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Record W2268117188 · doi:10.18260/1-2--19040

A Community Partner's Role During a First-Year Service Learning Project

2020· article· en· W2268117188 on OpenAlexaff
Libby Osgood, Clifton Johnston, Andrew Trivett

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsUniversity of Prince Edward IslandDalhousie University
FundersAmerican Society for Engineering Education
KeywordsService-learningService (business)Work (physics)Process (computing)Local communityQuality (philosophy)The InternetCommunity servicePsychologyMedical educationComputer sciencePublic relationsEngineeringMarketingBusinessPedagogyWorld Wide WebPolitical scienceMedicine

Abstract

fetched live from OpenAlex

There are 3 primary roles in a service learning (SL) project: student, teacher, and community organization representative (COR).It has been established that students enjoy and benefit from SL experiences.[1][2][3][4][5] Teachers benefit as well, in their ability to meet educational objectives. 1 For the community organizations, the advantage appears to be obvious; their problem is resolved.However, the benefits for the COR must be more fully explored.This paper will examine the advantages as well as the inconveniences experienced by one of the authors while participating in a SL project.In the 2011 -2012 academic year, 45 first-year engineering students at the University of Prince Edward Island in Canada were introduced to a need from a remote village in Kenya.Though it would have been preferable to work directly with the villagers, poor internet quality and the extreme distance made this impossible.As a result, people from the local community, who regularly travelled to the village, identified the need and acted as the COR during the 15-week long project.In groups of 3, the students designed charcoal presses to convert agricultural waste into charcoal briquettes more efficiently than the current process.The COR was involved in the design process during the problem introduction, a hands-on demonstration of the process, question and answer sessions, reviews, and the design exposition.Also, while in the Kenyan village, the COR facilitated an exchange of information and performed an experiment designed by the students.The time demand, though great, gave the students a better understanding of the needs of the villagers.This paper will consider a qualitative assessment of the COR's involvements.This will be achieved through an examination of activities between the students and the COR, including a firsthand account of the events that took place in the remote village.Finally, the accomplishments and deficiencies that the COR experienced will be analyzed, and recommendations will be made to ensure that all participants' expectations are achievable.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.001
Scholarly communication0.0030.002
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.003

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 head0.078
GPT teacher head0.314
Teacher spread0.236 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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