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Inquiry-Based Learning (IBL) as a Driver of Curriculum: A Staged Approach

2019· article· en· W2933183369 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

VenuePapers on postsecondary learning and teaching. · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCurriculumMathematics educationInquiry-based learningComputer sciencePsychologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Inquiry-based learning provides students with an opportunity to take ownership of their learning while developing important higher order skills necessary for designing innovative solutions to complex modern health problems. In our undergraduate health sciences program, critical thinking, creativity, research skills and innovative thinking are core program learning outcomes, and thus inquiry-based learning is an important pillar of our curriculum. We have taken a staged approach, integrating inquiry-based learning (IBL) into each year of a four-year undergraduate degree program that scaffolds structure and independence to suit undergraduate student needs from the first to third years and culminating in an independent, student-driven honours thesis in the fourth year. In this paper, we share practical IBL strategies that pair with student needs throughout the four-year continuum and highlight strategies to address challenges at each stage of learning.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.298
Teacher spread0.287 · 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