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Record W178161130

Participation in the Classroom: Classification and Assessment Techniques

2014· article· en· W178161130 on OpenAlexaff
Jessey Wright

Bibliographic record

VenueScholarship@Western (Western University) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsWestern University
Fundersnot available
KeywordsVariety (cybernetics)Class (philosophy)Critical thinkingPsychologyStudent engagementMathematics educationPedagogyMedical educationComputer scienceMedicine
DOInot available

Abstract

fetched live from OpenAlex

Class participation and active engagement are both critical components for student success in a variety of classroom settings. This is especially true in philosophy classrooms where students are expected to develop and refine their ability to critically and productively engage with the literature being studied while also participating in conversations with their peers. Including participation expectations in classes is a common strategy, used by teachers, for developing and honing important skills in students. In requiring participation in their respective courses, teachers seek to refine and cultivate critical thinking and communication skills in their students. This workshop begins with an overview of research that, on the one hand, examines different strategies for effectively encouraging student participation and, on the other, also provides recommendations for broadening our definition of student participation in the classroom. Following the literature review, I will provide an active learning, self-assessment tool for evaluating course participation (this tool can be adapted to larger classroom settings and contexts, as well) that, I suggest, will be of benefit to teachers and students alike.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.166
GPT teacher head0.425
Teacher spread0.259 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2014
Admission routes1
Has abstractyes

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