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Record W4406282375 · doi:10.5296/jse.v15i1.22472

A Self-Evaluation Framework to Enrich Online Forum Work by Students in Graduate Contexts

2025· article· en· W4406282375 on OpenAlex
Nancy Maynes, Blaine E. Hatt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Studies in Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsNipissing University
Fundersnot available
KeywordsWork (physics)Graduate studentsSociologyGraduate researchMathematics educationPsychologyComputer sciencePedagogyMedical educationEngineering ethicsEngineeringLibrary scienceMechanical engineeringMedicine

Abstract

fetched live from OpenAlex

This paper presents a model for self-evaluation of online learning contributions used with graduate students. The model is outlined, followed by a detailed assignment copy that shows students how to use the model and attendant criteria for each component of the model to plan, write, and assess their own online contributions as the sub-topics within a graduate course evolve. Finally, an example of one student’s self-analysis, developed using this framework is provided to show the depth and breadth of posts that can be garnered by applying this framework. The example is provided in three parts that correspond to the three elements of the model, in abbreviated form (i.e., where the student provided several examples, one example was chosen as a sample).

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.054
GPT teacher head0.492
Teacher spread0.438 · 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