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Record W3080543791 · doi:10.5430/ijhe.v9n6p64

Assessing scientific literacy skill perceptions and practical capabilities in fourth year undergraduate biological science students

2020· article· en· W3080543791 on OpenAlexafffundvenue
Nadia M. Cartwright, Danyelle M. Liddle, Benjamin G. Arceneaux, Genevieve Newton, Jennifer M. Monk

Bibliographic record

VenueInternational Journal of Higher Education · 2020
Typearticle
Languageen
FieldPsychology
TopicEducational Strategies and Epistemologies
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsPerceptionPsychologyMedical educationScientific literacyMathematics educationInformation literacyLiteracyScience educationPedagogyMedicine

Abstract

fetched live from OpenAlex

In a fourth year undergraduate nutritional toxicology course that included an instructional emphasis on scientific literature critique activities and assessments, we determined the change in students’ (n=144) scientific literacy (SL) skills. The change in students’ perceived and practical SL skills were determined by the completion of two surveys, administered at the start and end of the semester. Additionally, we conducted a follow-up SL survey at the end of the subsequent academic semester (i.e., four months later) to determine if students retained any improvements in their SL skills. Over the semester, students showed improvements in their perceived capabilities of all SL skill parameters assessed (P<0.05); however, the most significant gains were apparent in the areas of i) knowledge application (specifically identifying novel problems or research questions and using new information to address unfamiliar problems or knowledge gaps), and ii) knowledge translation and communication (translating complex information from the scientific literature into clear and understandable terms). There was no change in students TOSLS score between the start and end of the semester (P>0.05). In the follow-up SL survey students showed further improvements in their perceptions of the SL skills for 7 or the 10 parameters assessed compared to the end of the previous semester (P<0.05), however, there remained no change in their practical SL skills assessed using TOSLS. Collectively, these data demonstrate that students’ perceptions of their SL capabilities may not align with their practical capabilities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.086
GPT teacher head0.486
Teacher spread0.399 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations16
Published2020
Admission routes3
Has abstractyes

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