The DOI matches its Crossref record; 114 of the 115 references it cites were found in a registry or an index.
Computational Analyses of Multilevel Discourse Comprehension
Open accessAbstract
The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kilgarriff, A. (2000) · Language · doi:10.2307/417141 · Cited by 11,529
Bruner, J. (1986) · doi:10.4159/9780674029019 · Cited by 8,657
Eye movements in reading and information processing: 20 years of research
Rayner, K. (1998) · Psychological Bulletin · doi:10.1037/0033-2909.124.3.372 · Cited by 7,979
Building a Large Annotated Corpus of English: The Penn Treebank
Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
Halliday, M. A. K., & Hasan, R. (2014) · Routledge eBooks · doi:10.4324/9781315836010 · Cited by 7,392
Actual Minds, Possible Worlds.
Mergler, N. L., Schleifer, R., & Bruner, J. S. (1986) · MLN · doi:10.2307/2905728 · Cited by 6,626
Landauer, T. K., & Dumais, S. T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.211 · Cited by 6,282
Strategies of Discourse Comprehension
Staczek, J. J., van Dijk, T. A., & Kintsch, W. (1985) · Modern Language Journal · doi:10.2307/326517 · Cited by 5,377
Toward a model of text comprehension and production.
Kintsch, W., & van Dijk, T. A. (1978) · Psychological Review · doi:10.1037/0033-295x.85.5.363 · Cited by 5,298
Variation across Speech and Writing
Biber, D. (1988) · doi:10.1017/cbo9780511621024 · Cited by 5,227
Research works printed but not linked: 16
- Baayen R. H., 1995, The CELEX Lexical Database (Release 2) {CD‐ROM}
- Charniak E., 2000, Proceedings of the First Conference on North American Chapter of the Association for Computational Linguistics, 132
- Gough P. B., 1972, Language by ear and by eye, 331
- Hempelmann C. F., 2005, Proceedings of the 27th Annual Meetings of the Cognitive Science Society, 941
- Hewitt P. G., 1998, Conceptual physics
- Koslin B. I., 1987, The DRP: An effective measure in reading
- McCarthy P. M., 2006, Proceedings of the Florida Artificial Intelligence Research Society International Conference (FLAIRS), 764
- McClelland J. L., 1986, Parallel distributed processing, 122
- McNamara D. S., Assessing reading in the 21st century: Aligning and applying advances in the reading and measurement sciences
- McNamara D. S., 2008, Towards a comprehensive model of comprehension, The psychology of learning and motivation, 297
- Meyer B. J. F., 2007, Reading comprehension strategies: Theories, interventions, and technologies, 347
- Pennebaker J. W., 2007, Linguistic inquiry and word count
- Prince E. F., 1981, Radical pragmatics, 223
- Rayner K., 1994, The psychology of reading
- VanderVeen A., 2007, Theories of text comprehension: The importance of reading strategies to theoretical foundations of reading comprehension, 137
- Williams P. J., 2007, Reading comprehension strategies: theories, interventions, and technologies, 199
Cited by
Sorted by citations
Items 101–200 of 325
Burkhart, C., Lachner, A., & Nückles, M. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235209 · Cited by 17
Keys to Detecting Writing Flexibility Over Time: Entropy and Natural Language Processing
Snow, E. L., Allen, L. K., Jacovina, M. E., Crossley, S. A., Perret, C. A., & McNamara, D. S. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2015.23.4 · Cited by 18
“Importantly, these Easability Components are aligned within an existing multilevel framework of comprehension (Graesser & McNamara, 2011).”
Self-citationMills, C., & D’Mello, S. K. (2015) · Educational Data Mining · Cited by 18
Kumar, Y., Parekh, S., Singh, S., Li, J. J., Shah, R. R., & Chen, C. (2023) · Dialogue & Discourse · doi:10.5210/dad.2023.101 · Cited by 35
“Several research studies have investigated how finding and scoring discourse from essays helps to provide a better holistic score to essays (McNamara et al., 2014; Graesser and McNamara, 2011; Burstein et al., 2001; Nadeem et al., 2019; Burstein et al., 1998).”
