MétaCan
Menu
Back to cohort
Record W3108996734 · doi:10.20961/shes.v3i3.46304

Increasing Student Learning Outcomes, the Material Determines the Length of Time used in Everyday Life Through Demonstration Methods

2020· article· en· W3108996734 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

VenueSocial Humanities and Educational Studies (SHEs) Conference Series · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Methods and Outcomes
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics educationEveryday lifeClass (philosophy)PsychologyComputer scienceMathematicsArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

<p><em>Based on the problems that arise in this report, the research objectives that will be achieved through the application of the demonstration method using clock media are to improve mathematics learning outcomes about determining the length of time used in everyday life.</em></p><p><em>in class III This research was conducted at SDN 2 Tegalsumur. This research was conducted through 2 cycles where each cycle consisted of 4 stages, namely planning, implementing, observing / observing, and reflecting. The results of the pre-cycle research with the results: from 18 students only 5 students (29%) obtained complete learning. After the improvement in the first cycle of students who completed learning rose to 14 students (77.78%). improvement of learning cycle II can increase student understanding with the results of achieving completeness to 15 students (83.33%). This increase shows that the methods used in the learning improvement process can improve student learning outcomes.</em></p>

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
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 head0.202
GPT teacher head0.448
Teacher spread0.246 · 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