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We developed a sustained content literacy intervention that emphasized building domain and topic knowledge from Grade 1 to Grade 2 and evaluated transfer effects on students' reading comprehension outcomes. The Model of Reading Engagement (MORE) intervention emphasizes thematic lessons that provide an intellectual framework for helping students connect new learning to a general schema (i.e., how scientists study past events). A total of 30 elementary schools (N = 2,952 students; N = 144 teachers) were randomly assigned to a treatment or control group. Over 12 months, the treatment group students participated in (a) spring Grade 1 thematic content literacy lessons in science and social studies followed by wide reading of thematically related informational texts during summer, and (b) fall to spring Grade 2 thematic content literacy lessons in science. After implementation of Grade 1 thematic content literacy lessons and summer support for reading, treatment group students experienced smaller summer losses on a domain-general measure of reading than control group students. Following the sustained implementation of thematic content literacy lessons in science through Grade 2, treatment group students also outperformed their control group peers on a science content reading comprehension outcome (ES = 0.18). Furthermore, we found transfer effects on science content reading comprehension that varied by passage-item type (near-, mid-, and far-transfer passages determined by the inclusion and number of directly taught words in passages). A sustained content literacy intervention that aligns content and instruction across grades can help students transfer knowledge to novel reading comprehension tasks.

The purpose of the study was to assess the volume of academic vocabulary in elementary grades disciplinary textbooks. Academic vocabulary was examined in a corpus of best-selling elementary grades textbooks in three disciplinary areas--science, mathematics, and social studies. Academic words in texts were determined through automated procedures involving statistical modeling. Four academic vocabulary variables were created: Total Academic Words; Discipline-Match Academic Words (science domain-specific academic words in science textbooks, and so on); High Challenge Total Academic Words; and High Challenge Discipline-Match Academic Words. Longitudinal multilevel Poisson regression was conducted for selected research issues. Main conclusions were: (a) The estimated overall elementary grades volume of academic vocabulary in disciplinary textbooks was relatively high. Summed across all grades and disciplines, 31% of all of the estimated unique word types in the textbooks were academic word types. By the end of elementary school, children who read or listened to disciplinary textbooks like the ones in the present study corpus would have been exposed to approximately one academic word type for every three unique word types encountered. (b) Moreover, approximately one or two of every four or five academic word types was estimated to be a word that would present challenge to typically developing and struggling students. (c) For all three disciplines, with minor exception, the estimated volume of newly-appearing academic words in a grade increased through the earliest grades, tended to peak in third or fourth grade, and then decelerated slightly thereafter.

This study investigated the effectiveness of the Model of Reading Engagement (MORE), a content literacy intervention, on first graders' science domain knowledge, reading engagement, and reading comprehension. The MORE intervention emphasizes the role of domain knowledge and reading engagement in supporting reading comprehension. MORE lessons included a 10-day thematic unit that provided a framework for students to connect new learning to a meaningful schema (i.e., Arctic animal survival) and to pursue mastery goals for acquiring domain knowledge. A total of 38 first-grade classrooms (N = 674 students) within 10 elementary schools were randomly assigned to (a) MORE at school (MS), (b) MORE at home, (MS-H), in which the MS condition included at-home reading, or (c) typical instruction. Since there were minimal differences in procedures between the MS and MS-H conditions, the main analyses combined the two treatment groups. Findings from hierarchical linear models revealed that the MORE intervention had a positive and significant effect on science domain knowledge, as measured by vocabulary knowledge depth (effect size [ES] = 0.30), listening comprehension (ES = 0.40), and argumentative writing (ES = 0.24). The MORE intervention effects on reading engagement as measured by situational interest, reading motivation, and task orientations were not statistically significant. However, the intervention had a significant, positive effect on a distal measure of reading comprehension (ES = 0.11), and there was no evidence of Treatment × Aptitude interaction effects. Content literacy can facilitate first graders' acquisition of science domain knowledge and reading comprehension without contributing to Matthew effects.

Academic vocabulary networks were examined in 3 elementary grades textbook programs (first through fifth grade) in 3 domains--science, mathematics, and social studies. Within each program, a given network consisted of a focal domain-specific academic word and the collection of words from all grades that overlapped in meaning with the focal word. Academic words and the networks for each domain-specific academic word were computationally determined. For each network, the time at which the first network word appeared represented the inception of the network. The network's expansion across the grades was tracked as additional words appeared. The main research questions were as follows: (a) Did network growth patterns across grades vary according to domain? and, within domain, (b) Did network patterns vary according to two focal domain-specific academic word characteristics? The two focal word characteristics were the age at which the focal word's meaning was typically known and the timing of the introduction of the focal word. Multilevel growth model analyses were conducted. The dependent variable was number of words, called "nodes," in a network at each time point across the grades. Main conclusions were the following: (a) network patterns varied across domains, with social studies networks most different from those in the other two domains; and (b) network growth pattern varied according to selected focal word characteristics, and the focal word characteristic effect varied by domain.

