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Record W2278417301 · doi:10.12735/ier.v3i2p01

In their Own Words: Using First-Year Teacher Blogs to Prepare Preservice Educators

2015· article· en· W2278417301 on OpenAlexvenueno aff
Laura Reynolds

Bibliographic record

VenueInternational Education Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationTeacher preparationPsychologyPedagogyTeacher educationComputer science

Abstract

fetched live from OpenAlex

Teacher-preparation programs strive to bridge the gap between theory and practice, and to prepare preservice teachers for the challenges and realities of the classroom. As budgets tighten and the alternative and online preparation of teachers becomes more common, field experiences in classrooms are increasingly limited. Creatively bridging the gap between theory and practice using teacher-created blogs provides preservice teachers the opportunity to gain insight into the challenges and life of teachers as well as the chance to reflect and make connections between coursework and their future profession. Although preservice teachers are often required to create blogs, little attention has been given the use of teacher blogs as a part of course readings and discussions, or as a supplement or replacement for field experiences. The purpose of the present study was to first explore the impact first-year teacher blogs had on pre-service teacher perceptions of the classroom, and then to determine if reading, analyzing and reflecting on the blogs impact how students perceive the applicability and utility of course content. Participants were 58 undergraduate preservice teachers seeking initial certification and enrolled in an educational psychology course at the regional campus of a public midwestern university in the United States. Results indicated that the teacher-created blogs impacted preservice teacher reflection and refinement of the realities of the classroom, and that reading teacher accounts via blogs facilitated realistic expectations of the challenges facing novice teachers. The finding may prove useful in that utilizing blogs may be helpful in situations when courses are on-line, or do not include the recommended opportunity for practical classroom interaction (Cheng & Tang, 2008).

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)0.005
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.219
GPT teacher head0.575
Teacher spread0.355 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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