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Record W2891832582 · doi:10.5539/res.v10n4p74

Digital Skills for Elderly People: A Learning Experiment in Four European Countries

2018· article· en· W2891832582 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of European Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsTouchscreenErasmus+PsychologySmart phoneExploratory researchDigital learningMotor skillPhoneApplied psychologyComputer scienceMultimediaHuman–computer interactionPedagogySociologyDevelopmental psychology

Abstract

fetched live from OpenAlex

The problem of learning digital skills among the elderly addressed in this paper is focused on a methodology that tries to overcome the barriers in adoption of touchscreen digital technology faced by older adults, by using a game-based learning approach. The paper provides an overview of some early results and findings from an exploratory study among the elderly from four European countries based on the use of touchscreen tablets for playing games as a pre-course activity for learning how to use a smart phone. The learning was carried out with pre-selected games designed to enhance the motor skills of the players and improve the coordination between cognitive and motor skills capacity. The results presented in the paper were collected within the partners of the project GIRDA – Gameplay foR Inspiring Digital Adoption from the European ERASMUS+ programme. The paper describes the research setting, the experiments and the results accompanied by discussion and the conclusion.

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)0.003
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 score0.931
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.031
GPT teacher head0.346
Teacher spread0.315 · 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