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Record W4415986462 · doi:10.21810/sfuer.v14i1.2376

The Implementation of Project-Based Learning in K-12 Education

2021· article· W4415986462 on OpenAlexaffvenue
Bingjie Qi

Bibliographic record

VenueSFU Educational Review · 2021
Typearticle
Language
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsBrock University
Fundersnot available
KeywordsProblem-based learningExperiential learningConstructivist teaching methodsNarrativePerceptionLearning to learnActive learning (machine learning)Face (sociological concept)

Abstract

fetched live from OpenAlex

Project-based learning (PBL) is a constructivist teaching strategy that encourages students to explore real problems and acquire knowledge and skills by adhering to teachers’ guidelines. This study aims to examine the effects of project-based learning on students, and qualities required of K-12 teachers who engage in PBL. This study will use a narrative literature review to synthesize previous findings on the implementation of PBL in primary and secondary levels, and to interpret teachers’ and students’ perceptions regarding project-based learning. This review argues that PBL is beneficial for students in terms of attitudes towards learning and academic performance, as well as the development of practical skills. The review also examines the challenges that teachers may face and the features of highly successful PBL teachers. Based on the results, implications and recommendations are presented.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.433
Teacher spread0.400 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes2
Has abstractyes

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