Flores-Carrasco, P. G., Mújica, A. D., & Herrera, I. E. L. (2016) · Revista Electrónica Educare · doi:10.15359/ree.21-1.7 · Cited by 17
Ozernov‐Palchik, O., Centanni, T. M., Beach, S. D., May, S. C., Hogan, T. P., & Gabrieli, J. D. E. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117570 · Cited by 17
Pyburn, D. T., & Pazicni, S. (2014) · Journal of Chemical Education · doi:10.1021/ed500006u · Cited by 17
Constructing inferences in naturalistic reading contexts
Graesser, A. C., Li, H., & Feng, S. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781107279186.014 · Cited by 17
Self-citationVieira, L. N. (2016) · Bristol Research (University of Bristol) · doi:10.14456/nvts.2016.16 · Cited by 18
Natural language processing as a technique for conducting text‐based research
Allen, L. K., Creer, S. D., & Poulos, M. C. (2021) · Language and Linguistics Compass · doi:10.1111/lnc3.12433 · Cited by 19
“Additionally, text manipulation can lead to unintended changes; for example, increasing cohesion tends to increase sentence length (Graesser & McNamara, 2011).”
Natural language processing and discourse complexity studies
Solnyshkina, M. I., McNamara, D. S., & Zamaletdinov, R. R. (2022) · Russian Journal of Linguistics · doi:10.22363/2687-0088-30171 · Cited by 16
“16 https://wordnet.princeton.edu/ и Д. Макнамара (Graesser & McNamara 2011) предлагают следующее предложение и его пропозициональный анализ: When the board met on Friday, they discovered they were bankrupt.”
Self-citationShi, G., Lippert, A. M., Shubeck, K. T., Fang, Y., Chen, S., Pavlik, P. I., Greenberg, D., & Graesser, A. C. (2018) · Behaviormetrika · doi:10.1007/s41237-018-0065-9 · Cited by 16
Self-citationNiu, J., & Jiang, Y. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-02986-7 · Cited by 15
“As it can be applied to almost any text, its metrics can be used to compare texts belonging to various genres (Graesser and McNamara, 2011).”
Designing practical science assessments in England: students’ engagement and perceptions
Masri, Y. E., Erduran, S., & Ioannidou, O. (2021) · Research in Science & Technological Education · doi:10.1080/02635143.2021.1872519 · Cited by 15
“Moreover, a comparison of language complexity using CohMetrics (Graesser et al. 2014; Graesser and McNamara 2011) of the first two assessment tasks with two physics GCSE assessment tasks covering the same concepts suggests that the language complexity in the questions Figure 5.”
MethodA Comparative Study on English and Chinese Word Uses with LIWC
Li, H., Cai, Z., Graesser, A. C., & Duan, Y. (2012) · The Florida AI Research Society · Cited by 15
Self-citationLiu, Y., & Liang, J. (2024) · Linguistics and Education · doi:10.1016/j.linged.2024.101273 · Cited by 14
Hayashi, Y. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22244-4_12 · Cited by 16
Supporting Social Deliberative Skills Online: The Effects of Reflective Scaffolding Tools
Murray, T., Stephens, A. L., Woolf, B. P., Wing, L., Xu, X., & Shrikant, N. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39371-6_36 · Cited by 14
A theoretically motivated method for automatically evaluating texts for gist inferences
Wolfe, C. R., Dandignac, M., & Reyna, V. F. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01284-4 · Cited by 15
Computational linguistics analysis of leaders during crises in authoritarian regimes
Dowell, N., Windsor, L., & Graesser, A. C. (2015) · Dynamics of Asymmetric Conflict · doi:10.1080/17467586.2015.1038286 · Cited by 14
“Coh-Metrix provides hundreds of measures at multiple levels, including genre, cohesion, syntax, word characteristics, as well as other aspects of language and discourse (Graesser & McNamara, 2011; Graesser, McNamara, & Kulikowich, 2011).”
BackgroundSelf-citationClinton‐Lisell, V., Legerski, E. M., & Rhodes, B. (2019) · Frontiers in Education · doi:10.3389/feduc.2019.00110 · Cited by 14
“Pronouns can benefit reading comprehension because the process of connecting a pronoun to its referent can assist in making connections in the text (Graesser and McNamara, 2011).”
