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Record W2621190005

Creating Critical Classrooms: Reading and Writing with an Edge (2Nd Ed.)

2015· article· en· W2621190005 on OpenAlexaboutno aff
Diane E. DeFord, Melissa Wells, Catherine A. Sanderson, Jennipher Frazier

Bibliographic record

VenueLanguage Arts · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPedagogyCurriculumCritical literacySociologyContext (archaeology)Reading (process)Mathematics educationPsychologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Technology & Critical Literacy in Early Childhood by Vivian Maria Vasquez and Carol Branigan Felderman, New York, NY: Routledge, 2012, 128 pp., ISBN 978-0- 415- 53950- 0In scope, Technology and Critical Literacy in Early Childhood highlights the work of preservice and inservice teachers, as well as teacher leaders in settings such as learning cooperatives, public schools, and private schools in Washington DC, North Carolina, Georgia, Virginia, and Ontario, Canada. Written for preservice and classroom teachers and teacher educators, this text explores the integration of literacy, social studies, and science with new forms of communication in early childhood settings (ages 3-8). It provides clear examples of how professional standards and sound classroom practices work together to enrich the lives of young children. This well-written and accessible text also offers ways to enact social justice themes that position children as highly engaged, critical literacy users. The authors embed Reflection Points, invitations to Try This, and resource boxes to help readers move beyond the text into their personal classroom spaces.The first chapter, Setting a Context for Exploring Critical Literacies Using Technology, and last chapter, Desires, Identities, and New Communication Technologies, set up the theoretical underpinnings of critical literacies and how new communications impact children's literacy development and identities. These chapters provide clear rationales and guidelines so teachers can implement highly effective curricula. Each chapter provides examples of lessons, teacher and student interactions, and results obtained when children are immersed in such classrooms.Chapter 2, Teaching and Learning with Voice Thread, and Chapter 3, Yes We Can!: Using Technology as a Tool for Social Action, illustrate the use of VoiceThread in a variety of classrooms. In a first-grade charter school classroom, children discussed and wrote about social justice issues. Small groups researched issues people face in different countries. One group met Lubo, an African man who was rescued as a child from a refugee camp and relocated to North Carolina. As an adult, he dreamed of helping other children like himself. This group used VoiceThread to talk with refugees in Africa and inform others about their project. These projects helped them study life in different countries and be advocates to change unfair issues children can face. In other Pre-K- first- grade classrooms, children explored their classrooms and communities using technology in social studies and science. One Pre-K class studied water and pollution and helped others save on energy; another class learned about endangered animals and the rainforest; yet another first-grade class studied the weather and produced weather forecasts for their school. Across these contexts, students used information gained to develop technology and communication skills, thus bettering their own lives and the lives of others in their schools and communities.Chapter 4, Our Families Don't Understand English! and Chapter 5, What about Antarctica? describe second-grade podcasts that address issues of diversity, difference, language, and power. Most of these students from seven different countries participated in free or reduced-free lunch programs, so these issues were of personal import. A touching story of Subrina, a Latina student from Guatemala, illustrates how podcasts foster growth in oral and written communication. …

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.004
Scholarly communication0.0120.010
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0220.015

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 head0.029
GPT teacher head0.329
Teacher spread0.300 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations27
Published2015
Admission routes1
Has abstractyes

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