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Record W2951710402 · doi:10.37119/ojs2019.v25i1.420

Early Career Teachers’ Experiences of Communicating with Families via Technology: Educatively Dwelling in Tension

2019· article· en· W2951710402 on OpenAlexaffvenue
Nathalie Reid, Joanne Farmer, Claire Desrochers, Sue McKenzie-Robblee

Bibliographic record

Venuein education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPedagogyVariety (cybernetics)Agency (philosophy)ReciprocalPsychologySociologyMathematics educationComputer science

Abstract

fetched live from OpenAlex

A variety of online programs, apps, and digital learning management systems currently “provide teachers with a means to more easily communicate and share information with students and parents through discussion forums, social media, videoconferencing, email, grade books, and announcements” (Howell & O’Donnell, 2017, p.28). While technology is often seen as shaping positive shifts in teachers’ and schools’ abilities to communicate with families, we, the five co-researchers in the study Understanding the Interactions Between Early Career Teachers and Families, wondered how early career teachers were experiencing the use of technology to interact with families. During semi-structured interviews with each of the 20 teacher participants, we were awakened, for example, to tensions experienced by many of the teachers when expectations to communicate with families electronically conflicted with their longings for more relational and reciprocal interactions. Yet, we also came to see that the teachers were learning to dwell in these tensions in ways that opened potential for educative (Dewey, 1938) growth and movement toward the kinds of interactions with families they were imagining. This paper takes up technology as one of the resonant threads drawn from and across the teachers’ storied experiences, and inquires narratively into the kinds of generative tensions that many of the teachers were experiencing and drawing on as they imagined increased relational and reciprocal ways of interacting with families, and then moves to wonder how dwelling in these tensions might shape preservice and in-service teacher education.Keywords: Early career teachers; families; technology; interactions; agency

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

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

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 head0.039
GPT teacher head0.335
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2019
Admission routes2
Has abstractyes

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