MétaCan
Menu
Back to cohort
Record W2616249471 · doi:10.18260/1-2--14619

Same Course, Two Methods Of Learning : Assessment Of The Students Success

2020· article· en· W2616249471 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMathematics educationCourse (navigation)Computer scienceAutodidacticismPoint (geometry)Artificial intelligencePsychologyMathematicsEngineering

Abstract

fetched live from OpenAlex

This paper discusses the implementation of a self-directed learning strategy for instruction in an introductory materials science course. Student's performance metrics are directly compared to those from a more traditional lecture-oriented course. The raw data reveal that the students who have chosen the self-directed learning version of the course obtain a final mark higher than that obtained by the students who were taught in a conventional manner . Multivariable analysis taking into account the GPA of the students, their level at their entry in the engineering program, the mark obtained in the common final exam and that obtained in quizzes were performed in order to point out the most influencing factor(s). It appears that the difference in student's success is mostly due to a better performance of the self-directed learning students in the continuous evaluation by computerised quizzes, the other variables having a negligible effect. We conclude that the main cause of the higher success of the self-directed learning students in the course should probably be the consequence of their attitude toward their responsibility in the learning process.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.382
Teacher spread0.366 · 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

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicExperimental Learning in EngineeringFrench-language works237,207