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Record W1726619814 · doi:10.22329/celt.v1i0.3185

16. “Learning by Doing” in a Graduate Course in Human Development and Family Studies: Service Learning Utilizing an Evaluation Project

2008· article· en· W1726619814 on OpenAlexvenueno aff
Karen Kopera-Frye, Jeanne M. Hilton

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsnot available
Fundersnot available
KeywordsService-learningScholarshipService (business)Learning sciencesPsychologyPedagogyKnowledge managementEngineering ethicsExperiential learningSociologyComputer scienceEngineeringPolitical scienceBusiness

Abstract

fetched live from OpenAlex

The purpose of this paper is to share our experiences involving a creative approach to service learning that was implemented in a Human Development and Family Studies graduate course. In our departmental pursuit of evolving scholarship and promoting scholarly teaching and learning (Kopera-Frye, Hilton, & Cavote, 2003), this course represents an example of how one can promote higher-level learning among our future professionals. This service learning approach utilized in this particular course focuses on needs assessment and program evaluation, a direction not usually found in typical service learning projects that involve a social volunteerism approach. By discussing the theoretical basis for the project, course format, and providing some qualitative/evaluative data, we will contribute to the knowledge base on innovative ways to promote scholarly learning. Challenges and issues that need to be anticipated before designing this type of service learning experience will be highlighted.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.004
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 head0.154
GPT teacher head0.399
Teacher spread0.245 · 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
Published2008
Admission routes1
Has abstractyes

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