MétaCan
Menu
Back to cohort
Record W2380899543 · doi:10.33524/cjar.v17i1.246

Dana, N. F. (2013). Digging deeper into action research: A teacher inquirer’s field guide. Thousand Oaks, CA: Corwin.

2016· article· en· W2380899543 on OpenAlexaffvenue
Marcela Herrera Farfán

Bibliographic record

VenueThe Canadian Journal of Action Research · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTerminologyDiggingAction (physics)Action researchField (mathematics)PedagogyMathematics educationCurriculumPsychologySociologyHistoryPhilosophyMathematics

Abstract

fetched live from OpenAlex

This book is one in a series conducted by Nancy Dana, professor in the School of Teaching and Learning at the University of Florida. Specifically, this book comes as a practical complement to her previous book ‘The reflective educator’s guide to classroom research: Learning to teach and teaching to learn through practitioner inquiry’ (Dana & Yendol-Hoppey, 2008) which is a comprehensive introduction. The title of the book briefly describes what the book is about. For example, the concept digging deeper and ‘field guide’ suggest a topic related to nature. Actually, according to Merriam Webster’s ‘field guide’ mainly refers to a manual to explore nature (Merriam-webster.com). The title also talks about ‘action research’ and ‘teacher inquirer’. Thus, the title of this book as a whole refers to a manual that will guide teacher researchers as they explore action research. This is an easy-to-read, instructive book which is mainly intended for school teachers. However, the advice for action research provided here can also be used for post-secondary level education. Since the main goal of this book is to provide guidance and useful tips for either novice teacher researchers or more experienced ones, this book does not contain a great deal of research field related terminology. Dana’s book is suitable for both novice and experienced researchers.

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 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)0.016
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.518
GPT teacher head0.545
Teacher spread0.027 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations8
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe Canadian Journal of Action ResearchSame topicTeacher Education and Leadership StudiesFrench-language works237,207