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Record W2224247626 · doi:10.1021/acs.jchemed.5b00420

Chemical Information Literacy: p<i>K</i><sub>a</sub> Values—Where Do Students Go Wrong?

2015· article· en· W2224247626 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

VenueJournal of Chemical Education · 2015
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInformation literacyLiteracyMathematics educationComputer scienceScientific literacyPsychologyPedagogyWorld Wide WebScience education

Abstract

fetched live from OpenAlex

Chemical information literacy is an essential skillset for navigating, evaluating, and using the wealth of print and online information. Accordingly, efforts are underway to improve students’ acquisition and mastery of this skillset. However, less is known about students’ abilities related to finding and using chemical information to solve problems. We studied students’ abilities in one area of chemical information literacy: finding, estimating, and using p K a values in organic acid–base problems. We identified areas of student difficulty related to these skills, implemented instruction aligned with desired learning outcomes, and then studied students’ success rates after instruction. Our results revealed improvements in some areas but not in others. In particular, students still struggled when the desired information was not directly available in the literature (i.e., data had to be estimated) or when students had to use the information in more complex contexts.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.320
Teacher spread0.308 · 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