Bibliographic record
Abstract
Assessment for Reading Instruction, 3rd edition by Michael C. McKenna & Katherine A. Dougherty Stahl New York, NY/USA: The Guilford Press, 2015, 324 pages ISBN: 978-1-4625-2104-3 (paperback) As increasing emphasis is placed on the importance of literacy skills, many classroom teachers feel overwhelmed or left behind. Classrooms that exceed student capacity, readers who find themselves well below grade level standards, and government mandates that tie student success to teacher success have placed a tremendous amount of pressure on classroom teachers. With a wide variety of readers and reading levels in one classroom, teachers are often spread too thin and find themselves in need of practical information and tools that will help them advance their students' reading levels. Michael C. McKenna and Katherine A. Dougherty Stahl have created a practical and comprehensive text that covers reading assessment and that gives teachers a wealth of useful knowledge that can be applied directly to their classroom experience. It is clear, concise, and offers real-world examples that will prove invaluable to teachers. The third edition of Assessment for Reading Instruction obviously builds upon the previous two, but within the last six years, several topics have become more prominent in the field of literacy education. Among the most important is the use of response to intervention (RTI) as it relates to literacy education. McKenna and Stahl have written a companion book entitled Reading Assessment in an RTI Framework that describes how key assessments fit into the response to intervention (RTI) model (McKenna & Stahl, 2013). This text is meant to work hand in hand with Assessment for Reading Instruction. The ever-evolving national focus on Common Core State Standards (CCSS) in the United States is another reason the authors included vital information to their Assessment for Reading Instruction text. With many regions adopting the CCSS or a similar version of it, the realization that vast numbers of students are below grade level readers has flustered educators. There is no one chapter dedicated to Common Core within this text. However, there are CCSS connections within many of the tips, skill sets, and assessments included. Finally, this text includes a chapter that focuses exclusively on vocabulary, its importance, how it can be assessed, and the issues that cause it to be problematic. The text is divided into eleven chapters. It begins with a basic introduction of reading assessment in which multiple reading models are detailed. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.080 | 0.069 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".