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Record W2121337498

Collaborative Online Teaching: A Model for Gerontological Social Work Education

2015· article· en· W2121337498 on OpenAlexaffvenue
Amy Fulton, Christine A. Walsh, Anna Azulai, Cari Gulbrandsen, Hongmei Tong

Bibliographic record

VenueInternational journal of e-learning & distance education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedical educationWork (physics)PsychologyReflection (computer programming)ReflexivityGraduate studentsHigher educationUndergraduate educationPedagogySociologyComputer scienceMedicineEngineering
DOInot available

Abstract

fetched live from OpenAlex

Social work students and faculty are increasingly embracing online education and team teaching. Yet models to support these activities have not been adequately developed. This paper describes how a team of instructors (a senior faculty member, three doctoral students, and a post-doctoral fellow) developed, delivered and evaluated an undergraduate gerontological social work course using a collaborative online teaching and learning model. Our findings suggest that the course model served to: (a) facilitate undergraduate students’ use of higher order learning (reflection, reflexivity and application of knowledge to practice) and reduce ageism; (b) increase instructional skill among doctoral students and (c) provide the opportunity for gerontology training to undergraduate social work students across a large geographical area.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.448
Teacher spread0.383 · 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 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

Citations6
Published2015
Admission routes2
Has abstractyes

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