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Record W3028223264 · doi:10.1111/medu.14250

Faculty development in the COVID‐19 pandemic: So close ‐ yet so far

2020· article· en· W3028223264 on OpenAlexaff
Heather Buckley

Bibliographic record

VenueMedical Education · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsStornoway Diamond (Canada)
Fundersnot available
KeywordsCitationLibrary scienceCoronavirus disease 2019 (COVID-19)PandemicHistorySociologyMedicineComputer science

Abstract

fetched live from OpenAlex

Conceptual advances in faculty development are broadening to emphasise the importance of relationships and social networks to faculty learning.1 In-person events traditionally provide a venue for these relationships to develop and be sustained. The onset of the coronavirus disease 2019 (COVID-19) pandemic forced the rapid acceptance of online platforms as the only approach for interpersonal connection within the department. Within these virtual-only conditions, a faculty development intervention was quickly created for a cohort of dispersed faculty staff that could harness the power of relationships and social networks for support of faculty members and learning about the programme's new format (online) and additional content (student stress). A provincial virtual faculty development session was developed to bring four regionally dispersed faculty staff groups together to learn with and from each other. Social network theory prioritises relationships and interactions; this lens was used to design and plan the intervention. Although the four regions fit the description of a socio-centric (closed) network, strong reciprocal connections between regional groups could not be assumed as these groups had not met together for several years. Communications were organised centrally by the author (HB) as provincial lead, but distributed through four local regional sites. Better uptake was anticipated if the regional leads and site administrators reached out to faculty members; pre-existing peer relationships can exert influence on the decision to attend.1 Other sources of expertise (faculty development, information technology [IT], student affairs, etc.) were invited to bridge any knowledge gaps around virtual learning and managing student stress. The session was organised to maximise time for informal questions and answers. Formal presentations were avoided to encourage spontaneous informal discussion. Continuity of connection was offered afterwards through email, a written overview of conversation highlights and a follow-up debrief session; IT services also offered additional drop-in clinics. Initially, creating a virtual faculty development session seemed like a fairly straightforward solution, but it was surprisingly a lot of work! Setting realistic expectations and event participants was critical; many educational leaders and teachers within medicals schools have other responsibilities and are overstretched during the COVID-19 pandemic. Facilitating discussion virtually required extra attention to ‘read the Zoom™ (Zoom Video Communications Inc., San Jose, CA, USA).’ Arranging for a co-facilitator to help keep track of comments and questions was helpful. Many participants did not seem to be familiar with each other, although there was reference to some pockets of strong ties within regions. When there was a reference to a past shared experience amongst participants, it seemed to encourage participation in the virtual session. There also appeared to be less of a ‘group think’ mentality, which sometimes is observed when faculty development participants in this context are physically co-located. Participants seemed quite open to share varied and even competing opinions, which then required nuanced facilitation. As well, it was also harder to have informal or ‘sidebar’ conversations, which can also be influential for faculty learning.1 Perhaps smaller breakout rooms may help facilitate organic conversations. Faculty members also seemed to value other forms of follow-up communication (email, written summaries and debriefs) to sustain conversations. Perhaps most satisfyingly, he or she indicated that connecting with each other was highly valued. Connection allowed them to develop an informed and shared understanding of the changes to his or her role, as well as the reassurance and confidence to embrace new challenges, such as teaching virtually and attending to student well-being. In future, planning additional evaluation that includes measuring social network structural and qualitative changes, although not feasible at the onset of the COVID-19 pandemic, would be helpful to further assess impact and align with current evaluation trends.

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)0.010
metaresearch head score (Gemma)0.026
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.022
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0220.016
Scholarly communication0.0140.016
Open science0.0020.025
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0200.003

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 head0.070
GPT teacher head0.354
Teacher spread0.284 · 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
GenreCommentary

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".

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Citations38
Published2020
Admission routes1
Has abstractyes

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