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Record W2465002647

Assessment for Reading Instruction, 3rd edition

2016· article· en· W2465002647 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Practices and Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)LiteracyMathematics educationVariety (cybernetics)Intervention (counseling)PsychologyPedagogyComputer sciencePolitical scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

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. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.084
GPT teacher head0.386
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it