BackgroundHow features of digital text affect reading efficiency and comprehension
Voiskounsky, A. E., & Solodov, M. Y. (2020) · Psychology in Education · doi:10.33910/2686-9527-2020-2-2-134-142 · Cited by 13
Haag, N., Roppelt, A., & Heppt, B. (2015) · Learning and Individual Differences · doi:10.1016/j.lindif.2015.08.010 · Cited by 13
Toyama, Y. (2021) · Reading Research Quarterly · doi:10.1002/rrq.440 · Cited by 12
Mining Social Deliberation in Online Communication -- If You Were Me and I Were You
Xu, X., Murray, T., Woolf, B. P., & Smith, D. A. (2013) · Cited by 12
The impact of conversational agents’ language on summary writing
Li, H., & Graesser, A. C. (2021) · Journal of Research on Technology in Education · doi:10.1080/15391523.2020.1826022 · Cited by 12
“…analysis tool was developed based on the multilevel theoretical framework, including textbase, situation model, genre, rhetorical structure, and pragmatic communication (Graesser & McNamara, 2011), most of which are similar to those listed in the prag-matics-based framework (Snow & Uccelli, 2009).”
MethodSelf-citationTowards Careful Practices for Automated Linguistic Analysis of Group Learning
Howley, I. K., & Rosé, C. P. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.33.12 · Cited by 12
“…categories and word frequency), syntax (via sentence level structure), text base (diversity of vocabulary and referring to objects through pronouns, etc.), situation model (computed as aspects of cohesion), and genre & rhetorical structure (referred to as narrativity) (Graesser & McNamara, 2011).”
BackgroundBraun, I., & Nückles, M. (2014) · Science Education · doi:10.1002/sce.21117 · Cited by 12
Nahatame, S. (2023) · Bilingualism Language and Cognition · doi:10.1017/s136672892200089x · Cited by 11
Quinn, M. S., Campbell, K., & Keane, M. T. (2020) · Cognition · doi:10.1016/j.cognition.2020.104520 · Cited by 11
An Analysis of the Linguistic Features of Popular Chinese Online Fantasy Novels
Jin, J., & Liu, S. (2022) · Discourse Processes · doi:10.1080/0163853x.2022.2028432 · Cited by 11
“The LSA model allows researchers to find information beyond the lexical level in texts and reveals semantical relations between the entities of interest (Graesser & McNamara, 2011).”
BackgroundInfluentialVideo and Computer Games as Grounding Experiences for Learning
Black, J. B., Khan, S., & Huang, S.-C. D. (2014) · Oxford University Press eBooks · doi:10.1093/acprof:osobl/9780199896646.003.0020 · Cited by 11
A multi-dimensional analysis of writing flexibility in an automated writing evaluation system
Allen, L. K., Likens, A. D., & McNamara, D. S. (2018) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3170358.3170404 · Cited by 11
“These components provide measures of the principal sources of text difficulty and are well aligned with an existing multilevel framework [34].”
BackgroundSelf-citationAdvanced Educational Technology for Science Inquiry Assessment
Li, H., Gobert, J. D., Graesser, A. C., & Dickler, R. (2018) · Policy Insights from the Behavioral and Brain Sciences · doi:10.1177/2372732218790017 · Cited by 11
“Coh-Metrix can extract hundreds of language features at multiple textual levels from the word level to the sentence, paragraph, text, and genre (Graesser & McNamara, 2011).”
BackgroundSelf-citationPredicting the difficulty of EFL reading comprehension tests based on linguistic indices
Rafatbakhsh, E., & Ahmadi, A. (2023) · Asian-Pacific Journal of Second and Foreign Language Education · doi:10.1186/s40862-023-00214-4 · Cited by 15
“Also, informational texts include more unfamiliar words and require more knowledge (Graesser & McNamara, 2011).”
BackgroundDavidson, M. M., & Weismer, S. E. (2018) · Autism & Developmental Language Impairments · doi:10.1177/2396941518806109 · Cited by 10
“…and comprehension, we know that narrative fiction texts are related to individual reader abilities but are generally considered easier to comprehend (Eason et al., 2012; Graesser & McNamara, 2011), and a child’s reading ability predicts how much they choose to read (van Bergen et al., 2018).”
BackgroundLiu, Y., & Tseng, W. (2019) · System · doi:10.1016/j.system.2019.102145 · Cited by 10
Writing Quality Predictive Modeling: Integrating Register-Related Factors
Wang, H., & Troia, G. A. (2023) · Written Communication · doi:10.1177/07410883231185287 · Cited by 10
Does high perceptual load assist in reducing the seductive details effect?
