Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-25T15:06:48.953Z Has data issue: false hasContentIssue false

3 - Cognitive Models of Task Performance for Reading Comprehension

Published online by Cambridge University Press:  05 June 2012

Jacqueline P. Leighton
Affiliation:
University of Alberta
Mark J. Gierl
Affiliation:
University of Alberta
Get access

Summary

Reading comprehension is a central skill students must learn to become successful learners in other content domains. For example, adequate reading skills are required to acquire scientific and mathematical literacy skills. In the present volume, then, we begin by describing cognitive models of task performance in reading comprehension, because reading skills function as a gatekeeper for the acquisition of most other academic skills.

Although students typically prefer reading over mathematics (OECD, 2004), many students continue to struggle with their reading performance. According to 2003 PISA results (Lemke et al., 2004), students in the United States scored 495 on the reading component, which is not measurably different from the OECD average of 494 (PISA results are scaled to have a mean of approximately 500 with a standard deviation of 100). This is good news for American students. However, it should be noted that among the thirty-eight countries participating in the assessment, eleven countries scored higher in reading than the United States.

More recently, the U.S. National Center for Education Statistics (2009) reported that although students' reading scores on the National Assessment of Educational Progress (NAEP) have increased since 1992, they remain unchanged from 2007 to 2009. In particular, 67 percent of students in grade four read at a basic level, and only 33 percent were classified as either proficient or advanced.

Type
Chapter
Information
The Learning Sciences in Educational Assessment
The Role of Cognitive Models
, pp. 71 - 114
Publisher: Cambridge University Press
Print publication year: 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bartlett, F.C. (1932). Remembering: A study in experimental and social psychology. Cambridge, UK: Cambridge University Press.Google Scholar
Bejar, I.I., Williamson, D.M., & Mislevy, R.J. (2006). Human scoring. In Williamson, D.M., Mislevy, R.J., and Bejar, I.I. (Eds.), Automated scoring of complex tasks in computer-based testing (pp. 49–81). Mahwah, NJ: Erlbaum.Google Scholar
Bower, G.H. & Morrow, D.G. (1990). Mental models in narrative comprehension. Science, 247, 44–48.CrossRefGoogle ScholarPubMed
Britton, B.K. & Gülgöz, S. (1991). Using Kinstch's computational model to improve instructional text: Effects of repairing inference calls on recall and cognitive structures, Journal of Educational Psychology, 83, 329–345.CrossRefGoogle Scholar
Butcher, K.R. & Kintsch, W. (2003). Text comprehension and discourse processing. In Healy, A.F. and Proctor, R.W. (Eds.), Handbook of psychology: Volume 4 experimental psychology, (pp. 575–595). Hoboken, N.J.: Wiley.Google Scholar
Cain, K. & Oakhill, J.V. (1999) Inference making and its relation to comprehension failure. Reading and Writing, 11, 489–503.CrossRefGoogle Scholar
Campbell, J.R. (2005). Single instrument, multiple measures: considering the use of multiple item formats to assess reading comprehension. In Paris, S.G. & Stahl, S.A. (Eds.), Children's reading comprehension and assessment (pp. 347–368). Mahwah, NJ: Erlbaum.Google Scholar
Crocker, M.W. (2005). Rational models of comprehension: Addressing the performance paradox. In Culter, A. (Ed.), Twenty-first century psycholinguistics: Four cornerstones (pp. 363–380). Hillsdale, NJ: Erlbaum.Google Scholar
Dawson, M.R.W. (1998). Understanding cognitive science. Blackwell.Google Scholar
Dikli, S. (2006). An overview of automated scoring of essays. Journal of Technology, Learning, and Assessment, 5(1). Retrieved May 21, 2010 from http://www.jtla.org.Google Scholar
