MétaCan
Menu
Back to cohort
Record W7053216531

A special digital environment to optimize interprofessional collaboration and promote learner engagement

2022· other· en· W7053216531 on OpenAlexaboutno aff

Bibliographic record

VenueR-libre (Université Téluq) · 2022
Typeother
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)Context (archaeology)Flexibility (engineering)Digital healthDigital literacyHealth careMental healthLiteracy
DOInot available

Abstract

fetched live from OpenAlex

As part of a project funded by the Social Sciences and Humanities Research Council (SSHRC), we would like to implement a module for use in conjunction with Moodle, with the goal of optimizing interprofessional collaboration and promoting learner engagement. \n \nThis project is based on the fact that clear adaptation and flexibility needs in education have been identified. Health sciences education is one example, particularly in the context of complex impairments (such as chronic pain, long COVID or mental health issues), where these needs are at the core of clinical and educational challenges. Such a context calls for interprofessional practice and requires taking into account different professional cultures and practice settings, in addition to the patient’s life circumstances, literacy level and culture. Learners, whether they are patients or informal caregivers, and teachers must develop adaptation skills and equip themselves to consider diverse contexts and cultures. Patients and their loved ones will go through a learning path (from disease and self-management of this disease and including any care that may be considered), at the same time as or before starting on their care pathway, to enable them to engage as full participants in their care. It is our aim to give them the necessary tools to do so. The use of digital learning environments (DLEs), which eliminates the constraints of time and geography, provides opportunities to demystify all that is involved in this process, and opens up a wealth of learning opportunities. These DLEs thus provide special access to a diverse array of contexts and cultures. But how can their full pedagogical potential be harnessed? \nWe contend that learner engagement and interprofessional collaboration are necessary. In order to foster these, we propose first to identify knowledge about cultures and contexts, as this is often implied and can lead to misunderstandings. Next we propose to organize it in such a way that DLE users will be equipped to mobilize this knowledge. For this purpose, we will develop and evaluate computerized tools for leveraging this knowledge, engaging learners and optimizing interprofessional collaboration practices. These tools will be brought together in a module used in conjunction with the Moodle environment: the SPÉCIAL module, which stands for Scénarisation PÉdagogique Collaborative Intégrant des Alternatives et des Liens [Scripting that is PEdagogical [and] Collaborative Integrating Alternatives and Links]. The links developed are those between 1) learning data and knowledge that has been accumulated and updated, in particular through artificial intelligence (AI) techniques, 2) pedagogical tools (DLEs, portfolios, etc.), and 3) the environments where the users are found. \n \nProject team: \nPrincipal investigator (P.I.): Isabelle Savard \n \nCo-investigators: \nPatrick Plante – TÉLUQ University \nGustavo Angulo - TÉLUQ University \nDaniel Lemire - TÉLUQ University \nJean-Sébastien Roy - Laval University \nKarine Latulippe – McGill University \nLuc Côté - Laval University

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.021
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.005
Open science0.0010.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.008

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 head0.006
GPT teacher head0.174
Teacher spread0.169 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueR-libre (Université Téluq)Same topicLaser Design and ApplicationsFrench-language works237,207