This article explores the role of text cohesion in the comprehension and production of text. While most discourse models have considered the roles of the text features and the reader, the crucial role of writers’ epistemic stance has not been widely considered. The thesis explored here is that levels of cohesion emerge in text based on the epistemic stance of the author relative to the reader. Evidence is provided indicating that text genres show compensatory relationships between different features related to (...) text difficulty. For example, while science texts have more challenging words than do narratives, they tend to have higher cohesion and simpler syntax. These text profiles indicate that skilled writers have an awareness of readers’ needs. By contrast, less skilled writers seem to have less sensitivity to the interplay between textual dimensions and less audience awareness. For example, evidence is reviewed showing that more proficient essays are characterized by lower cohesion than less proficient essays: less skilled writers tend to use more cohesive cues than do more skilled writers. To the extent that an author understands the readers’ needs, the author has a more successful epistemic stance toward the reader. This stance is partially evidenced by the crucial role of cohesion in text comprehension and writing. (shrink)

Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research (...) exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA. (shrink)

The goal of this study was to assess the relationships between computational approaches to analyzing constructed responses made during reading and individual differences in the foundational skills of reading in college readers. We also explored if these relationships were consistent across texts and samples collected at different institutions and texts. The study made use of archival data that involved college participants who produced typed constructed responses under thinking aloud instructions reading history and science texts. They also took assessments of vocabulary (...) knowledge and proficiency in comprehension. The protocols were analyzed to assess two different ways to determine their cohesion. One approach involved assessing how readers established connections with themselves. The other approach involved assessing connections between the constructed responses and the texts that were read. Additionally, the comparisons were made by assessing both lexical and semantic comparisons. The result showed that both approaches for analyzing cohesion and making the comparisons were correlated with vocabulary knowledge and comprehension proficiency. The implications of the results for theory and practice are discussed. (shrink)

Since 2020, the COVID-19 pandemic had an impact on education worldwide. There is increased discussion of possible negative effects on students’ learning outcomes and the need for targeted support. We examined fourth graders’ reading achievement based on a school panel study, representative on the student level, with N = 111 elementary schools in Germany. The students were tested with the Progress in International Reading Literacy Study instruments in 2016 and 2021. The analysis focused on total average differences in reading achievement (...) between 2016 and 2021, average differences controlling for student composition, and changes in achievement gaps between student subgroups. The methodological approach met international standards for the analysis of large-scale assessments. The results showed a substantial decline in mean reading achievement. The decline corresponds to one-third of a year of learning, even after controlling for changes in student composition. We found no statistically significant changes of achievement gaps between student subgroups, despite numerical tendencies toward a widening of achievement gaps between students with and without immigration background. It is likely that this sharp achievement decline was related to the COVID-19 pandemic. The findings are discussed in terms of further research needs, practical implications for educating current student cohorts, and educational policy decisions regarding actions in crises such as the COVID-19 pandemic. (shrink)