Embretson, S.E. & Wetzel, C.D. (1987). Component latent trait models for paragraph comprehension. Applied Psychological Measurement, 11, 175–193.CrossRefGoogle Scholar
Ferstl, E.C. & Kintsch, W. (1998). Learning from text: Structural knowledge assessment in the study of discourse comprehension. In Goldman, S.R. & Oostendorp, H. (Eds.), The constructions of mental representations during reading, (pp. 247–277). Mahwah, NJ: Erlbaum.Google Scholar
Francis, D.J., Fletcher, J.M., Catts, H.W., & Tomblin, J.B. (2005). Dimensions affecting the assessment of reading comprehension. In Paris, S.G. & Stahl, S.A. (Eds.), Children's reading comprehension and assessment (pp. 369–394). Mahwah, NJ: Erlbaum.Google Scholar
Fox, E. & Alexander, P.A. (2009). Text comprehension: A retrospective, perspective, and prospective. In Israel, S.E. & Duffy, G.G. (Eds.), Handbook of research on reading comprehension (pp. 227–239). New York City: Routledge.Google Scholar
Gaddy, M.L., Broek, P., & Sung, Y-C. (2001). The influence of text cues on the allocation of attention during reading. In Sanders, T., Schilperoord, J., & Spooren, W. (Eds.), Text representation: Linguistic and psycholinguistic aspects, (pp. 89–124). Amsterdam, Netherlands: John Benjamins Publishing Company.Google Scholar
Gerrig, R. & McKoon, G. (1998). The readiness is all: The functionality of memory-based text processing. Discourse Processes, 26, 67–86.CrossRefGoogle Scholar
Gilabert, R., Martínez, G., & Vidal-Abarca, E. (2005). Some good texts are always better: text revision to foster inferences of readers with high and low prior background knowledge. Learning and Instruction, 15, 45–68.CrossRefGoogle Scholar
Glenberg, A.M., Jaworski, B., Rischal, M., & Levin, J. (2007). What brains are for: Action, meaning, and reading comprehension. In McNamara, D.S. (Ed.), Reading comprehension strategies: Theories, interventions, and technologies, (pp. 221–240). New York: Erlbaum.Google Scholar
Glenberg, A.M. & Robertson, D.A. (1999). Indexical understanding of instructions. Discourse Processes, 28, 1–26.CrossRefGoogle Scholar
Goldman, S.R. (1985). Inferential reasoning in and about narrative texts. In Graesser, A.C. & Black, J.B. (Eds.), The psychology of questions (pp. 247–276). Hillsdale, NJ: Erlbaum.Google Scholar
Gorin, J. (2005). Manipulating processing difficulty of reading comprehension questions: The feasibility of verbal item generation. Journal of Educational Measurement, 42, 351–373.CrossRefGoogle Scholar
Gorin, J. & Embretson, S.E. (2006). Item difficulty modeling of paragraph comprehension items. Applied Psychological Measurement, 30, 394–411.CrossRefGoogle Scholar
Graesser, A.C. & Kreuz, R.J. (1993). A theory of inference generation during text comprehension. Discourse Processes, 16, 145–160.CrossRefGoogle Scholar
Graesser, A.C., Singer, M., & Trabasso, T. (1994). Constructing inferences during narrative text comprehension. Psychological Review, 101, 371–395.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle Scholar
Graesser, A.C., Millis, K.K., & Zwaan, R.A. (1997). Discourse comprehension. Annual Review of Psychology, 48, 163–189.CrossRefGoogle ScholarPubMed
Graesser, A.C. (2007). An introduction to strategic reading comprehension. In McNamara, D.S. (Ed.), Reading comprehension strategies: Theories, interventions, and technologies, (pp. 3–26). New York: Erlbaum.Google Scholar
Hannon, B. & Daneman, M. (2001). A new tool for measuring and understanding individual differences in the component processes of reading comprehension. Journal of Educational Psychology, 93, 103–128.CrossRefGoogle Scholar
Holmes, V.M. (2009). Bottom-up processing and reading comprehension in experienced adult readers. Journal of Research in Reading, 32 (3), 309–326.CrossRefGoogle Scholar
Jackson, N. E. (2005). Are university students' component reading skills related to their text comprehension and academic achievement?Learning and Individual Differences, 15, 113–139.CrossRefGoogle Scholar
