This section is a brief review of the theory underlying WordSift. The challenges and complexities of reading comprehension in adolescence have received increasing recognition in recent years. Vocabulary is a central arena in which the discrete skills of reading (decoding, sight-word recognition, reading fluency and accuracy) come together with top-down cognitive processes involved in comprehension. As researchers such as Catherine Snow have noted, a deficit in any of these areas may prevent an adolescent reader from comprehending grade-level text, but deficits in vocabulary knowledge and the semantic knowledge that it represents may be the most widely shared problem among struggling adolescent readers (Snow et al, 2007; Kamil, 2003).

The problem of vocabulary is especially important for English Language Learners (August and Shanahan, 2006). Vocabulary continues to be a challenge even beyond the point when the students have developed sufficient English proficiency to the point where they are “reclassified” as fluent English speakers (Butler and Hakuta, 2006). High-achieving English Learners (and former English Learners) continue to have great needs in developing the kinds of high academic vocabulary that are required for competitive performance on college entrance tests such as the SAT, limiting access to selective higher education. Thus, educators need to appropriately address vocabulary development in adolescence across the full range of student experiences, abilities and educational aspirations (Educational Testing Service, 2008).

The power of vocabulary in predicting cognitive processing in phonological, orthographic, and semantic processing as well as reading rates and other tasks is well-documented (Nation & Snowling, 2004; Yang & Perfetti, 2006). Walter Kintsch’s work on situation modeling from text also demonstrates the importance of higher order reading comprehension abilities and its relationship to vocabulary (Kintsch, 2086; Perfetti, Landi & Oakhill, 2005). Catherine Snow and her colleagues have also demonstrated increasing correlations between vocabulary scores and reading comprehension scores as student move from primary to secondary grades (Snow, Porche, Tabors & Harris, 2007).

The challenges of vocabulary are now fairly well mapped. Of special interest are academic words (Coxhead, 2000) that cut across subject matter areas (e.g., affirm, interpret, deny, evidence, conclusion, theory, factor, process) in contrast to subject-specific words such as mitosis, plate tectonics or prepositional phrase. Academic words are of special interest because they are unlikely to be identified in glossaries in many subject area textbooks, yet they are crucial for understanding the meaning of the text. Word Generation, an instructional program developed by Snow and her colleagues, focuses on explicit teaching of these academic words, and this program was recently reported to have an especially beneficial effect for English Language Learners (SERP Institute, 2009).

Other vocabulary categories of interest are subject-specific lists (e.g., Marzano & Pickering, 2005), Biemiller’s list of “Words Worth Teaching” based on the work of Isabel Becks and her colleagues on the Living Word Vocabulary and his own empirical work identifying key words (Beck, McKeown & Kucan, 2002; Biemiller, 2005, 2006). With increased capacity for automated word frequency counts in an ever-increasing database of texts, there is now increased capacity in the field to target specific words for specific students, based on their backgrounds and the instructional subject area. Such lists enable explicit instruction of specific vocabulary in the context of students read content area texts. By the middle school grades, students are expected to read and understand expository texts with demanding vocabulary (Gardner, 2004). There is a Matthew effect, with the rich getting richer with respect to vocabulary and, ultimately, reading comprehension (Nagy & Anderson, 1984; Nagy & Herman, 1987; McKeown, 1985; Stanovich, 1986; Swanborn & de Glopper, 2002). Fortunately, there is evidence that vocabulary instruction can have an important and lasting impact on student word learning (Beck, Perfetti & McKeown, 1982; Carlo et al, 2004).

While this characterization is true for all students, it is especially true for English Language Learners. WordSift thus attempts to address one of the greatest challenges facing educators of English Language Learners: how to grow and enrich the academic vocabulary of their students across the grade levels, and especially through academic content instruction. Educators specializing in English Language Learners are faced with a substantial group of students who are “stuck” at the intermediate level of English language proficiency, leading to labels such as long-term ELLs or “lifers”.

From a pedagogical viewpoint, an important key to addressing this problem lies in the realization that English language development for these students, while the primary responsibility of the ESL/ELD teacher or specialist especially for ELL students in the beginning levels of English language development, needs to be an overarching objective for all teachers of English Language Learners – the so-called “mainstream” teacher in the typical elementary grade, or the subject area teachers in language arts, math, science, social studies, and electives in the secondary grades. Language development needs to occur in context, and content area learning provides the best context for it to occur.

But can we expect mainstream and content area teachers to take on this shared responsibility? Teacher practice is the product of a complex set of situations, beginning in teacher preparation programs (in which considerable separation of responsibilities for “mainstream” and “ELL students” take root) and the culture of the school created by its demographic composition, district expectations and the site leadership and professional support. A key challenge is to help content teachers define a new identity for themselves -- as a language teacher of their discipline. We are hopeful that WordSift can be a helpful tool in that direction.


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