The measurement of verbal working memory capacity and its relation for reading comprehension. The Quarterly Journal of Experimental Psychology, 49, 51–79.CrossRefGoogle Scholar
  114. Wechsler, D. (1999). Wechsler abbreviated scale of intelligence. New York, NY: Harcourt Brace & Company.Google Scholar
  115. Wexler, J., Vaughn, S., Edmonds, M., & Reutebuch, C. K. (2008). A synthesis of fluency interventions for secondary struggling readers. Reading and Writing: An Interdisciplinary Journal, 21, 317–347.  https://doi.org/10.1007/s11145-007-9085-7.CrossRefGoogle Scholar
  116. Wiig, E. H., & Secord, W. A. (1992). Test of word knowledge (TOWK). San Antonio: Psychological Corporation.Google Scholar
  117. Woodcock, R. W., McGrew, K. S., & Mather, N. (2001). Woodcock–Johnson III. Boston, MA: Houghton Mifflin Harcourt.Google Scholar
  118. Zorzi, M., Houghton, G., & Butterworth, B. (1998). Two routes or one in reading aloud? A connectionist dual-process model. Journal of Experimental Psychology: Human Perception and Performance, 24, 1131–1161.  https://doi.org/10.1037/0096-1523.24.4.1131.CrossRefGoogle Scholar
  119. Zvonik, E. & Cummins, F. (2003). The effect of surrounding phrase lengths on pause duration. In Eighth European conference on speech communication and technology (Vol. 82, pp. 176–193).  https://doi.org/10.2307/329207

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Mercedes Spencer
    • 1
  • Allison F. Gilmour
    • 2
  • Amanda C. Miller
    • 3
  • Angela M. Emerson
    • 4
  • Neena M. Saha
    • 1
  • Laurie E. Cutting
    • 1
  1. 1.Department of Special Education, Vanderbilt Kennedy CenterVanderbilt UniversityNashvilleUSA
  2. 2.Department of Teaching and LearningTemple UniversityPhiladelphiaUSA
  3. 3.Department of Psychology and Neuroscience, Regis CollegeRegis UniversityDenverUSA
  4. 4.Center for Neuromodulation, Stanley D. and Joan H. Ross Center for Brain Health and PerformanceOhio State UniversityColumbusUSA

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