Jenkins, J.R., Fuchs, L.S., Broek, P., Espin, C.A., & Deno, S.L. (2003). Accuracy and fluency in list and context reading of skilled and RD groups: Absolute and relative performance levels. Learning Disabilities Research and Practice, 18, 222–236.CrossRefGoogle Scholar
Johnson-Laird, P. N. (1983). Mental models. Towards a cognitive science of language, inference, and consciousness. Cambridge, MA: Harvard University Press.Google Scholar
Just, M.A. & Carpenter, P.A. (1980). A theory of reading: From eye fixations to comprehension. Psychological Review, 87, 329–354.CrossRefGoogle ScholarPubMed
Just, M.A. & Carpenter, P.A. (1987). The psychology of reading and language comprehension. Boston, MA: Allyn and Bacon.Google Scholar
Just, M. A. & Carpenter, P. A. (1992). A capacity theory of comprehension: Individual differences in working memory. Psychological Review, 99, 122–149.CrossRefGoogle ScholarPubMed
Kendou, P. & Broek, P. (2007). The effects of prior knowledge and text structure on comprehension processes during reading of scientific texts. Memory & Cognition, 35 (7), 1567–1577.CrossRefGoogle Scholar
Kintsch, W. (1988). The use of knowledge in discourse processing: A CI model. Psychological Review, 95, 163–182.CrossRefGoogle Scholar
Kintsch, W. (August 23, 1993). The long and crooked way toward a model of text comprehension. Current Contents, 34. Accessed from World Wide Web on September 10, 2009, at http://garfield.library.upenn.edu/classics1993/A1993LR55300001.pdf.
Kintsch, W. (1998). Comprehension: A paradigm for cognition. Cambridge, UK: Cambridge University Press.Google Scholar
Kintsch, W. (2005). An overview of top-down and bottom-up effects in comprehension: The CI perspective. Discourse Processes, 39 (2,3), 125–128.CrossRefGoogle Scholar
Kintsch, W. & Dijk, T.A. (1978). Towards a model of text comprehension and production. Psychological Review, 85, 363–394.CrossRefGoogle Scholar
Kinstch, W. & Kintsch, E. (2005). Comprehension. In Paris, S.G. & Stahl, S.A. (Eds.), Children's reading comprehension and assessment (pp. 71–92). Mahwah, NJ: Erlbaum.Google Scholar
Kintsch, W. & Rawson, K.A. (2005). Comprehension. In Snowling, M.J. and Hulme, C. (Eds.), The science of reading, (pp. 209–226). Malden, MA: Blackwell.Google Scholar
Landauer, T.K., Laham, D., & Foltz, P.W. (2000). The Intelligent Essay Assessor. IEEE Intelligent Systems, 27–31.Google Scholar
Landauer, T.K., Laham, D., & Foltz, P.W. (2003). Automated essay scoring: A cross disciplinary perspective. In Shermis, M. D. and Burstein, J. C. (Eds.), Automated essay scoring and annotation of essays with the Intelligent Essay Assessor (pp. 87–112). Mahwah, NJ: Erlbaum.Google Scholar
Leighton, J.P. & Gierl, M.J. (Eds.). (2007). Cognitive diagnostic assessment for education. Theories and applications. Cambridge, MA: Cambridge University Press.CrossRef
Lemke, M., Sen, A., Pahlke, E., Partelow, L., Miller, D., Williams, T., Kastberg, D., & Jocelyn, L. (2004). International Outcomes of Learning in Mathematics Literacy and Problem Solving: PISA 2003 Results From the U.S. Perspective. (NCES 2005–003). Washington, DC: U.S. Department of Education, National Center for Education Statistics.Google Scholar
Leslie, L. & Caldwell, J.S. (2009). Formal and informal measures of reading comprehension. In Israel, S. and Duffy, G. (Eds.), Handbook of research on reading comprehension (pp. 403–427). Mahwah, NJ: Erlbaum.Google Scholar
Linderholm, T., Virtue, S., Tzeng, Y., & Broek, P. (2004). Fluctuations in the availability of information during reading: Capturing cognitive processes using the landscape model. Discourse Processes, 37 (2), 165–186.CrossRefGoogle Scholar
Magliano, J.P., Trabasso, T., & Graesser, A.C. (1999). Strategic processing during comprehension. Journal of Educational Psychology, 91, 615–629.CrossRefGoogle Scholar
