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Record W2067958083 · doi:10.1021/ed077p935

Lessons for Introductory Chemistry

2000· article· en· W2067958083 on OpenAlexaff
John S. Martin, E. V. Blackburn

Bibliographic record

VenueJournal of Chemical Education · 2000
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryScience educationMathematics educationEngineering physicsEngineeringPsychology

Abstract

fetched live from OpenAlex

These twelve lessons, and an introductory lesson, are tutorials in basic topics of introductory chemistry. They are suitable for school use, individual study, or distance learning. They are particularly valuable as review material for students in more advanced courses who may have been away from the subject for some time. They contain a great variety of problems and exercises driven by random-number generators, so that the same problem never repeats exactly. The lessons are, for the most part, Socratic dialogues in which the student is required to answer questions and perform simulated experiments in order to discover chemical principles. They are organized in an intuitive chapter and page structure. One may move readily around each lesson. There are many on-screen facilities such as help, data tables, and a calculator. "Chemical Calculations: Combustion Analysis" is one of the 12 modules in Introductory Chemistry Lessons. This screen shows an animation of the combustion of a hydrocarbon. Note the on-screen data table displayed at the bottom of the screen and the on-screen calculator in the lower right corner. Many lessons contain simulations and animations corresponding to those in the previously published Simulations and Interactive Resources ( 1 ). The lessons on the periodic table, oxidation numbers, nomenclature, and reactions will be reinforced by playing the Periodic Table Games ( 2 ). These latter two programs are meant to be coordinated with the lessons. They are now available for free download by Journal subscribers. All of the lessons end with comprehensive review quizzes. It is good strategy for a student to look first at the quiz, to ascertain whether the material of the lesson will be of value, or whether only certain topics are needed. Ten of the quizzes produce scores out of 100. Scores may be recorded in a dataset, and presented in histogram form. There is a "hall of fame" display, which shows the top fifteen scores. The instructor may view the lesson scores or reset the scoreboards. Scores are kept starting on the date of resetting.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.241
Threshold uncertainty score0.805

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.005
Open science0.0020.005
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.2410.167

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 head0.016
GPT teacher head0.328
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

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Citations0
Published2000
Admission routes1
Has abstractyes

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