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Record W3172577139 · doi:10.5130/ijcre.v14i1.7665

Undergraduate students’ perceptions of community engagement: A snapshot of a public research university in Canada

2021· article· en· W3172577139 on OpenAlexaffabout
Sarika Haque, Taylor Krawec, Joan Chu, Tammy Wong, Mohammad Chowdhury, Tanvir Chowdhury Turin

Bibliographic record

VenueGateways International Journal of Community Research and Engagement · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedical educationPerceptionIncentivePopulationPsychologyCommunity engagementStudent engagementPublic universitySocial mediaMedicinePublic relationsPolitical science

Abstract

fetched live from OpenAlex

Students who participate in regular community engagement (CE) often experience benefits in different areas of their lives. Many academic institutions have implemented action plans to increase CE within the student population. At the University of Calgary, Canada, this is done primarily through its broader Eyes High strategy. As there remains a gap in the literature about students' perceptions of CE and their awareness of university CE strategies, this study aims to identify undergraduate students’ awareness of the Eyes High strategy, attitudes towards and levels of engagement, and challenges and potential methods to increase CE participation. Data was collected through a voluntary online survey (n=528). Participants were recruited through posters, social media, online faculty platforms and by faculty members. Survey results indicated students lacked knowledge regarding the Eyes High strategy. It was noted that students’ knowledge, attitudes and practices of CE increased as they spent more time at the university. The top perceived challenges to CE were lack of time, accessible information, support and incentives. To increase accessibility and student participation, we suggest introducing the Eyes High Strategy and CE activities early to the undergraduate population through workshops, credit-based courses and/or professional development requirements. Our data suggests that students are not well informed about the Eyes High strategy. There is thus a need for the university to build a campus-wide, student-informed initiative to proactively engage students. This research will serve as a gateway to further explore communicative methods that might better convey university priorities to students.

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)0.055
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0550.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0000.007
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 head0.377
GPT teacher head0.458
Teacher spread0.081 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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