MétaCan
Menu
Back to cohort
Record W2149758608

Evaluating Asynchronous Discussion as Social Constructivist Pedagogy in an Online Undergraduate Gerontological Social Work Course

2015· article· en· W2149758608 on OpenAlexaff
Cari Gulbrandsen, Christine A. Walsh, Amy Fulton, Anna Azulai, Hongmei Tong

Bibliographic record

VenueInternational Journal of Learning Teaching and Educational Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReflexivitySocial constructivismPedagogyConstructivism (international relations)Asynchronous communicationConstructivist teaching methodsConstruct (python library)Reflection (computer programming)PsychologyMathematics educationSociologyTeaching methodComputer scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

Our design-based research project used constructivist grounded theory methodology to determine if specific pedagogies used in an online gerontological social work course stimulated learners’ critical reflection and reflexivity. The purpose of our study was to describe the learning that occurred in response to an instructional design based on social constructivism and to identify strategies for improving the instructional design in future iterations of the course. Our analysis focused on two specific pedagogies that are grounded in social constructivism; the asynchronous discussion and the use of problem-based learning to better understand how learners construct meaning and to determine whether these pedagogies are effective means of stimulating critical reflection and reflexivity. Social work education scholars have suggested that critical reflection and reflexivity are higher-level cognitive operations that are conducive to learners’ developing capacity for anti-oppressive social work practice with older adults.    Â

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)0.027
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.362
GPT teacher head0.620
Teacher spread0.258 · 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 designObservational
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

Citations4
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Learning Teaching and Educational ResearchSame topicSocial Work Education and PracticeFrench-language works237,207