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Record W2803927829 · doi:10.1021/acs.jchemed.7b00852

The Unknown Exercise: Engaging First-Year University Students in Classroom Discovery and Active Learning on an Iconic Chemistry Question

2018· article· en· W2803927829 on OpenAlex
Glen R. Loppnow

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

VenueJournal of Chemical Education · 2018
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Alberta
FundersDirectorate for Biological SciencesUniversity of Alberta
KeywordsMathematics educationPsychomotor learningActive learning (machine learning)TeamworkClass (philosophy)Cooperative learningDiscovery learningChemistryPsychologyLearning cycleGroup workIdentification (biology)Critical thinkingChemistry educationTeaching methodCognitionComputer scienceArtificial intelligenceSocial psychologyEcology

Abstract

fetched live from OpenAlex

Scientific process thinking is usually lacking in first-year post-secondary general chemistry courses, as is a deep discussion of analytical techniques used to determine much of what we know about modern chemistry. A classroom activity is described here that brings the identification and characterization of a chemical unknown into the classroom, emphasizing self-directed, active, and teamwork learning within a social constructivist framework. In this way, the cognitive processes of identifying and characterizing an unknown can be emphasized separately from the psychomotor skills involved in the laboratory. Students work in pairs using self-directed learning to research the separation and characterization methods used by chemists. Each group advocates for a particular method, the class votes, and the instructor carries out the proposed method. The results are shown to the students (but not analyzed for them), and the cycle repeats until the unknown is identified. Students are assessed both individually and as a group. This activity was performed by 20–30 students in each of 3 years within two different first-year general chemistry contexts. Results show enhanced engagement in course and activity material and equivalent learning to lecture-delivered material based on assessment scores.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.008
GPT teacher head0.297
Teacher spread0.289 · 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