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Record W2508964360 · doi:10.1080/03057267.2016.1226573

Trends in research on project-based science and technology teaching and learning at K–12 levels: a systematic review

2016· review· en· W2508964360 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

VenueStudies in Science Education · 2016
Typereview
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsRigourField (mathematics)Educational researchScience educationEngineering ethicsNothingSociologyComputer scienceMathematics educationManagement scienceEpistemologyPsychologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Project-based teaching is nothing new; it originates from the work of authors like Dewey and Kilpatrick. Recent decades have seen renewed interest in this approach. In many countries, it is currently considered to be an innovative approach to science and technology (S&T) teaching. In this article, we present a systematic review of what recent scientific publications teach us about this approach: How is this approach identified in these publications? How is the use of this approach in school S&T justified? What are the main research questions covered by studies in the field? What do these studies on this approach teach us? To answer these questions, we have selected and analysed articles published, between 2000 and 2014, in journals that are specialised in school science and technology education and that are indexed in ERIC database. In the synthesis based on this analysis, we present: (a) the theoretical constructs used by the authors to refer to this approach and the features identified to define it; (b) the justifications for this approach; (c) the research questions covered by studies in the field; (d) the data collection and analysis methods used in these studies; and (e) the main findings. In addition to presenting a synthesis of current research in this field, we offer a critical discussion thereof with a focus on two aspects, namely the way PBSTL is conceptualised and the rigour of the research methods used to ensure the validity of findings.

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)0.074
metaresearch head score (Gemma)0.059
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.848
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0740.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.011
Science and technology studies0.0040.008
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.395
GPT teacher head0.595
Teacher spread0.200 · 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