Magliano, J.P., Millis, K., Ozuru, Y., & McNamara, D.S. (2007). A multidimensional framework to evaluate reading assessment tools. In McNamara, D.S. (Ed.), Reading comprehension strategies: Theories, interventions, and technologies (pp. 107–136). New York City: Erlbaum.Google Scholar
Marr, D. (1982). Vision. San Francisco: W.H. Freeman.Google Scholar
McKoon, G. & Ratcliff, R. (1992). Inferences during reading. Psychological Review, 99, 440–466.CrossRefGoogle ScholarPubMed
Miller, J.R. & Kintsch, W. (1980). Readability and recall of short prose passages: A theoretical analysis. Journal of Experimental Psychology: Human Learning and Memory, 6, 335–354.Google Scholar
Myers, J.L., O'Brien, E.J. Albrecht, J.E., & Mason, R.A. (1994). Maintaining global coherence during reading. Journal of Experimental Psychology: Learning, memory, and Cognition, 20 (4), 876–886.Google Scholar
Myers, J. & O'Brien, E. (1998). Accessing the discourse representation during reading. Discourse Processes, 26 (2), 131–157.CrossRefGoogle Scholar
,National Center for Education Statistics (2009).The Nation's Report Card: Reading 2009 (NCES 2010–458). Institute of Education Sciences, U.S. Department of Education, Washington, D.C.Google Scholar
,National Reading Panel (NRP). (2000). Teaching children to read: An evidence-based assessment of the scientific research literature on reading and its implications for reading instruction. Washington, DC: The National Institute of Child Health and Human Development.Google Scholar
Newell, A. & Simon, H.A. (1972). Human problem solving. New Jersey: Prentice-Hall.Google Scholar
Oakhill, J.V., Cain, K.E., & Bryant, P.E. (2003). The dissociation of word reading and text comprehension: Evidence from component skills. Language and Cognitive Processes, 18, 443–468.CrossRefGoogle Scholar
,Organization for Economic Cooperation and Development. (2004). Learning for tomorrow's world: First results from PISA 2003. Paris, France: Author.Google Scholar
Perfetti, C.A. (1999). Comprehending written language: A blueprint of the reader. In Brown, C.M., & Hagoort, P. (Eds.), The neurocognition of language processing (pp. 167–208). London: Oxford University Press.Google Scholar
Perfetti, C.A., Landi, N., & Oakhill, J. (2005). The acquisition of reading comprehension skill. In Snowling, M.J. and Hulme, C. (Eds.), The science of reading, (pp. 227–247). Malden, MA: Blackwell.Google Scholar
Pressley, M. & Afflerbach, P. (1995). Verbal protocols of reading: The nature of constructively responsive reading. Hillsdale, NJ: Erlbaum.Google Scholar
Pressley, M., Woloshyn, V., & Associates, . (1995). Cognitive strategy instruction thatreally improves children's academic performance (2nd ed.). Cambridge, MA: Brookline Books.Google Scholar
Raaijmakers, J.G. & Shiffrin, R.M. (1981). Search of associative memory. Psychological Review, 88, 93–134.CrossRefGoogle Scholar
Rayner, K., Pollatsek, A., & Starr, M. (2003). Reading. In Healy, A.F. and Proctor, R.W. (Eds.), Handbook of psychology: Volume 4 experimental psychology, (pp. 549–574). Hoboken, N.J.: Wiley.Google Scholar
Reichle, E.D., Pollatsek, A., Fisher, D.L., & Rayner, K. (1998). Toward a model of eye-movement control in reading. Psychological Review, 105, 125–157.CrossRefGoogle Scholar
Rips, L.J. (1994). The psychology of proof. Cambridge, MA: MIT Press.Google Scholar
Samuels, S.J. (1994). Word recognition. In Ruddell, R. B., Ruddell, M. R., & Singer, H. (Eds.), Theoretical models and processes of reading (pp. 359–380). Newark, DE: International Reading Association.Google Scholar
Samuels, S.J. & Flor, R. (1997). The importance of automaticity for developing expertise in reading. Reading and Writing Quarterly, 13, 107–122.CrossRefGoogle Scholar
Sheehan, K.M. & Ginther, A. (2000, April). What do passage-based multiple-choice verbal reasoning items really measure? An analysis of the cognitive skills underlying performance on the current TOEFL reading section. Paper presented at the annual meeting of the National Council of Measurement in Education (NCME), New Orleans, LA.
