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Record W2126383630 · doi:10.3991/ijet.v7i4.2301

Virtual Portfolio: A Strategy for Learning Assessment in a Graduated Virtual Program Results of a Pilot Study

2012· article· en· W2126383630 on OpenAlex
Carmen Marín, Shirley Montero Rodríguez

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Emerging Technologies in Learning (iJET) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
FundersUniversidad de Costa Rica
KeywordsSession (web analytics)PortfolioDimension (graph theory)Quarter (Canadian coin)Pilot programComputer scienceVirtual learning environmentElectronic portfolioPsychologyHuman–computer interactionMultimediaMathematics educationApplied psychologyMedical educationWorld Wide Web

Abstract

fetched live from OpenAlex

Learning evaluation in a graduated master virtual program was assessed using virtual portfolio strategy as a tool to assess learning. A pilot study determined dimension and direction of interactions between students and professor during the first quarter of the program. Results show the most frequent dimension was social (55,9%), followed by procedimental (41,4%). In direction student /professor (32,7%) was the most, followed by professor /student. The predominance of social interactions might be explained because this research was done at the very beginning of the program. We expect the analysis of subsequent recorded chat session, forums discussions and people´s comments will show progressively switch toward cognitive interactions.

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)0.006
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.079
GPT teacher head0.472
Teacher spread0.393 · 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