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Record W4311813729 · doi:10.1080/09500693.2022.2146468

Using activity theory as an analytical lens to conceptualise a framework for fostering interdisciplinary science habits in postsecondary students

2022· article· en· W4311813729 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Science Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsToronto Metropolitan UniversityUniversity of CalgaryUniversity of Manitoba
FundersUniversity of ManitobaUniversity of Calgary
KeywordsScience educationConceptual frameworkFocus groupMathematics educationActivity theoryPedagogySociologyPsychologyEngineering ethicsEngineeringSocial science

Abstract

fetched live from OpenAlex

This study presents a conceptual framework for embedding interdisciplinary learning approaches in a postsecondary science program in order to foster interdisciplinary science habits in students. The framework was developed through the lens of a multi-year interdisciplinary postsecondary science program that encompasses a series of courses in which science disciplines are bridged within an authentic science research environment. The validity of the developed framework is supported by the empirical data comprising live experiences of the students obtained through questionnaires, interviews and focus groups. The data were processed and evaluated using content analysis and activity theory. This work provides design principles that will be useful for both program developers and education researchers seeking to launch effective interdisciplinary science programs.

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)0.011
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.413
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0020.001
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 head0.177
GPT teacher head0.567
Teacher spread0.389 · 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