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Record W2346688782 · doi:10.1921/gpwk.v25i2.890

Challenges and opportunities for applying groupwork principles to enhance online learning in social work

2016· article· en· W2346688782 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGroupwork · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsWork (physics)Group workOnline learningFoundation (evidence)Online participationSocial mediaOrder (exchange)Engineering ethicsPsychologyPedagogySociologyComputer scienceEngineeringThe InternetMultimediaPolitical scienceWorld Wide Web

Abstract

fetched live from OpenAlex

The recent increase in the number of social work courses being offered in online formats raises challenges and opportunities for social work educators. Simultaneously, the literature suggests that group work principles can serve as an important foundation for effective online education. This article examines the obstacles and opportunities for using group work principles to advance effective learning in online education. Three examples of fully online social work classes - a BSW group work course, an MSW group course and an MSW field work seminar - are discussed in order to identify and assess some of these obstacles and opportunities. Recommendations for best practices in online education are identified. The potential role of group work educators as leaders in facilitating effective online learning is also explored.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.213
GPT teacher head0.405
Teacher spread0.192 · 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