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Building Professional Practice Education Cultures in the Online Environment

2010· book-chapter· en· W2498600402 on OpenAlexaffabout
Marion Brown

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTransformative learningCraftReflection (computer programming)PedagogyWork (physics)Critical reflectionSociologyThe InternetField (mathematics)Engineering ethicsEngineeringComputer scienceWorld Wide WebGeography

Abstract

fetched live from OpenAlex

The gradual introduction of Internet-based delivery methods into higher education has broadened technology usage and led to reflection on the pedagogical implications for social work education taught online, with considerations for content, design and delivery. This chapter reviews the use of online technologies in post secondary education, the use of critical reflection as a pedagogical tool, and social work field education, to contextualize the experience of the Dalhousie University School of Social Work’s distance delivery field education course. In the experience of Dalhousie University School of Social Work, the knowledge, skills, abilities, and attitudes of its student practitioners have been enhanced through the use of online integrative seminar case analysis and critical reflection facilitated via distance delivery. This chapter develops the connections among the online environment, adult education principles, and critical reflection on field education in social work, to craft an expanded message regarding transformative social work practice.

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)0.004
metaresearch head score (Gemma)0.003
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: Other
Teacher disagreement score0.011
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0110.007
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.026
GPT teacher head0.387
Teacher spread0.362 · 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

Citations2
Published2010
Admission routes2
Has abstractyes

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