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Record W4399488649 · doi:10.22318/icls2024.122460

Applying the Understanding by Design (UbD) Model to Support Critical Thinking and Multidisciplinary Inquiry in the Chinese High School Biology Curriculum

2024· article· en· W4399488649 on OpenAlexaffabout
Xinhua Zhang, Xiaoru Su, Siqi Huang, Huiyu Tian, Jianbin Chen, Renato Gil Gomes Carvalho, James D. Slotta

Bibliographic record

VenueProceedings. · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMultidisciplinary approachCurriculumEngineering ethicsMathematics educationComputer scienceManagement sciencePedagogyPsychologyEngineeringSociologySocial science

Abstract

fetched live from OpenAlex

This paper presents a method of guiding teachers to develop "critical action inquiry" curriculum lessons, using a UbD (Understanding by Design) approach.This method is being developed at South China Normal University, as part of an ongoing collaboration with researchers in the Critical Action Learning Exchange (CALE) project, at the University of Toronto.In this design-based research involving 12 faculty and 92 students, the research team and the pedagogical team accompanied teachers in their development of pedagogical scenarios and use UbD as a framework.We present our application of UbD to the design of a Critical Action Inquiry project called the Dongguan Coastal Flooding project.We show how the design of CALE activities can be guided by UbD, and discuss our next steps for applications with teachers in southern China.

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)0.012
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.011
Scholarly communication0.0050.006
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.093
GPT teacher head0.404
Teacher spread0.311 · 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 designNot applicable
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

Citations1
Published2024
Admission routes2
Has abstractyes

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