Wang, Z., Ardasheva, Y., & Lin, L. (2019) · Educational Psychology · doi:10.1080/01443410.2019.1686465 · Cited by 11
“According to reading comprehension literature (Goldman et al., 2016; Graesser & McNamara, 2011), learning from a single text involves readers constructing at least three layers of memory representations capturing different aspects of the text, namely, (a) the surface level, “an unanalyzed verbatim…”
MethodACHIEVING ACTIVE LEARNING AND DEEP LEARNING WITH MEDIA USING THE EXAMPLE OF TEACHING FINANCE
Zureck, A. (2021) · Problems of Education in the 21st Century · doi:10.33225/pec/21.79.485 · Cited by 10
“Both points have a negative impact on the comprehension of informational texts and require a higher level of processing (Graesser & McNamara, 2011).”
Understanding reading as a form of language-use: A language game hypothesis
Wallot, S. (2015) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2015.07.006 · Cited by 10
Toward a Real-time (Day) Dreamcatcher: Detecting Mind Wandering Episodes During Online Reading.
Mills, C., & D’Mello, S. K. (2015) · Educational Data Mining · Cited by 10
COGNITIVE AND LINGUISTIC FACTORS OF READING ARABIC: THE ROLE OF MORPHOLOGICAL AWARENESS IN READING
Tibi, S. (2016) · QSpace (Queen's University Library) · Cited by 10
Fluency Differences by Text Genre in Proficient and Struggling Secondary Students
Paige, D. D., Magpuri‐Lavell, T., Rasinski, T. V., & Rupley, W. (2015) · Advances in Literary Study · doi:10.4236/als.2015.34016 · Cited by 9
“Graesser & McNamara (2011) suggest these levels reflect a compositional viewpoint to which is attached a “knowledge and process point of view” (p. 373).”
BackgroundXiao-hua, L., & Brown, G. (2019) · Journal of Research in Reading · doi:10.1111/1467-9817.12275 · Cited by 9
How Good Is Popularity? Summary Grading in Crowdsourcing.
Li, H., Cai, Z., & Graesser, A. C. (2016) · Educational Data Mining · Cited by 9
Self-citationThe effects of genetic and environmental factors on writing development
Erbeli, F., Hart, S. A., Kim, Y. G., & Taylor, J. E. (2017) · Learning and Individual Differences · doi:10.1016/j.lindif.2017.08.005 · Cited by 9
Computer-Based Assessment Of Essays Based On Multiple Documents
Magliano, J. P., Hastings, P., Kopp, K. J., Blaum, D., & Hughes, S. (2018) · Routledge eBooks · doi:10.4324/9781315627496-28 · Cited by 9
Lippert, A. M., Gatewood, J. D., Cai, Z., & Graesser, A. C. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-22341-0_26 · Cited by 10
Self-citationMoody Agents: Affect and Discourse During Learning in a Serious Game
Forsyth, C. M., Graesser, A. C., Olney, A. M., Millis, K., Walker, B. S., & Cai, Z. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-19773-9_14 · Cited by 9
“Finally, discourse features of the student input during interaction with OperationARIES! were analyzed using the computational linguistic tool, Coh-Metrix.”
MethodInfluentialSelf-citationSurprise: Youve got some explaining to doPreprint
Foster, M. I., & Keane, M. T. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1308.2236 · Cited by 13
“In discourse research (cf., Graesser & McNamara, 2011), the explanatory coherence of texts is often operationalized by using latent semantic analysis (LSA) scores, where higher LSA scores indicate that the one text is more coherent than another (Landauer & Dumas, 1996, 1997).”
BackgroundReadability as a measure of textual complexity: determinants and evidence in Brazilian companies
de Souza, J. A. S., & Borba, J. A. (2021) · Revista Contabilidade & Finanças · doi:10.1590/1808-057x202114180 · Cited by 11
“This software, documented by Graesser et al. (2004), was developed, refined, and tested between 2002 and 2011, at the University of Memphis.”