Singer, M. & Kintsch, W. (2001). Text retrieval: A theoretical explanation. Discourse Processes, 31, 27–59.CrossRefGoogle Scholar
Snowling, M.J. & Hulme, C. (2005). Editorial part III. In Snowling, M.J. and Hulme, C. (Eds.), The science of reading, (pp. 207–208). Malden, MA: Blackwell.Google Scholar
Stanovich, K.E. (2000). Progress in understanding reading: Scientific foundations and new frontiers. New York: Guilford.Google Scholar
Trabasso, T. & Broek, P.W. (1985). Causal thinking and the representation of narrative events. Journal of Memory and Language, 24, 612–630.CrossRefGoogle Scholar
Trabasso, T., Broek, P., & Suh, S. (1989). Logical necessity and transitivity of causal relations in the representation of stories. Discourse Processes, 12, 1–25.CrossRefGoogle Scholar
Dijk, T.A. & Kintsch, W. (1983). Strategies of discourse comprehension. New York: Academic Press.Google Scholar
Broek, P., Risden, K., & Husebye-Hartmann, E. (1995). The role of readers' standards for coherence in the generation of inferences during reading. In Lorch, R.F. Jr. & O'Brien, E.J. (Eds.), Sources of coherence in text comprehension (pp. 353–373). Hillsdale, NJ: Erlbaum.Google Scholar
Broek, P., Risden, K., Fletcher, C.R., & Thurlow, R. (1996). A “landscape” view of reading: Fluctuating patterns of activation and the construction of a stable memory representation. In Britton, B.K. & Graesser, A.C. (Eds.), Models of text understanding (pp. 165–187). Mahwah, N.J.: Erlbaum.Google Scholar
Broek, P., Young, M., Tzeng, Y., & Linderholm, T. (1998). The Landscape model of reading: Inferences and the online construction of memory representation. In Oostendorp, H. & Goldman, S.R. (Eds.), The construction of mental representations during reading (pp. 71–98). Mahwah, N.J.: Erlbaum.Google Scholar
Broek, P., Rapp, D.N., & Kendeou, P. (2005). Integrating memory-based and constructionist approaches in accounts of reading comprehension. Discourse Processes, 39, 299–316.CrossRefGoogle Scholar
Verhoeven, L. & Perfetti, C. (2008). Advances in text comprehension: Model, process, and development. Applied Cognitive Psychology, 22, 293–301.CrossRefGoogle Scholar
Whitten, S. & Graesser, A.C. (2003). Comprehension of text in problem solving. In Davidson, J.E. and Sternberg, R.J. (Eds.), The psychology of problem solving (pp. 207–229). New York: Cambridge University Press.Google Scholar
Zwaan, R.A. & Radvansky, G.A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123, 162–185.CrossRefGoogle ScholarPubMed
Zwaan, R.A., Stanfield, R.A., & Yaxley, R.H. (2002). Do language comprehenders routinely represent the shapes of objects?Psychological Science, 13, 160–171.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×