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Record W4220703600 · doi:10.3102/0013189x221090229

The Effect of Faculty Research on Student Learning in College

2022· article· en· W4220703600 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

VenueEducational Researcher · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsUniversity of Victoria
FundersNational Research University Higher School of EconomicsAll India Council for Technical Education
KeywordsGeneralizability theoryPsychologyEducational researchMathematics educationIdentification (biology)Medical educationMedicine

Abstract

fetched live from OpenAlex

Whether faculty research affects college student learning has long been the subject of debate. Previous studies use subjective measures of student learning; focus on correlation rather than causation; and typically focus on one college, thus lacking generalizability. Using unique, large-scale survey and assessment data that we collected from nationally representative samples of STEM undergraduates in China, India, and Russia, as well as a causal identification strategy that accounts for differential sorting of students to faculty, we present generalizable estimates of the effect of faculty research on objective, standardized measures of student learning. Results show that faculty research has a negative effect on student learning, suggesting direct trade-offs between the university’s dual mission of producing research and 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)0.055
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0550.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.445
GPT teacher head0.661
Teacher spread0.217 · 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