BackgroundMethodSanabria, A., Restrepo, M., Walker, E., & Glenberg, A. M. (2022) · Journal of Speech, Language and Hearing Research · doi:10.1044/2021_jslhr-21-00266 · Cited by 5
Pinchbeck, G. G. (2017) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/28660 · Cited by 8
Distractions in digital reading: a meta-analysis of attentional interference effects
Shen, Y. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1671214 · Cited by 17
Detecting Financial Statement Fraud through Multidimensional Analysis of Text Readability
Yang, F., David, J. M., & Chang, C.-C. A. (2023) · Journal of Forensic Accounting Research · doi:10.2308/jfar-2021-019 · Cited by 8
The Imagination Principle in Multimedia Learning
Leopold, C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333.039 · Cited by 7
Graesser, A. C., Greenberg, D., Frijters, J. C., & Talwar, A. (2021) · Revista signos · doi:10.4067/s0718-09342021000301089 · Cited by 7
“The theoretical model underlying the AutoTutor lessons consisted of the multilevel framework of Graesser and McNamara (2011), as well as other discourse processing models (Kintsch, 1998; Perfetti, 1999).”
BackgroundMethodSelf-citationGazzola, M. G., Leal, S. E., Pedroni, B., Rocha, F. T., Pompéia, S., & Aluísio, S. M. (2022) · Language Resources and Evaluation · doi:10.1007/s10579-021-09571-3 · Cited by 7
“They are grouped into three levels—related to words, sentences, and connections between sentences, as we replicated the the work by Graesser et al. (2011), and are detailed below.”
BackgroundMethodSnow, E. L., Allen, L. K., Jacovina, M. E., Perret, C. A., & McNamara, D. S. (2015) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2723576.2723592 · Cited by 7
“Narrativity has previously been identified as an important component of writing through the use of natural language processing techniques [7, 8].”
BackgroundSelf-citationReading into the Text: Investigating the Influence of Text Complexity on Cognitive Engagement.
Vega, B., Shi, F., Lehman, B. A., Graesser, A. C., & D’Mello, S. K. (2013) · Educational Data Mining · Cited by 7
Self-citationThe Readability of Malaysian English Children Books: A Multilevel Analysis
Ismail, A., Yusof, N., & Yunus, K. B. (2016) · International Journal of Applied Linguistics & English Literature · doi:10.7575/aiac.ijalel.v.5n.6p.214 · Cited by 7
“Graesser and McNamara (2011) specifically presented a multilevel theoretical framework based on studies of reading comprehension in various fields which includes six levels of discourse (text and spoken), where comprehension can happen.”
BackgroundMethodLi, H., Gobert, J. D., Dickler, R., & Morad, N. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-93843-1_20 · Cited by 7
Wei, J., & Chen, Z. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104437 · Cited by 7
Arai, Y., & Takizawa, K. (2024) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2024.100110 · Cited by 12
Khodadady, E. (2017) · Sociology International Journal · doi:10.15406/sij.2017.01.00016 · Cited by 6
“It provides measures at five discourse levels of words, syntax, text base, situation model, and genre [32,19].”
BackgroundImportance of Learner Characteristics in Intelligent Tutoring for Adult Literacy
Hollander, J., Sabatini, J., Graesser, A. C., Greenberg, D., O’Reilly, T., & Frijters, J. C. (2023) · Discourse Processes · doi:10.1080/0163853x.2023.2203543 · Cited by 6
“…of Education’s College and Career Readiness Standards for Adult Education (Pimentel, 2013), a multilevel framework of discourse comprehension (Graesser & McNamara, 2011), and a face-to-face reading comprehension curriculum that was successful for low-skill readers in schools (Lovett et al.,…”
BackgroundSelf-citationEffectiveness of Automated Chinese Sentence Scoring with Latent Semantic Analysis
Liao, C.-H., Kuo, B., & Pai, K.-C. (2012) · The Turkish Online Journal of Educational Technology · Cited by 6
Linguistic Variables Determining the Difficulty of Eiken Reading Passages
Hamada, A. (2015) · JLTA Journal · doi:10.20622/jltajournal.18.0_57 · Cited by 6
“The central feature of Coh-Metrix is its ability to compute the numerous linguistic variables involved in the cognitive process of reading comprehension (Crossley et al., 2008; Graesser et al., 2004; Graesser & McNamara, 2011).”
BackgroundAn analysis of the continuity of elementary and middle school English textbooks using Coh-Metrix.
