Explore the vast range of titles available.

The importance of having a highly qualified teacher in every classroom is an educational necessity. Determining which teacher characteristics define teacher quality and measuring their impact on student outcomes has offered mixed results. This study explored the effect of teachers’ knowledge of language and literacy on their students’ reading outcomes in foundational skills and reading comprehension. Data from 9,640 students and 512 classroom teachers in 112 schools were analyzed using multi-level mixed effects modeling to account for the nested data. After controlling for student and teacher-level variables, results showed that teachers’ knowledge of language and literacy reliably predicted students’ spring foundational skills scores, but not reading comprehension scores. These findings support the idea that more knowledgeable teachers generate students with more favorable reading outcomes. Implications are discussed in addition to directions for future research.

In recent years, a wave of science of reading (SOR) reforms have swept across the nation. Although advocates argue that these are based on science-based research, SOR remains a contested and ambiguous notion. In this essay, Elena Aydarova uses an anthropology of policy approach to analyze advocacy efforts that promoted SOR reforms and legislative deliberations in Tennessee. Drawing on Barthes's theory of mythology, this analysis sheds light on the semiotic chains that link SOR with tradition, knowledge-building curricula, and the scaling down of social safety nets. This deciphering of SOR mythologies underscores how the focus on \"science\" distorts the intentions of these myths to naturalize socioeconomic inequality and depoliticize social conditions of precarity. This study problematizes the claims made by SOR advocates and sheds light on the ways these reforms are likely to reproduce, rather than disrupt, inequities and injustices.

Reports from research and the larger educational community demonstrate that too many students have limited ability to comprehend texts. The research reported here involved a two-year study in which standardized comprehension instruction for representations of two major approaches was designed and implemented. The effectiveness of the two experimental comprehension instructional approaches (content and strategies) and a control approach were compared. Content instruction focused student attention on the content of the text through open, meaning-based questions about the text. In strategies instruction, students were taught specific procedures to guide their access to text during reading of the text. Lessons for the control approach were developed using questions available in the teacher's edition of the basal reading program used in the participating classrooms. Student participants were all fifth graders in a low-performing urban district. In addition to assessments of comprehension of lesson texts and an analysis of lesson discourse, three assessments were developed to compare student ability to transfer knowledge gained. The results were consistent from Year 1 to Year 2. No differences were seen on one measure of lesson-text comprehension, the sentence verification technique. However, for narrative recall and expository learning probes, content students outperformed strategies students, and occasionally, the basal control students outperformed strategies students. For one of the transfer assessments, there was a modest effect in favor of the content students. Transcripts of the lessons were examined, and differences in amount of talk about the text and length of student response also favored the content approach.

Israeli 1st-grade children in two different schools in the same neighborhood who were using either a gender-stereotyped or a gender-fair basal reader were asked to judge for a series of female-stereotyped, male-stereotyped, and gender-neutral activities whether they were characteristic of females, of males, or of both. Children using the gender-fair basal reader indicated that more activities were appropriate for both males and females than did children using the gender-stereotyped reader. As well, those using the gender-fair basal reader judged stereotypically female activities as more appropriate for both males and females than did children using the gender-stereotyped reader. Type of basal reader did not impact judgments of the gender-appropriateness of either male-stereotyped or gender-neutral activities. There were no main effects or interactions with children's own sex or of mothers' work status. The importance of gender-fair portrayals in basal readers was discussed.

We investigated a small-group intervention designed to teach vocabulary and comprehension skills to preschoolers who were at risk for language and reading disabilities. These language skills are important and reliable predictors of later academic achievement. Preschoolers heard prerecorded stories 3 times per week over the course of a school year. A cluster randomized design was used to evaluate the effects of hearing storybooks with and without embedded vocabulary and comprehension lessons. A total of 32 classrooms were randomly assigned to experimental and comparison conditions. Approximately 6 children per classroom demonstrating low vocabulary knowledge, totaling 195 children, were enrolled. Preschoolers in the comparison condition did not learn novel, challenging vocabulary words to which they were exposed in story contexts, whereas preschoolers receiving embedded lessons demonstrated significant learning gains, although vocabulary learning diminished over the course of the school year. Modest gains in comprehension skills did not differ between the two groups. The Story Friends curriculum appears to be highly feasible for delivery in early childhood educational settings and effective at teaching challenging vocabulary to high-risk preschoolers.

In this article, the authors review the research on curriculum-based measurement (CBM) in reading published since the time of Marston's 1989 review. They focus on the technical adequacy of CBM related to measures, materials, and representation of growth. The authors conclude by discussing issues to be addressed in future research, and they raise the possibility of the development of a seamless and flexible system of progress monitoring that can be used to monitor students' progress across students, settings, and purposes.

This study presents results from a project to develop and pilot a new type of performance assessment of the skills used when teaching reading and writing. To provide context for this new approach, we begin by identifying the different types of knowledge that have historically been the focus of teacher assessment. Next we describe the newly developed performance assessment and present results from a pilot with 59 teacher candidates. The results suggest that the performance tasks can provide reliable evidence of the skills used to teach a range of reading and writing content across the K-6 grade span. We conclude by discussing the importance of future studies to further evaluate the validity argument for this type of performance assessment. We suggest potential uses such as studying teacher knowledge and learning, evaluating teacher education and professional development, and providing formative feedback as part of teacher preparation.

For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is leveraged to predict the difficulty of practice texts used in a reading comprehension intelligent tutoring system, iSTART. Human raters estimated the text difficulty level of 262 texts across two text sets (Set A and Set B) in the iSTART library. NLP tools were used to identify linguistic features predictive of text difficulty and these indices were submitted to both flat and hierarchical machine learning algorithms. Results indicated that including NLP indices and machine learning increased accuracy by more than 10% as compared to classic readability metrics (e.g., Flesch-Kincaid Grade Level). Further, hierarchical outperformed non-hierarchical (flat) machine learning classification for Set B (72%) and the combined set A + B (65%), whereas the non-hierarchical approach performed slightly better than the hierarchical approach for Set A (79%). These findings demonstrate the importance of considering deeper features of language related to text difficulty as well as the potential utility of hierarchical machine learning approaches in the development of meaningful text difficulty classification.

This study analyzed the prevalence and characteristics of low-frequency and rare words, together described as rarer words, in elementary-level texts, examining both narrative and expository materials to assess their vocabulary demands. By mapping the nature of shifts in rarer words across grade levels and text types, this research aimed to better understand the lexical challenges students face as they progress as readers. Analyzing a corpus of 300,000 words from narrative and expository texts at grades 1, 3, and 5, the research employed both quantitative and qualitative methods. Quantitatively, a digital program categorized words into four frequency groups—high, medium, low, and rare—while examining features of word length and age of acquisition that can influence word meaning recognition. Qualitatively, the analysis classified rarer words into 13 lexical categories and assessed their morphological family membership. The findings reveal an increase in total rarer words from 5.7% to 8.7% across grades, alongside a major rise in unique rarer words (32% to 43%). The complexity of features predicting word recognition—word length and age of acquisition—also escalates with grade level. Notably, 23% of rarer words are forms typically not taught in vocabulary instruction, such as proper names, while 76% of rare words belong to morphological families in the high-, medium-, and low-frequency word zones. These results highlight the need for targeted vocabulary instruction that incorporates the complexities of rarer word usage in authentic texts, ultimately aiming to enhance students’ reading comprehension.