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Record W2152236904 · doi:10.1152/advan.00001.2006

Promoting self-directed learning using a menu of assessment options: the investment model

2006· article· en· W2152236904 on OpenAlex
P. K. Rangachari

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

VenueAJP Advances in Physiology Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInvestment (military)AutodidacticismPsychologyMathematics educationComputer scienceMedical educationMedicinePolitical science

Abstract

fetched live from OpenAlex

Undergraduate science students took an Inquiry course in their second (sophomore) year. The course was designed to explore the social life of scientific knowledge. They were given a set of eight assessment options: personal logs, targeted oral examinations, commentaries, mini-lectures, individual explorations, research proposals, book reviews, and problem-solving exercises. Each option had a specific maximum mark (percentage or grade point) associated with it. Students were permitted to select any set of options to obtain their total grade for the course. From the student's perspective, the course provided a valuable learning experience and enabled them to recognize the complexities involved in the process of generating scientific information and making it useful and relevant to the public. The opportunity given to select their own assessment options enhanced their learning. For me, as the sole instructor managing 51 students, the experience was rewarding.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.428
Teacher spread0.406 · 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