Kim, J.-R., & 양지윤 (2012) · English Teaching · doi:10.15858/engtea.67.2.201207.319 · Cited by 6
The Effects of Text Complexity on Online Review Helpfulness
Hine, M. J. (2015) · Communications of the IIMA · doi:10.58729/1941-6687.1353 · Cited by 6
“These include connectives that are additive (also, moreover), temporal (and then, after, during), causal (because, so) and logical operators (therefore, if, and, or) (Graesser & McNamara, 2011).”
BackgroundInfluentialWei, Y., Evers-Vermeul, J., & Sanders, T. J. M. (2020) · Dialogue & Discourse · doi:10.5087/dad.2020.103 · Cited by 6
“For instance, they can use connectives such as so and therefore to provide the reader with information on the type of coherence relation to be established, in this case a causal one (Britton 1994, Graesser & McNamara 2011, Mak & Sanders 2010, van Silfhout et al. 2014, 2015).”
BackgroundUmarji, O., Day, S., Xu, Y., Zargar, E., Yu, R., & Connor, C. M. (2020) · Reading and Writing · doi:10.1007/s11145-020-10081-x · Cited by 6
Understanding Reading Comprehension Performance in High School Students
Kwiatkowska-White, B. (2012) · QSpace (Queen's University Library) · Cited by 6
Li, X., Wang, X., & Daems, J. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2026.2631658 · Cited by 5
Hamza, M. M. A. (2024) · International Conference on IoT, Communication and Automation Technology (ICICAT) · doi:10.1109/icicat62666.2024.10923368 · Cited by 5
RetractedConstructing explanatory models from text-based information: Why instructional tools help
James, K., & Goldman, S. R. (2020) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2020.101918 · Cited by 5
An Introduction to Multilevel Analyses of Text Readability in Accounting and Finance
Yang, F., Chang, C.-C. A., & Mo, L. (2021) · Journal of Emerging Technologies in Accounting · doi:10.2308/jeta-19-09-02-37 · Cited by 5
Wang, Q., & Xu, J. (2023) · Linguistica Antverpiensia New Series – Themes in Translation Studies · doi:10.52034/lans-tts.v22i.768 · Cited by 5
Bahari, A., Alavinia, P., & Mohammadi, M. (2024) · Journal of Computer Assisted Learning · doi:10.1111/jcal.13005 · Cited by 8
Attentional mediators of the effect of interest on comprehension
Gericke, C., Soemer, A., & Schiefele, U. (2024) · Learning and Instruction · doi:10.1016/j.learninstruc.2024.102010 · Cited by 5
Kumaresan, V., Jeyakarthic, M., P., M., Jona Innisai Rani, P., Mohan, E., & R, S. K. (2025) · International Conference on Signal Processing, Computing and Control (ISPCC) · doi:10.1109/ispcc66872.2025.11039410 · Cited by 5
Myers, J. C., McCarthy, P. M., Duran, N. D., & McNamara, D. S. (2010) · Behavior Research Methods · doi:10.3758/s13428-010-0021-4 · Cited by 5
Self-citationTitles support the development of coherent situation models
Christofalos, A. L., Raney, G. E., Daniel, F. K., & Demos, A. P. (2020) · Journal of Research in Reading · doi:10.1111/1467-9817.12315 · Cited by 5
A Measure of Text Formality as a Human Construct
Li, H., Cheng, Q., & Graesser, A. C. (2015) · The Florida AI Research Society · Cited by 5
Self-citationTyped versus Spoken Conversations in a Multi-party Epistemic Game
Morgan, B., Burkett, C. M., Bagley, E., & Graesser, A. C. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-21869-9_86 · Cited by 5
Self-citationPsychological Aspects of AI Enhanced Learning Experiences
Kok, C. L., Ho, C. K., Koh, Y. Y., Heng, J. B. W., & Teo, T. H. (2024) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon61640.2024.10902839 · Cited by 4
“Heffernan [4].”
Applying Semantic Analysis to Training, Education, and Immersive Learning
Robson, R., & Ray, F. (2012) · Cited by 4
Chasing Theory with Technology: A Quest to Understand Understanding
McNamara, D. S. (2021) · Discourse Processes · doi:10.1080/0163853x.2021.1917914 · Cited by 4
“As such, while we included basic indices such as number of words, parts of speech, and so on, our ultimate goal was to explain and predict text difficulty guided by theories of comprehension (Graesser & McNamara, 2011).”
