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Record W1568015750 · doi:10.22329/celt.v6i0.3737

19. Evidence in Support of Removing Boundaries to Undergraduate Research Experiences

2013· article· en· W1568015750 on OpenAlexaffvenue
Neil Haave, Doris Audet

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUndergraduate researchDisadvantagedPsychologyAcademic achievementMathematics educationHigher educationMaturity (psychological)Medical educationPrivilege (computing)PedagogyMedicine

Abstract

fetched live from OpenAlex

Undergraduate research is one of several high impact educational practices used by educational institutions to increase student engagement and success (Kuh, 2008). Many studies on the impact of undergraduate research have surveyed students or faculty on their personal experience and its influence on students’ subsequent degrees and employment (Brownell & Swaner, 2010). These studies have documented the ability of high impact educational practices to have the greatest influence on those students who self-identify as belonging to a minority or disadvantaged group. Few studies, however, have documented the impact on students with lower grades. The privilege of being admitted to an undergraduate research experience (e.g., an independent studies course) is typically reserved for upper-year students who have proven themselves academically. This paper presents correlational data from our campus showing that academically weaker students have a greater increase in academic performance between prior grade point average (GPA) and final grade in an independent studies course than academically stronger students. In addition, student annual GPA data shows that the impact of undergraduate research serves to raise student GPA in the year of an independent studies course. Although the findings are based on data from one small campus, they do raise the question that if undergraduate research has the greatest impact on academically weaker students and accelerates academic maturity, is limiting registration into these courses on the basis of superior GPA and years of study placing inappropriate boundaries on student 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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
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 science0.0000.000
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 head0.081
GPT teacher head0.376
Teacher spread0.296 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations5
Published2013
Admission routes2
Has abstractyes

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