This study described and analyzed the vocabulary of 4 current, best-selling core reading programs and developed word lists based on these analyses. Results showed a good deal of similarity but also some significant differences among the programs. Across grades 1-6, all of them included a substantial number of tokens (approximately 380,000-660,000) and a substantial number of types (approximately 18,000-21,000). Approximately 90% of words were quite frequent, among the 4,000 most frequent English words. Most words were not repeated frequently; about 45% occurred only once or twice. Approximately 3,500 words were identified as relatively frequent and widely dispersed and about 1,000 words as relatively frequent, widely dispersed, and likely to be unknown. The lists developed include types in the programs, word families in the programs, frequent word families, general-utility word families, and challenging general-utility words families. The discussion centers on educational uses of the findings and the lists.

The present study used data from the Early Childhood Longitudinal Study--Kindergarten Class of 1998-1999 to examine whether the relationship between first-grade word-reading and reading-comprehension growth through eighth grade was different for language-minority learners (LMs) versus native English-speaking students (NEs). Among high word readers, LMs' reading comprehension was lower than NEs, but over time, they closed the gap, exhibiting similar levels at eighth grade. Among low word readers, LMs' reading comprehension was similar to NEs', but over time, a gap between LMs and NEs widened. Therefore, initially high word reading particularly advantaged LMs, and low word reading particularly disadvantaged LMs.

The Common Core raises the stature of texts to new heights, creating a hubbub. The fuss is especially messy at the early grades, where children are expected to read more complex texts than in the past. But early-grades teachers have been given little actionable guidance about text complexity. The authors recently examined early-grades texts to discover what makes them complex and now report that there is a lot that can help teachers, specifically, young children's texts are special, a handful of text characteristics can signal text-complexity level, sometimes the interplay of text characteristics modulates text-complexity level, and knowing why a text is complex can facilitate text selection.

The purpose of the study was to address possible text complexity shifts across the past six decades for a continually best-selling first-grade core reading program. The anthologies of one publisher's seven first-grade core reading programs were examined using computer-based analytics, dating from 1962 to 2013. Variables were Overall Text Complexity Level and nine text-characteristic operationalizations: number of Syllables in words and Decoding (word structure); Age of Acquisition, Abstractness, and Word Rareness (word meaning); and Intersentential Complexity, Text Density, Phrase Diversity, and Noncompressibility (discourse level). Multilevel modeling was conducted. There were three main conclusions: (1) Overall Text Complexity levels trended toward more complexity in more recent years. (2) For four of the nine text characteristics, program years were different in the text characteristic progression from the beginning to the end of the first-grade year. Initially in the fall, programs of later years exposed children to word structures (Syllables and Decoding) that were as easy or easier than in earlier years, but there was intense, and incomparable, control over gradually increasing the complexity of word structures throughout the year, ending the first-grade year with the most complex word structures of any year. Simultaneously, as compared with earlier years, there was a pronounced diminished emphasis in the later program years on selected aspects of repetition and redundancy (Text Density and Phrase Diversity) across the first-grade year. (3) Two of the six text characteristics, Age of Acquisition and Word Rareness, trended toward more complexity on average in the later program years.

ANGELS IN EARLY MEDIEVAL ENGLAND. By Richard Sowerby. Oxford Theology and Religion Monographs. Oxford: Oxford University Press, 2016. Pp. xv + 256; 12 illustrations. $95. In this elegantly written and [...]

The Common Core set a standard for all children to read increasingly complex texts throughout schooling. The purpose of the present study was to explore text characteristics specifically in relation to early-grades text complexity. Three hundred fifty primary-grades texts were selected and digitized. Twenty-two text characteristics were identified at 4 linguistic levels, and multiple computerized operationalizations were created for each of the 22 text characteristics. A researcher-devised text-complexity outcome measure was based on teacher judgment of text complexity in the 350 texts as well as on student judgment of text complexity as gauged by their responses in a maze task for a subset of the 350 texts. Analyses were conducted using a logical analytical progression typically used in machine-learning research. Random forest regression was the primary statistical modeling technique. Nine text characteristics were most important for early-grades text complexity including word structure (decoding demand and number of syllables in words), word meaning (age of acquisition, abstractness, and word rareness), and sentence and discourse-level characteristics (intersentential complexity, phrase diversity, text density/information load, and noncompressibility). Notably, interplay among text characteristics was important to explanation of text complexity, particularly for subsets of texts.

Healthcare students have expressed a need for more education on the aging adult population. Interprofessional education (IPE) is a well-known educational model intended to increase students' knowledge, skill, and abilities to use evidence-based practice for improved patient outcomes. At a Midwestern, urban-based university, we have implemented an interprofessional, student-led Geriatric Assessment Clinic in order to allow students in six health professions (including medicine, nutrition, occupational therapy, physical therapy, social work, and speech language pathology) to practically apply their skills in the aging adult population while learning to work with other healthcare professionals. This holistic clinic is free of cost to the aging adults who participate in it. The following article discusses the purpose, implementation, benefits, and limitations of such a clinic as it relates to both the patients who attend and the students who participate. [ABSTRACT FROM AUTHOR]

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