BackgroundSelf-citationDeveloping a cognitive model of L2 reading comprehension for evaluative purposes in an EMI context
Toprak-Yıldız, T. E. (2022) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2022.101200 · Cited by 6
Readability Assessment of Advanced English Textbooks: A Corpus-Linguistic Study
Hu, T. (2022) · Theory and Practice in Language Studies · doi:10.17507/tpls.1301.29 · Cited by 4
Bini, L. M., & Fissi, S. (2025) · Social Responsibility Journal · doi:10.1108/srj-10-2023-0547 · Cited by 4
Information Quality Dimensions for Maps and Texts
Batini, C., & Scannapieco, M. (2016) · Data-centric systems and applications · doi:10.1007/978-3-319-24106-7_3 · Cited by 4
Predicting Expository Text Processing: Causal Content Density as a Critical Expository Text Metric
Follmer, D. J., Li, P., & Clariana, R. B. (2021) · Reading Psychology · doi:10.1080/02702711.2021.1912867 · Cited by 4
“…selected texts was individually analyzed on specific text metrics based on research examining features of text related to syntactic pattern density and believed to be supportive of readers’ developing situation models (Graesser & McNamara, 2011; Van Dijk & Kintsch, 1983; Zwaan & Radvansky, 1998).”
BackgroundMethodInfluentialIntegrating SARA Assessment with Reading Comprehension Training in AutoTutor
Smith, E. H., Hollander, J., Graesser, A. C., Sabatini, J., & Hu, X. (2021) · English Teaching · doi:10.15858/engtea.76.s1.202109.17 · Cited by 4
Self-citationNykyporets, S., & Chopliak, V. (2023) · ГРААЛЬ НАУКИ · doi:10.36074/grail-of-science.15.09.2023.58 · Cited by 4
“Building on the ideas of Graesser and McNamara [4], this study promotes interdisciplinary learning as a conduit for cognitive flexibility.”
Text content variables as a function of comprehension: Propositional discourse analysis
Solnyshkina, M. I., Harkova, E. V., & Ebzeeva, Y. N. (2023) · Russian Journal of Linguistics · doi:10.22363/2687-0088-35915 · Cited by 4
Formality of the Chinese collective leadership
Li, H., & Graesser, A. C. (2016) · Behavior Research Methods · doi:10.3758/s13428-016-0775-4 · Cited by 4
“These dimensions align with multilevel theoretical frameworks of language and discourse that differentiate structures, strategies, and cognitive processes at different levels of language and discourse (Graesser & McNamara, 2011; Kintsch, 1998).”
BackgroundSelf-citationToyama, Y. (2019) · eScholarship (California Digital Library) · Cited by 4
The Adaptive Features of an Intelligent Tutoring System for Adult Literacy
Shi, G., Wang, L., Zhang, L., Shubeck, K. T., Peng, S., Hu, X., & Graesser, A. C. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77857-6_42 · Cited by 4
Self-citation
Metadata
- Authors
- Graesser, A. C., & McNamara, D. S.
- Affiliations
- University of Memphis (US)
- Corresponding author
- Graesser, Arthur C.
- Venue
- Topics in Cognitive Science
- Publisher
- Wiley
- Published
- 2011-04
- Volume
- 3
- Issue
- 2
- Pages
- 371-398
- ISSN
- 1756-8757 (ISSN-L)
- 1756-8765
- OpenAlex
- W2087016971
- Cited by
- 325
- References
- 115
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 13 · 2023: 24 · 2022: 46 · 2021: 27 · 2020: 22 · 2019: 22 · 2018: 17 · 2017: 13 · 2016: 23 · 2015: 28 · 2014: 27 · 2013: 18 · 2012: 15
- FWCI
- 3.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Topics in Cognitive Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (0904909, DRK12, 0918409, 0834847, 0325428)
- U.S. Department of Defense (H9C104-07-0014)
- Institute of Education Sciences (R305G020018, R305A080594, R305B070349, R305A080589, R305H050169)
- Topics
- Social Sciences › Linguistics and Language › Text Readability and Simplification
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Social Sciences › Linguistics and Language › Linguistics and Discourse Analysis
- Keywords
- Coh-Metrix, textual cohesion, situation model, textbase, pragmatic communication, narrative texts, scientific texts
- MeSH terms
- Artificial Intelligence, Cognition, Humans, Linguistics, Reading, Semantics, User-Computer Interface, Comprehension
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
