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Record W1940981162 · doi:10.19030/cier.v8i3.9345

Engaging Post-Secondary Students And Older Adults In An Intergenerational Digital Storytelling Course

2015· article· en· W1940981162 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

VenueContemporary Issues in Education Research (CIER) · 2015
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsStorytellingDigital storytellingPsychologyTheme (computing)Medical educationPedagogyNarrativeMedicineComputer science

Abstract

fetched live from OpenAlex

A five day Digital Storytelling course was offered to Social Work students, integrating a three day workshop with older adult storytellers who shared storied related to the theme stories of home. A course evaluation was conducted exploring the Digital Storytelling experience and learning in an intergenerational setting. Findings from surveys distributed at the end of the course to students and storytellers revealed that students’ knowledge of and interest in Digital Storytelling and its application was enhanced. The intergenerational component was positive for students and older adults. Students identified the intergenerational component as a highlight of the course which improved their awareness of older adult issues and knowledge of working with aging populations. Older adult participants enjoyed working with the students which increased their understanding of younger generations. This innovative course enhanced students’ learning experiences, meriting consideration for the incorporation of intergenerational learning opportunities and Digital Storytelling into future social service and aging related courses to better prepare students for gerontological 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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.154
GPT teacher head0.514
Teacher spread0.360 · 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