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“Tell Me About Yourself” - Using eportfolio as a Tool to Integrate Learning and Position Students for Employment, a Case from the Queen's University Master of Public Health Program

2018· article· en· W2912135023 on OpenAlexaffvenueabout
Brenda Melles, Andrew Leger, Leigha Covell

Bibliographic record

VenueThe Canadian Journal for the Scholarship of Teaching and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedical educationPsychologyFocus groupProfessional developmentPedagogySociologyMedicine

Abstract

fetched live from OpenAlex

This paper explores the use of eportfolio to develop, demonstrate and promote core competencies in a Professional Master of Public Health (MPH) program at Queen’s University in Kingston, Ontario, Canada. Piloted in 2016, the MPH Competency eportfolio is described as a purposeful collection of electronic evidence that demonstrates learning and achievement in public health over time. The eportfolio was framed both as a reflective learning process and a showcase product to demonstrate skills and competencies to potential employers. The eportfolio was implemented using an available tool on Queen’s University’s Learning Management System. To understand the impact of the eportfolio, students responded to a questionnaire and participated in a focus group. Themes identified from the student responses were: eportfolio helped students integrate and reflect on their learning and experience. eportfolio helped students to position their professional identity and experience for employers. Students were more convinced of the value of eportfolio as a reflection tool than as a showcase product for a professional setting. Students were not convinced that employers will actually look at an eportfolio. The technology used in this study was limiting for students. Students were interested in using other established and more user-friendly platforms. The findings of this study will benefit any program or course of study seeking a means to help students integrate their learning and demonstrate their accomplishments, skills, and competencies. This paper addresses how to integrate eportfolio at the program level and also provides insight into the student experience of their use. Cet article explore l’emploi d’un eportfolio pour développer, démontrer et promouvoir les compétences de base offertes dans un programme de maîtrise professionnelle en santé publique à l’Université Queen’s, à Kingston, en Ontario, au Canada. Le programme pilote, un eportfolio des compétences pour la maîtrise en santé publique, a été lancé en 2016. On le décrit comme un recueil ciblé de preuves électroniques qui démontrent l’apprentissage et les réussites en santé publique au fil des ans. On dit également que le eportfolio est à la fois un processus d’apprentissage par la réflexion ainsi qu’un produit phare qui permet de démontrer les aptitudes et les compétences aux employeurs potentiels. Le eportfolio a été mis en oeuvre grâce aux outils disponibles dans le système de gestion de l’apprentissage de l’Université Queen’s. Afin de comprendre l’impact du eportfolio, les étudiants ont répondu à un questionnaire et ont participé à un groupe de discussion. Les thèmes identifiés à partir des réponses des étudiants sont les suivants : Le eportfolio a aidé les étudiants à intégrer leur apprentissage et leurs expériences et à y réfléchir. Le eportfolio a aidé les étudiants à positionner leur identité et leurs expériences professionnelles à l’intention des employeurs. Les étudiants étaient davantage convaincus de la valeur du eportfolio en tant qu’outil de réflexion plutôt qu’en tant que produit phare pour un milieu professionnel. Les étudiants n’étaient pas convaincus que les employeurs allaient réellement examiner un eportfolio. La technologie employée dans cette étude était limitative pour les étudiants. Les étudiants étaient intéressés à utiliser d’autres plate-formes établies et plus faciles à employer. Les résultats de cette étude seront utiles pour n’importe quel programme ou n’importe quel cours qui vise à trouver un moyen d’aider les étudiants à intégrer leur apprentissage et à démontrer leurs réussites, leurs aptitudes et leurs compétences. Cet article explique comment intégrer un eportfolio dans un programme et fournit également des renseignements sur l’expérience des étudiants qui l’ont utilisé.

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)0.016
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.000
Scholarly communication0.0010.001
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 head0.110
GPT teacher head0.441
Teacher spread0.331 · 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.

Study designQualitative
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

Citations5
Published2018
Admission routes3
Has abstractyes

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