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Record W3109211628 · doi:10.20961/shes.v3i3.45908

Application of Project Based Learning Models to Improve Student Learning Outcomes in Science Material

2020· article· en· W3109211628 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 educationAction researchLearning cycleCompleteness (order theory)PsychologyProject-based learningComputer scienceMathematics

Abstract

fetched live from OpenAlex

<p><em>This study aims to determine the increase in learning outcomes in science learning through the application of the PjBL model. This research is a classroom action research with 21 students of grade VI SD Margadana 5 Tegal as the subject. This research was conducted in 3 cycles, each cycle of 2 meetings. Each meeting consists of 4 stages, namely planning, implementing, observing and reflecting. Based on the results of the research, in the first cycle, it was obtained an average of 68.09 classical student learning outcomes with 52% student completeness success, and in the second cycle the classical student learning outcomes were 70.47 with the completeness success increasing to 67% and still under the indicators of success. In cycle III, the classical average of student learning outcomes was 83.33 with the success of student completeness increasing to 86% in this case it was more than the 75% achievement indicator. So from cycle I, cycle II and cycle III there is an increase in student learning outcomes. So, in this study it can be concluded that using the PjBL model can improve student learning outcomes in science subjects magnetic and non-magnetic objects.</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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.186
GPT teacher head0.423
Teacher spread0.237 · 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