MétaCan
Menu
Back to cohort
Record W4297133532 · doi:10.32550/teknodik.vi0.962

3 DIMENSIONS OF ANIMATION IN SUPPORTING THE STUDENT INFORMATION PROCESSING

2022· article· en· W4297133532 on OpenAlex
Deni Darmawan

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

VenueJurnal Teknodik · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSTEM Education
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsAnimationMathematics educationComputer scienceInformation processingMultimediaPsychologyComputer graphics (images)

Abstract

fetched live from OpenAlex

This study is a breakthrough in supporting students’ sd, SMP, AND high school in the SouthGarut in performing information processing of learning both for the exact and social. The study tries toanswer the question of how large the focus of information-processing speed of the student learningbased on element formation 3dimensi animation on the exact and social subjects (IPS). The study wasconducted on students at elementary, junior high, and high school. The study was conducted by usingthe method of research and development carried out experiments in which this research is consideringthe second year in which the CAI instructional model and formation animation 3dimensi been designedbefore. The study was conducted at the elementary school level, junior high, and high school located inthe southern Garut, with through stratified random sampling. The results showed that the speed ofinformation processing of learning both exact and social groups (IPS) conducted junior high schoolstudents were more superior than the elementary or high school students, through Computer AssistedInstruction teaching model loaded with animation 3dimensi formation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.373
Teacher spread0.346 · 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